Highly Energetic Al/Cuo Thermite Coatings Through Nanoparticle Composites

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DISS. ETH NO. 27006

Highly energetic Al/CuO thermite coatings through nanoparticle composites

A thesis submitted to attain the degree of

DOCTOR OF SCIENCE of ETH ZURICH (Dr. sc. ETH Zurich)

Presented by LARS EMIL DÖRNER M. Sc. Chemistry, University of Munich

Born on 11.12.1990 Citizen of Germany

Accepted on the recommendation of Prof. Dr. Maksym V. Kovalenko, examiner Prof. Dr. Markus Niederberger, co-examiner

2020

Declaration

I hereby confirm that I am the sole author of the written work herein enclosed and that I have compiled it in my own words. Parts excepted are corrections of form and content by the supervisors.

Title of work:

Highly energetic Al/CuO thermite coatings through nanoparticle composites

With my signature I confirm:

− I have committed none of the forms of plagiarism. − I have documented all methods, data and processes truthfully. − I have not manipulated any data. − I have mentioned all persons who were significant contributors to this work, as described below. − I have obtained copyright permissions from the journal for reproducing the text and Figs. in this thesis, where needed. − I am aware that the work may be screened electronically for plagiarism.

Place, date: Dübendorf, 01. August 2020 Signature

Dr. Bastian Rheingans carried out TEM analysis for Chapters 3, 4 and 5.

Dr. Luchan Lin contributed by FIB, TEM, STEM characterization in Chapter 6.

Dr. Sebastian Siol supported the projects by PVD coating of electrodes used in Chapters 4, 5 and 6.

Acknowledgements

First of all, I would like to thank my supervisors Dr. Lars P.H. Jeurgens and Prof. Dr. Maksym V. Kovalenko for the great opportunity to do my PhD at Empa and for supporting me and my project for several years. Lars, I always appreciated your advice, ideas and support and I will miss our weekly meetings. I would also like to thank Maksym for his continuous support and input. Thank you for giving me and my glovebox a home for the last four years even though space was tight.

I am thankful to Prof. Dr. Markus Niederberger for being a co-examiner of this thesis. I would like to thank all members of the examination committee for their time and effort.

Thanks to all current and former lab members of the Joining Technology and Corrosion group as well as the Kovalenko group at Empa. I did not only enjoy doing science with you but also like to thank you for nice discussions over lunch or coffee. I am very grateful to Patrik for teaching and showing me the possibilities of electrochemistry and his continuous help and support. Thanks to Claudia for always helping out with my XRD questions. I would like to specially mention Sebastian, Noemi and Bastian for their assistance and friendship.

I would like to thank Ralf Kägi for letting me use some crucial instruments at EAWAG and for fruitful help and discussions.

Last but not least, special appreciation belongs to my family for supporting me no matter on what journey I embark and for always being there when needed. I’m very grateful for my wife Kerstin, for always being at my side. I wouldn’t be where I am now without you. I would also like to thank my daughter Emilie for making breaks from writing very enjoyable with big smiles and giggles.

Table of Contents

Chapter 1. Introduction ...... 1

1.1 Overview of nanotechnology...... 1

1.2 Key inventions in the field of nanotechnology ...... 3

1.3 Nanocomposites ...... 5 1.3.1 Ceramic matrix nanocomposites ...... 6 1.3.2 Polymer matrix nanocomposites ...... 7

1.4 Metal Matrix Nanocomposites ...... 7 1.4.1 Synthesis routes for fabrication of metal matrix nanocomposites ...... 8 1.4.2 Major Applications of MMNCs ...... 9

1.5 Reactive nanocomposites...... 10 1.5.1 Development of reactive nanomaterials ...... 11 1.5.2 Production of nanothermites by arrested reactive milling ...... 13 1.5.3 Challenges in nanothermite research and application...... 14

1.6 Scope and outline of the dissertation ...... 15

Chapter 2. Methods and Techniques ...... 19

2.1 Preparatory methods ...... 19

2.2 Analytical Techniques...... 21

Chapter 3. Cost-effective sol-gel synthesis of porous CuO nanoparticle aggregates with tunable specific surface area ...... 31

3.1 Introduction ...... 31

3.2 Experimental section ...... 33

3.3 Results and discussion ...... 36

3.4 Conclusion ...... 52

Chapter 4. Electrophoretic deposition of nanoporous oxide coatings from highly-concentrated CuO nanoparticle dispersions...... 54

4.1 Introduction ...... 54

4.2 Experimental section ...... 57

4.3 Results and discussion ...... 61

4.4 Conclusions ...... 77

Chapter 5. Electrophoretic Deposition of Cupric Oxide Coatings with Tailored Nanoporosity by Nanoparticle Aggregate Design ...... 79

5.1 Introduction ...... 79

5.2 Experimental section ...... 81

5.3 Results and discussion ...... 85

5.4 Conclusion ...... 100

Chapter 6. Advanced manufacturing of energetic metal-matrix Al/CuO thermites nanocomposites with pristine interfaces by CuO electrophoretic deposition and Al electrodeposition infiltration ...... 103

6.1 Introduction ...... 103

6.2 Experimental section ...... 107

6.3 Results and discussion ...... 110

6.4 Conclusion ...... 122

Chapter 7. Conclusions and Outlook ...... 124

7.1 Conclusions ...... 124

7.2 Outlook ...... 125

References ...... 127

Appendix A: Abbreviation list ...... 148

Appendix B: Curriculum Vitae ...... 149

Appendix C: List of publications ...... 151

Appendix D: List of presentations ...... 152

Summary

Metal matrix nanocomposites are functional nanomaterials with exceptional properties as compared to their bulk counterparts, including increased strength and durability as well as enhanced conductivity depending on the properties of the reinforcing nanoscale components. Yet, despite their enormous potential for application e.g. in the automotive, aerospace and electronics sector, the use of these nanocomposites is so far limited due to their often complex and expensive production routes. This is particularly true for highly energetic (so-called reactive or thermite) nanocomposites, as composed of a "fuel" (e.g. Al, Ti, Zr) and "oxidizer"

(e.g. Fe2O3 or CuO). Namely, delicate fabrication procedures are needed to prevent unwanted exothermic reactions of the reactive phases during the preparation and processing steps. With their ability to sustain self-propagating high-temperature synthesis (SHS) reactions, nanothermites, as prepared in the form of e.g. nanocomposite or nanomultilayer pastes or foils, can serve as a customized local heat source for joining of a wide variety of dissimilar and heat-sensitive materials. However, research, innovation and application of this novel group of highly reactive materials is still constrained by the availability of SHS systems that provide a sufficient heat of reaction and can also be easily produced in an environmental way, at large scale and at low costs. To address these ultimate challenges, a novel green and cost-effective, high-quality production procedure for Al-based reactive nanocomposites was developed in this thesis. The potential of such reactive nanocomposites for applications in the fields of joining, combustion and propellants has been illustrated by the preparation of highly exothermic Al/CuO nanofoils

To allow economic, green, facile and scalable production of CuO nanoparticles for the production of the Al/CuO nanocomposites, a sol-gel synthesis method was adopted. Using copper acetate and ammonia carbonate as starting materials, submicron-sized nanoporous CuO nanoparticle (NP) aggregates (100 - 140 nm) were fabricated via a copper-carbonate containing precursor. The produced CuO aggregates contain crystallites with tunable shape and size in the range of 20 - 40 nm. By varying the starting conditions (pH and carbonate concentration), the nanoporosity and specific surface area of the micron-sized NP aggregates could be adjusted.

As a next step, different in-house produced and commercially-available CuO nanopowders were employed to prepare micrometer-thick nanostructured scaffolds by electrophoretic deposition (EPD), which can be subsequently electrochemically infiltrated with Al to obtain an energetic Al/CuO nanocomposite. To obtain suitable nanoporous CuO scaffolds for Al

infiltration, the CuO NP dispersion properties were tailored for the EPD step. To this end, a systematic investigation was performed of the electrophoretic mobilities and size distributions of dispersed CuO aggregates and agglomerates in different organic solvents for concentrations ranging from 50 to 5000 mg/L with and without surfactant addition, as guided by Dynamic Light Scattering (DLS) and Zeta potential measurements. The size, shape, phase purity and effective surface area of various in-house synthesized and commercially available CuO nanopowders were analyzed using SEM, TEM, BET and XRD. From these different nanopowders, dispersions with varying CuO NP concentrations in the range of 50 - 10000 mg/L were prepared using ethanol as a solvent and adding 5 wt.% acetylacetone as surfactant. The dispersion properties (particularly, the kinetics of NP aggregation and agglomeration, the effective particle mobility and dispersion conductivity) were investigated by DLS and Zeta potential investigations. The EPD process was tuned to produce nanoporous CuO coatings with different thicknesses, morphologies and porosities from the concentrated dispersions (5000 mg/L and 10000 mg/L), as characterized by SEM, profilometry and BET. It followed that the coating thickness is mainly governed by the size distribution of the aggregates, whereas the porosity of the formed scaffold is mainly determined by the morphology of the aggregates. A net attractive (electrostatic) particle-particle interaction is required to promote homogenous layer formation during the EPD step. Moreover, especially for larger electrode distances, a high effective particle mobility is crucial for successful electrophoretic deposition. The effective mobility is tightly linked to the aggregation and agglomeration behavior of the dispersion, which in turn is strongly influenced by the size, concentration and surface charge of the dispersed NP aggregates.

Finally, micrometer-thick nanoporous CuO scaffolds were fabricated according to the optimized procedures and electrochemically infiltrated with Al from the ionic liquid

BMImCl*AlCl3. The conditions and parameters for electrochemical infiltration were optimized by changing the deposition current, speed and pulse cycles, as guided by cross-sectional SEM analysis of the produced nanocomposites. Using the thus-optimized infiltration parameters (i.e. short high-current pulses with long restoration durations), dense Al/CuO composites were successfully produced. Importantly, the formation of interfacial AlOx reaction layers between the CuO nanoporous scaffold and the Al infiltrate, which would hamper the reactivity of the thermite nanocomposite, could be prevented. The nanocomposites exhibited a pristine Al/CuO interface, as confirmed by EM, SEM and XRD. DSC analysis revealed that the produced Al/CuO composite with an Al/CuO ratio of 1.6 reacted at 585 °C with an exothermic heat release as large as 1 kJ/g.

While the novel method for the production of reactive nanocomposites presented in this thesis was demonstrated for a specific combination of materials, it can easily be adopted for other material systems.

iii

Zusammenfassung

Metall-Matrix-Nanokomposite sind funktionelle Nanomaterialien mit aussergewöhnlichen Eigenschaften im Vergleich mit ihren oberflächenärmeren Grundmaterialien, einschliesslich erhöhter Festigkeit und Strapazierfähigkeit aber auch gesteigerter Leitfähigkeit abhängig von den Eigenschaften der eingebrachten Nanokomponenten. Trotz ihres enormen Anwendungspotentials zum Beispiel in der Automobil-, Raumfahrt und Elektronikindustrie, ist die Verwendung dieser Nanokompositen bisher eingeschränkt wegen ihrer oft komplexen und teuren Fertigungsabläufe. Dies trifft im besonderen Masse auf hoch energetische (sogenannte Reaktiv- oder Thermit-) Nanokomposite zu, die aus einem “Brennstoff” (z.B. Al, Ti, Zr) und einem “Oxidationsmittel” (z.B. Fe2O3 oder CuO) bestehen. Genauer gesagt, braucht es feinfühlige Herstellungsverfahren um ungewünschte exotherme Reaktionen der reaktiven Phasen während der Herstellungs- und Verarbeitungsschritte zu verhindern. Mit ihrer Fähigkeit, selbst ausbreitende Hochtemperatursynthesereaktionen (SHS) aufrechzuerhalten, können Nanothermite, wie sie in Form von z.B. Nanokomposit- oder Nanomultilayer, Pasten oder Folien hergestellt wurden, als maßgeschneiderte lokale Wärmequelle zum Verbinden einer Vielzahl unterschiedlicher und wärmeempfindlicher Materialien dienen. Forschung, Innovation und Anwendung dieser innovativen Gruppe hochreaktiver Materialien sind jedoch immer noch durch die Verfügbarkeit von SHS-Systemen eingeschränkt, die eine ausreichende Reaktionswärme liefern und auch auf umweltfreundliche Weise, in großem Maßstab und zu geringen Kosten leicht hergestellt werden können. Um diesen ultimativen Herausforderungen zu begegnen, wurde in dieser Arbeit ein neuartiges, umweltfreundliches, kostengünstiges und qualitativ hochwertiges Produktionsverfahren für reaktive Nanokomposite auf Al-Basis entwickelt. Das Potenzial solcher reaktiven Nanokomposite für Anwendungen in den Bereichen des Fügens, der Verbrennung und der Treibmittel wurde durch die Herstellung hochexothermer Al / CuO-Nanofolien veranschaulicht.

Um eine wirtschaftliche, grüne und leicht skalierbare Produktion von CuO-Nanopartikeln für die Herstellung der Al/CuO-Nanokomposite zu ermöglichen, wurde ein Sol-Gel- Syntheseverfahren angewandt. Unter Verwendung von Kupferacetat und Ammoniumcarbonat als Ausgangsmaterialien wurden submikrongroße nanoporöse CuO-Nanopartikel (NP)- Aggregate (100-140 nm) über eine kupfercarbonathaltige Vorstufe hergestellt. Die hergestellten CuO-Aggregate enthalten Kristallite mit einstellbarer Form und Größe im Bereich von 20-40 nm. Durch Variation der Ausgangsbedingungen (pH-Wert und Carbonat- konzentration) konnte die Nanoporosität und die spezifische Oberfläche der mikro- metergroßen NP-Aggregate eingestellt werden.

Im nächsten Schritt wurden verschiedene selbst hergestellte und kommerziell erhältliche CuO- Nanopulver verwendet, um durch elektrophoretische Abscheidung (EPD) mikrometerdicke nanostrukturierte Gerüste herzustellen, die anschließend elektrochemisch mit Al infiltriert werden können, um ein energetisches Al/CuO-Nanokomposit zu erhalten. Um geeignete nanoporöse CuO-Gerüste für die Al-Infiltration zu erhalten, wurden die CuO NP- Dispersionseigenschaften für den EPD-Schritt optimiert. Zu diesem Zweck wurde eine systematische Untersuchung der elektrophoretischen Beweglichkeit und Größenverteilungen von dispergierten CuO-Aggregaten und Agglomeraten in verschiedenen organischen Lösungsmitteln für Konzentrationen im Bereich von 50 bis 5000 mg/L mit und ohne Tensidzusatz durchgeführt, die sich an Messungen der Dynamischen Lichtstreuung (DLS) und des Zeta-Potenzials orientierte. Die Größe, Form, Phasenreinheit und effektive Oberfläche verschiedener intern synthetisierter und kommerziell erhältlicher CuO-Nanopulver wurden mittels REM, TEM, BET und XRD analysiert. Aus diesen verschiedenen Nanopulvern wurden mit Ethanol als Lösungsmittel und unter Zugabe von 5 Gew.-% Acetylaceton, als Tensid, Dispersionen mit unterschiedlichen CuO NP-Konzentrationen im Bereich von 50 - 10000 mg/L hergestellt. Die Dispersionseigenschaften (insbesondere die Kinetik der NP-Aggregation und -Agglomeration, die effektive Partikelmobilität und die Leitfähigkeit der Dispersion) wurden durch DLS- und Zeta-Potentialuntersuchungen erforscht. Der EPD-Prozess wurde so abgestimmt, dass aus den konzentrierten Dispersionen (5000 mg/L und 10000 mg/L) nanoporöse CuO-Beschichtungen mit unterschiedlichen Schichtdicken, Morphologien und Porositäten hergestellt werden können, die durch REM, Profilometrie und BET charakterisiert wurden. Daraus ergab sich, dass die Schichtdicke hauptsächlich durch die Größenverteilung der Aggregate gesteuert, während die Porosität des gebildeten Gerüstes hauptsächlich durch die Morphologie der Aggregate bestimmt wird. Um eine homogene Schichtbildung während des EPD-Schrittes zu fördern, ist eine netto-anziehende (elektrostatische) Partikel-Partikel- Wechselwirkung erforderlich. Darüber hinaus ist insbesondere bei größeren Elektroden- Abständen eine hohe effektive Partikel-Beweglichkeit entscheidend für eine erfolgreiche elektrophoretische Abscheidung. Die effektive Mobilität ist eng mit dem Aggregations- und Agglomerationsverhalten der Dispersion verbunden, das wiederum stark von der Größe, Konzentration und Oberflächenladung der dispergierten NP-Aggregate beeinflusst wird.

Schließlich wurden nach den optimierten Verfahren mikrometerdicke nanoporöse CuO- Gerüste hergestellt und elektrochemisch mit Al aus der ionischen Flüssigkeit BMImCl*AlCl3 infiltriert. Die Bedingungen und Parameter für die elektrochemische Infiltration wurden durch Änderung des Abscheidestroms, der Geschwindigkeit und der Impulszyklen optimiert, wobei die REM-Querschnittsanalyse der hergestellten Nanokomposite als Grundlage diente. Mit den

so optimierten Infiltrationsparametern (d.h. kurze Hochstrompulse mit langer Wiederherstellzeit) konnten dichte Al/CuO-Komposite erfolgreich hergestellt werden. Wichtig ist, dass die Bildung von AlOx-Grenzflächen zwischen dem nanoporösen CuO-Gerüst und dem Al-Infiltrat, welche die Reaktivität des Nanothermitkomposit hemmen würde, verhindert werden konnte. Die Nanokomposite wiesen eine reine Al/CuO-Grenzfläche auf, wie durch TEM, REM und XRD bestätigt wurde. Die DSC-Analyse ergab, dass das hergestellte Al/CuO- Komposit mit einem Al/CuO-Verhältnis von 1.6 bei 585°C mit einer exothermen Wärmeabgabe von bis zu 1 kJ/g reagierte.

Während die in dieser Arbeit vorgestellte neuartige Methode zur Herstellung reaktiver Nanokomposite für eine spezifische Materialkombination demonstriert wurde, kann sie leicht für andere Materialsysteme übernommen werden.

Chapter 1. Introduction

In 1965 Gordon Moore made the observation, that the number of transistors in a dense integrated circuit doubles every two years.1 While Moore's law reached its limit in 1998 when a threshold in transistor size was slowly reached, miniaturization in general is continuing.2,3 The steady reduction in size of components and devices brings new challenges to assemble systems with ever-smaller building blocks. In microelectronics and many other fields microjoining has been an integral part of the manufacturing process for many decades but faces challenges of the advancing miniaturization reaching the nanoscale. Due to many years of significant progress in nanoscience and technology, as well as the diversification and increased complexity of materials, the need for nanojoining technologies is steadily increasing. In brief, the emerging field of nanojoining deals with the joining of and with nanomaterials. Hence, the field of nanojoining is not only confronted with the challenges to assemble and interconnect nanoscale building blocks, such as nanowires and nanotubes to form nanoscale devices and systems. It also addresses the design and fabrication of novel nanostructured joining materials to enable benign joining of a wide range of dissimilar materials at ever-lower temperatures, which was the focus in this PhD thesis. The development of low cost, reliable and high performance micro- and nano-joining techniques is essential for industrial scale production of micro- and nano-scale devices.4

1.1 Overview of nanotechnology

The word "nano" describes a 10-9 fold value reduction and has its origins in the Greek language. It is considered to be the smallest dimensional scale at which humans can assemble and manipulate structures. Simultaneously, it is the dimension at which the largest molecules of living systems exist. “Nanotechnology” is a collective term describing the study and manipulation of objects within the size range from 1 to 100 nm. Today, nanotechnology includes research and applications in the fields of chemistry, physics, material science, engineering as well as biology and pharmacy. Nanomaterials exhibit special properties in comparison to their bulk counterparts. In the nanosize range, surface and/or interface properties influence the behavior of a material more strongly than its volume. In addition, quantum physical effects play an increasing role.

The first use of nanoparticles (NPs) dates back to the 14th and 13th centuries BCE to ancient Egypt where metallic copper or cuprous copper oxide nanoparticles were used to stain glass red.5 Since then metallic NPs have been unknowingly employed for their specific optical properties in many famous art pieces such as the Lycurgus Cup,6,7 the “Famille Rose”

porcelain8 and a vast range of stained glass windows.9,10 While the procedures to create such materials were known, the mechanisms underlying the different colorations were uncovered much later.

The scientist Richard Adolf Zsigmondy was one of the first to observe and measure the size of NPs.11 He investigated colloidal gold NPs as small as 10 nm using an ultra-microscope, which was capable of visualizing particles much smaller than the light wavelength, for which he was awarded the Nobel Prize in Chemistry in 1925. Reportedly, he was also the first to use the term "nanometer" to characterize the observed particle sizes. During the early 20th century, research on processes and phenomena governing material behavior in the nanorange started to boom.

The birth of nanotechnology as we know it today is said to be the famous lecture of Richard P. Feynman "There’s plenty of Room at the Bottom" in 1959 in which he envisioned to use machines to produce smaller machines down to the molecular level. Even though miniaturization had already taken great steps, he proclaimed scientists had not gone far enough. 'Why cannot we write the entire 24 volumes of the Encyclopaedia Britannica on the head of a pin?' is one of the famous quotes from his speech.12 In the following years revolutionary developments in physics, chemistry, and biology allowed tailoring and controlling matter at the level of molecules and atoms. A few years later in 1974 Norio Taniguchi, a Japanese scientist and engineer, first coined the term “nanotechnology”.13

US National Science and Technology Council today states three criteria in their definition of nanotechnology/nanoscience:

Dimension: at least one dimension 1–100 nanometers (nm)

Process: designed with methodologies that show fundamental control over the physical and chemical attributes of molecular-scale structures.

Building block building blocks can be combined to form larger structures.14 property:

The two terms nanoscience and nanotechnology need to be distinguished. Nanoscience on the one hand focuses on the design and manipulation of the materials e.g. the building blocks on an atomic or molecular level and studies the occurring phenomena such as optical and electronic properties. Nanotechnology on the other hand addresses the assembly of such nanomaterials as well as their analysis and characterization.

Manufacturing approaches for nanotechnology can be classified as either "top-down" and "bottom-up", which were introduced in detail by Drexler et al.15–17 The "bottom-up" method is defined as the (self)-assembly of machines from their basic chemical building blocks, which is often used in chemistry for example (Fig. 1.1). In contrast, the "top-down" procedure employs larger devices to assemble smaller components.

Figure 1.1 Illustration of ‘‘top-down” and ‘‘bottom-up” approaches in nanotechnology.

1.2 Key inventions in the field of nanotechnology

After Feynman's innovative lecture, several disciplines engaged in the field of nanotechnology. First major inventions and discoveries let, for example, to the development of new approaches in transistor design, resulting in the transition from microelectronics to nanoelectronics. In the 1960s, the first metal-oxide-semiconductor field-effect transistors (MOSFETs) were developed.18,19 While the first transistors of this type had a gate oxide thickness of 100 nm, in 2006 a Korean research team developed the world's smallest nanoelectronic device up to date, a 3 nm MOSFET.20 Being the most important transistor technology to date, this basic building block is one of the most frequently produced devices in history, with an estimated production of 1.3x1022 MOSFETs between 1960-2016.21,22

In the early 1980s, two major developments boosted nanotechnology and nanoscience: the characterization and tailoring of nanoclusters (e.g. fullerenes and colloidal nanocrystals) and the invention of the scanning tunneling microscope (STM).23 The development of the STM in 1981 allowed scientists to visualize individual atoms and molecules for the first time. Five years later the inventors of the STM, Binnig and Rohrer, were awarded the Nobel Prize in Physics. The instrument reformed nanotechnology, allowing researchers to view and manipulate

materials and surfaces in unprecedented ways. Using the concept of quantum tunneling, STMs employ a conducting tip, which is positioned in extremely close distance to the examined surface. The electrical current flowing between tip and surface (for a given applied potential between the tip and the sample surface) is measured, providing information about the inner structure and height relief of the surface (Fig. 1.2). Today STMs have 0.1 nm lateral resolution and 0.01 nm depth resolution. Based on STM technology, Binnig also developed atomic force microscope (AFM), allowing the imaging of nonconductive materials.24

Figure 1.2 Schematic representation of the basic STM setup.

Another milestone in nanotechnology was the discovery and synthesis of colloidal semiconductor nanocrystals, so called quantum dots in 1983.25–30 These semiconductors with a size of 2-20 nm have intermediate optical and electronic properties compared to bulk semiconductors or discrete molecules. Their optoelectronic properties change as a function of both size and shape. Smaller quantum dots follow the basics of quantum mechanics more strongly than larger ones, which have a bigger spectrum-shift towards red. Due to their high extinction coefficient, these nanoparticles are particularly promising for optical applications such as high- efficiency photovoltaics and lighting.

Nanotechnology is also used to develop nanostructured materials. Two examples are the catalytic materials MCM-41 and MCM-48, which were discovered in 1992 and are now used in water treatment or oil refineries.31,32 Several additional nanomaterials with regular pore systems have been developed for example zeolites, nanoporous organic or organometallic materials and metallophosphates.33 For catalysis, surface reactivity is the key criterion.

Therefore, a higher surface area, with an increased number of edges and corners is generated to reach a high concentration of coordinatively unsaturated sites e.g. by introducing unusual surface morphologies, surface defects or unusual electronic sites. The surfaces can be altered using grafting and/or tethering of organic or organometallic species or manipulated by deposition procedures.34 These alterations can induce special chemical and physical properties using size effects. Besides catalysis, nanostructured materials with modified surfaces find application in separation and environmental remediation.35

An important tool for top-down nanotechnology is nanolithography. In 1960 Möllensted and Speidel demonstrated the first electron beam lithography (EBL) process by writing of submicron sized characters using and electron optical microrecorder.36 Led by IBM, already during the 1970s big industrial companies have adapted EBL for their processes.37 A focused electron beam is used to trace out a pattern on a thin organic polymer film. The recording medium, also called resist, is then applied as a binary mask for further processing steps such as reactive ion etching, electroplating or physical vapor deposition.38,39

1.3 Nanocomposites

A rapidly growing field in nanotechnology are nanocomposites. By definition, nanocomposites are heterogeneous materials with several phases. At least one of these phases has one, two or three dimensions in the nanoscale range (less than 100 nm). This usually means that a solid-state matrix is combined with one or more nanodimensional phases. However, nanocomposites can also be gels, colloids or copolymers and they can consist of repeats of materials with nanoscale repeat distances.40 Depending on the matrix material, nanocomposites are classified as ceramic matrix nanocomposites (CMNC), metal matrix nanocomposites (MMNC) and polymer matrix nanocomposites (PMNC), in addition, carbon nanotubes (CNT) reinforced systems exist.41–43

Nanocomposites are developed as high performance materials with unique design possibilities and unprecedented combinations of properties (e.g. thermal, mechanical, electrical, optical, catalytical). Importantly, the properties of the nanocomposite generally differ from the properties of its individual components. Kamigaito et al. proposed size limitations for various properties under which these change significantly:44 less than 5 nm for catalytic activity; less than 20 nm for making a hard magnetic material soft; less than 50 nm for refractive index changes; less than 100 nm for mechanical strengthening and toughening, producing superparamagnetism or modifying hardness and plasticity. One of the key features of nanocomposites is the high density of internal interfaces, which can be varied by changing the concentration, size and shape of the imbedded nanoparticles.45,46

Like nanomaterials in general, nanocomposites can be produced using either bottom-up or top-down processes. For the production of materials with specific properties, the choice of method can be crucial. This is exemplified in Figure 1.3 for the production of a silicate polymer nanocomposite. In the bottom-up approach, nanosized objects are mixed and then grow and generate the desired well-organized material. In contrast, top-down approaches start with bulk material, which is broken down physically into smaller pieces which are mixed and form the nanocomposite.

Figure 1.3: Schematic representation of bottom up and top down approaches for the production of polymer nanocomposites. Modified from Tewarti et al.47

1.3.1 Ceramic matrix nanocomposites

A wide range of CMNCs material systems exist including Al2O3/SiC, SiO2/Ni, TiO2/Al2O3 and ZnO/Co which have been described in more detail in several reviews Refs48–50. CMNCs find application amongst others as optical amplifiers,51 structural materials,52 catalysts53 and have also gained momentum in the biomedical54,55 field.

The variety of methods employed to produce CMNCs is highlighted by different studies on 56 57,58 Al2O3/SiC: besides sol-gel synthesis, polymer precursors or simple powder 56,59,60 processes have been described. For incorporation of CNTs into SiO2 and SiC based composites, hot pressing sintering can be performed after mixing of the components.61,62 A novel procedure for reinforcement of high performance SiC ceramic nanocomposites with single-walled CNTs is based on the functionalization of CNTs. These are then mixed with precursors and pyrolyzed for the fabrication of the nanocomposite.52

1.3.2 Polymer matrix nanocomposites

A broad range of polymer-based nanocomposite systems have been developed. While sol-gel processes are also most commonly used to produce PMNCs, several other synthesis methods exist including intercalation processes63 (melt intercalation, in-situ intercalative polymerization and the usage of prepolymers from solution), template synthesis by mixing or in-situ polymerization.42 Numerous reviews describe properties and applications of PMNCs.64–66 The wide range of applications of these nanocomposites can be highlighted with the example of ZnO based PMNCs. These can function as energy storage in the form of supercapacitors as demonstrated with ZnO@amorphous ZnO-doped MnO2 core-shell nanocables with PVA/LiCl as electrolyte67 and PPy/graphene oxide/ZnO nanocomposites with PVA as electrolyte.68 ZnO surface-patterned Nafion shows great potential as a tool for harvesting energy as it can achieve a power density of 0.95 W/cm2 compared to 0.59 W/cm2 for non-patterned Nafion.69 The energy harvesting ability of ZnO PMNCs was also illustrated with ZnO nanowires incorporated in polycarbonate templates achieving a conversion efficiency of ~4.2%. ZnO/polymer nanocomposites show promising results as semiconductors applicable in optical and electrical devices with a high tuneability.70 By doping ZnO thin films with Al the band gap energy could be adjusted from 3.276 eV for 0 at.% Al to 3.294 eV for 3 at.% Al. In addition, polymer- based nanocomposites containing ZnO find application in the sensor industry as well as in the biomedical field. A great overview on synthesis, characterization and application of ZnO containing polymer based nanocomposites is given by Ponnamma et al.71

1.4 Metal Matrix Nanocomposites

Particle reinforced metal matrix composites (MMCs) are widely used materials due to their excellent combination of thermal stability, ductility and strength compared to fiber or flake reinforced composites.72–74 Today MMCs are mainly used as structural elements in the automotive, aerospace and military industry. The wish for custom-made materials with specific properties, including light weight and high performance, has propelled research on MMCs. More recently MMNCs have gained momentum due to their edge over conventional MMCs. Nanoscale reinforcements provide great improvements in terms of wear resistance, mechanical strength and damping properties, making them more attractive for broader use. Yet, regardless of their better performance characteristics, MMNCs have limited applications so far due to the complex processing and inadequate economic efficiency of their production.

Carbon nanotube metal matrix composites (CNT-MMNC) are also a very active field of research. In comparison to other carbon nanotube materials, CNT-MMNCs often have higher tensile strength and better electrical conductivity. In addition, boron nitride and carbon nitride reinforced MMNCs are actively investigated.75 The most common MMNCs use Al, Mg, Cu, Ti or Ni as well as their alloys as matrix metal72,76,85,86,77–84 which is reinforced with materials such 82 78 81 87 88 89 as SiC, TiO2, Al2O3, B4C, Y2O3, or Si3N4.

1.4.1 Synthesis routes for fabrication of metal matrix nanocomposites

Production methods of MMNCs can be grouped into three categories: solid-state, semi-solid and liquid methods.90 Solid-state methods include powder metallurgy where metal powder and reinforcement are first mixed and then bonded by compaction and sintering.91 A similar powder based method is mechanical alloying which uses a cycle of mixing through high-energy ball milling, cold-welding and fracturing to create the composite material.92 One of the key advantages of the high-energy ball milling process is its high productivity and ability to produce nanocomposites of metals and alloys with high melting temperatures. The drawback is the non-uniformity of the produced nanoparticles. By repeated fracturing and reformation in the metal alloying process, this weakness can be compensated.93 Other methods include diffusion bonding94 and physical vapor deposition,95 which also can be combined with powder metallurgy or mechanical alloying. A novel technique is the accumulative fold-forging in which cumulative layers are bonded through repetitive folding and subsequent forging. By adding the reinforcement materials in-between the folding processes a metal matrix nanocomposite is produced.87 Compocasting96 and thixoforging97 are two examples of semi-solid fabrication methods, which are not used very frequently.

Figure 1.4 Schematic representation of a stir casting setup.

Liquid fabrication processes include stir casting (as shown in Fig. 1.4), squeeze casting, electroplating/ electroforming and spray deposition. For stir casting, the discontinuous reinforcement, often ceramics, is added to molten metal, which is then solidified. This simple method is one of the cheapest ways to produce MMNCs.98 A challenge for this process is inhomogeneity due to insufficient mixing and gravity segregation (different densities of dispersant and matrix phase). Rheocasting tries to overcome this problem by mixing the reinforcement into a semi-solid matrix material with thus higher viscosity.99 Another way for production of MMNCs is squeeze casting. After slow mold filling the melt is allowed to solidify under very high pressure resulting in fine-grained structures.100 For the production of a nanocomposite, a prefabricated fiber or particle is infiltrated with melt before solidification of the material by pressure. Often ultrasonic dispersion of the particles in the molten metal is used for MMNC production,101 as normal stirring processes are often not able to homogenously distribute the nanoparticles in molten alloys or metal.102 Many other liquid state methods exist such as pressure infiltration,103,104 arc-discharge and spar plasma sintering.105 More recently additive manufacturing techniques such as selective laser melting have also been suggested for the production of MMNCs.72,106

1.4.2 Major Applications of MMNCs

One of the most prominent fields of MMNC application is the automotive sector. There, they are used as light weight alloy casings for reduced fuel consumption, in engines for selectively

reinforcing pistons, cylinder bores in engine blocks, intake and exhaust valves as well as brake components and many more.43 MMNCs can also be included as power module components in hybrid and electric cars.107,108 MMNCs display increased strength and hardness while being light which makes them not only attractive for the automotive but also for the aerospace industry. Light aluminum MMNCs can for example be utilized in the manufacturing process of helicopter parts such as rotor blades and swash pates, saving up to 60% mass when compared to conventional aluminum alloys. In addition, their strength is increased by 200%.107

Not only Al containing composites find application, TiC reinforced Fe and Ni based nanocomposites are commonly used in domestic applications. They are part of various tools like hammers, crimp rollers and canning tools and show superior performance compared to conventionally used steels and alloys.109

Even on the recreational level MMNCs can replace commonly used materials in e.g. bike frames or rackets. Due to their thermal properties they can also be used as heat sinks or as antennas due to their electrical properties and improved stiffness.110

A special case of MMNCs are reactive composites. In contrast to MMNCs presented so far, here the purpose of reinforcement is not to change or strengthen the metals properties but to create an intimate and large interfacial contact area between the reactants, i.e. between matrix and the embedded nanoparticles. The concentration of added (nano-)particles is typically much higher than in other MMNCs in order to achieve the optimum stoichiometric ratio of the reactions and thereby the maximize the exothermic reaction energy. This class of reactive MMNCs includes thermites (metal/metal oxide) and reactive intermetallic systems such as Ni/Al.111

1.5 Reactive nanocomposites

Reactive nanocomposites are currently of great interest for various industries including the semiconductor, aerospace, automotive, electronics, defense and biomedical sector. Depending on the material system and nanocomposite geometry the reaction can lead to explosive combustion or reactive joining. A key feature of reactive nanocomposites is their reaction mode as a Self-Propagating High-Temperature Synthesis (SHS) reaction: Once the reactants are ignited locally, the exothermic heat release allows the propagation of the 0. combustion front. Typically, a heat of reaction of Δ f << -30 kJ/mole is required to sustain a 112,113 SHS reaction with high propagation speed. 𝐻𝐻Reactive materials are usually inorganic material systems which react in non-detonating SHS reactions. Energetic materials on the

other hand are often organic compounds, which thermally explode when the entire mixture spontaneously reacts after heating.

The first reports employing highly exothermic SHS reactions date back to the research of Beketov in 1859-1889.114 He discovered that many metal oxides can be reduced by Al or Mg, which is nowadays is the basis of metallurgy. These results were taken and further advanced by H. Goldschmidt in 1898 in his pioneering paper leading to the invention of thermites for joining applications. His metallothermic welding process, in which Al is mixed with Fe2O3 to yield molten Fe and Al2O3 upon ignition of the SHS reaction, was primarily used for welding of railroads and is still used until today. In general, thermite SHS reactions are based on the oxidation of a metal (most often Al or Ti, also called “fuel”) by reduction of a metal oxide (“oxidizer”). An overview of the development of thermites is given by Wang et al.115

0. 3 Figure 1.5: Heats of reaction Δ f (in kJ/cm ) for different reactive material systems. a) Heats of reaction of various thermites, intermetallic and silicide systems. b) Heats of reaction of different Al based reactive material𝐻𝐻 systems. Data adapted from Fischer & Grubelich.116

Several reactive material systems have been developed releasing different amounts of energy (Fig. 1.5). Notably, most thermite systems release greater amounts of energy than intermetallic reaction systems. A limitation is that thermites typically require very high ignition temperatures e.g. more than 2400 K for Al/Fe2O3.

1.5.1 Development of reactive nanomaterials

First detailed descriptions of SHS reactions for combustion synthesis for a variety of different complex materials were published in the late 1960s.114 Studies in the following years showed

that SHS reactions can be optimized (lower ignition temperature, higher reaction speed) by increasing the contact area and reducing the diffusion distance between the reactants.114

With the rise of nanotechnology, reactive nanomaterials including nanothermites or superthermites were developed.117,118 However, several challenges still remain, such as uniform mixing/distribution of the reactants, as well as ageing and passivation of the reactive nanomaterials. In addition, the SHS reactivity can be inhibited by contaminated particle contact areas and porosity.

Zr/Si, Ni/Si and Al/Ni nanomultilayered systems (NML) were the first reported nanocomposites capable of SHS reactions.119–121 Using conventional thin film deposition techniques, reactive NMLs with thicknesses between 10 and 50 nm were produced. Ni/Al foils are commercially available today as NanoFoil®, which can be ignited at room temperature by electric sparks, laser pulses or hot filaments. It has been demonstrated that such reactive NMLs can be employed as a localized heat source for localized joining of heat sensitive components without damaging their functional properties. Moreover, such reactive joining processes can be performed in air without using chemically aggressive flux media (as typically needed for removing surface contaminants and native surficial oxides).122,123

Early investigations on the combustion behavior of the Ni/Al system showed that the ignition temperature of the composite depends on the size of the Al reinforcement.111 The authors prepared nanocomposites by mixing 1 μm sized Ni particles with Al particles in the size range of 25 nm to 20 μm using ultra sonic waves and subsequent pressing of the obtained mixture into pellets. Ignition studies of the samples with a 50-W CO2 laser showed that the ignition temperature can be reduced from 633 °C to 286 °C by decreasing the Al particle size, which was attributed to a melting point depression of the nano-scale Al phase. Yet, composites with smaller Al particles exhibited reduced burn rates as attributed to the increased volume fraction of native amorphous Al2O3 shell on the Al particles. Later reports confirmed that the native oxide shell, which forms even under shielding gas conditions, acts as a reaction barrier and thus has a strong influence on the reactive nanocomposites due to the high surface area to volume ratio of the embedded nanoparticles.124–126

This report initiated more detailed investigations on the effects of the particle size as well as preheating on the combustion behavior of nanothermites, including the first theoretical calculations.127,128 Experiments by Pantoya and Granier revealed an influence of the fuel to oxidizer ratio on the combustion and self-propagation performance of different nanothermite systems.124,125 They introduced the equivalence ratio Φ as

( ) = (1.1) ( ) 𝐹𝐹� 𝐴𝐴𝐴𝐴𝐴𝐴 𝜑𝜑 𝐴𝐴 𝐹𝐹� 𝑆𝑆𝑆𝑆 where F is the fuel, A is the oxidizer and the𝐴𝐴 subscripts ACT and ST the actual and stoichiometric ratios. The Al/MoO3 system was tested most intensively for fuel-lean (Φ < 1), stoichiometric (Φ = 1) and fuel-rich (Φ > 1) composites. Their results showed that the fastest ignition time was achieved with a slightly fuel-rich sample with Φ = 1.2.

1.5.2 Production of nanothermites by arrested reactive milling

Since conventional methods for nanothermite fabrication like high-energy ball milling would lead to the mechanic initiation of their reaction, new production methods such as arrested reactive milling (ARM) were developed.129,130 Precise observation of the temperature is the basis of ARM allowing the detection of a starting reaction by temperature spikes. To set the milling parameters several rounds of experiments have to be performed. Milling parameters for each cycle have to be determined to ensure that the reaction is not thermally or mechanically ignited, but sufficient mixing is achieved. Investigations of Al/Fe2O3 and Al/MoO3 nanocomposites produced by ARM showed that the highest reactivity was obtained when samples were fully mixed, while shorter consecutive rounds of mixing reduced the nanocomposite reactivity. Further studies on reactive intermetallic and metal-metalloid systems prepared by ARM illustrated that the softer material forms a matrix in which the harder material is distributed in.131–133 Milling leads to an interphase in which the reactants are mixed at the atomic scale. As this interphase functions as a reaction barrier, its thickness influences the combustion kinetics of the composite. Several reports claim that the interphase layer produced by ARM is thinner than natural oxide layers or intermixing layers which are the biproducts of alternative production methods like magnetron sputtering.134,135

Three studies on reactive magnetron sputtered nano-foils published by Blobaum et al. in 2003 134,136,137 focus on the Al/CuOx system. Al/CuOx is one of the most exothermic reactive thermites known. Nanofoils consisting of Al and CuO nanolayers could be deposited up to considerable thicknesses (14 μm). The CuOx layers were identified as Cu4O3 while the Al layers remained pure. A 1 μm Al/Cu4O3 bilayer with molar ratio Al/Cu of 1:0.4 released -3.9 ± 0.9 kJ/g of total heat, closely resembling the theoretical reaction enthalpy for a reaction of CuO and Al. The nanolayered composite also sustained self-propagation through the foil and could be used for joining as an outflow of copper was demonstrated during and after the reaction.

Even though magnetron sputtered multi-layer foils have great combustion performance and heat-release, the expensive procedure it is not suitable for large scale application. To optimize the fabrication process various methods and geometries have been put forward including coated nano-wires138 and composites produced by electrophoretic deposition,139 cryomilling,140 electrostatic self-assembly141 and electro spray deposition.142

1.5.3 Challenges in nanothermite research and application

Nanothermites have been employed as additives for propellants, explosives and pyrotechnics.143,144 Further they can be manufactured into reactive structural components (liners, munition cases) or used for self-propagating synthesis,145 joining, soldering and welding.120,146

Despite interest from various industries and the great potential applications of nanocomposites, only few of them are commercially available today. For example, only Al/Ni reactive nanofoils have reached market entry while other material systems would allow additional applications. Innovations in the field of reactive nanomaterials and nanothermites has been particularly hampered by the lack of inexpensive production methods yielding highly reactive composites. This is partially due to the available material systems: research has so far mainly focused on the production of intermetallic systems (e.g. Al/Ni) as thermite production is more difficult bearing the risk of thermal explosion. But only the most reactive intermetallic 0 3 0 systems combining Al with expensive metals like Pd (Δ f = -12.1 kJ/cm ) and Pt (Δ f = -

3 0 10.51 kJ/cm ) yield significantly more heat of reaction 𝐻𝐻than Ni/Al nano-foils with Δ 𝐻𝐻f = - 3 147 7.16 kJ/cm (Fig. 1.5). Therefore, rather thick foils of intermetallic reactive nanocomposites𝐻𝐻 are needed to ensure a reliable reactivity e.g. to melt solders in joining applications.114,123 Production of such thick foils by magnetron-sputtering is not only costly and time-consuming, it also results in residual stresses and growth defects due to the required interruption steps in the processing procedure. Moreover, most intermetallic reaction products e.g. Ni3Al are rather brittle, which limit their applications.

Therefore, there is a great need for new technologies and procedures allowing the low-cost production of SHS nanocomposites with highly exothermic heat of reactions. Such nano– thermite composite coating systems have great potential for a broad range of applications. For example, development of nanofoils based on Al and CuO would allow joining without the need of a soldering material. In addition, thinner foils could be used than currently state-of-the-art

0 commercial reactive NanoFoils® as the heat of reaction of the Al/CuO system (Δ f = -

3 0 3 20.83 kJ/cm ) is roughly 3 times higher than for Al/Ni (Δ f = -7.16 kJ/cm ). 𝐻𝐻 𝐻𝐻

1.6 Scope and outline of the dissertation

The goal of this PhD project was the design and development of a new cost-effective method to produce a highly energetic Al/CuO nanocomposite coating for joining applications. As a first step, submicron sized CuO NP aggregates were synthesized. To explore different avenues for subsequent electrophoretic deposition process of the CuO NPs from non-acqueous dispersions, various combinations of particle morphologies and concentrations, as well as different types of solvents and surfactants, were investigated. After successful deposition, the CuO nanostructured scaffold was electrochemically infiltrated with Al to realize the envisioned nanocomposite. The first chapter provides a short historical overview on nanotechnology and nanocomposites with a focus on metal matrix nanocomposites and reactive nanomaterials. Experimental methods and techniques used in this work are briefly described in Chapter 2. In Chapters 3-6, the experimental results of this thesis are presented corresponding to four first- author publications of the doctoral student (Lars Dörner). A summary of main results is presented in last chapter (Chapter 7), which also provides an outlook for further research directions. The full list of papers can be found in Appendix C.

Cost-effective sol-gel synthesis of porous CuO nanoparticle aggregates with tunable specific surface area (Chapter 3)

The synthesis of CuO nanoparticles has been explored for many years to support technologies such as catalysis, energy conversion, printable electronics and nanojoining. A wide variety of techniques have been developed and evaluated for synthesizing single-phase CuO NPs with controllable size and shape, including nanoparticles (0D), nanowires (1D), nanoplatelets (2D), thin films (2D), as well as their respective 3D hierarchical structures.148,149 However, ageing during storage, as well as successive manufacturing and processing steps, generally induce aggregation and/or agglomeration of primary NPs into larger entities with sizes of up to several microns. These aggregates consist of strongly bonded or fused primary NPs, which cannot be separated by subsequent handling and processing steps without fracturing.150 NP agglomerates comprise assemblies of more weakly bound primary NPs and NP aggregates (and/or a mixture thereof), which can be separated into their individual constituents by

providing sufficient external energy. NP aggregates are usually unwanted and avoided, yet tailored submicron sized porous NP aggregates can be advantageous: they can be more easily processed (i.e. both from handling and safety point of view) than individual nanoparticle and still offer the same nanoscale properties due to their nanoporous architecture.

In this study, an economic, green and easy-scalable sol-gel synthesis method was adopted to produce submicron sized nanoporous CuO NP aggregates. The size and shape of the primary CuO crystallites, as well as the nanoporosity of their fused CuO aggregates, can be tuned by controlled variation of the degree of supersaturation of the solution via pH and carbonate concentration. These CuO aggregates can be processed easily and safely in the form of a solution, dispersion or paste. Towards the goal of producing an Al infiltrated CuO nanocomposite coating, this chapter provides a first stepping stone allowing the tailored production of a key component, the CuO NP aggregates.

Electrophoretic deposition of nanoporous oxide coatings from concentrated CuO nanoparticle dispersions (Chapter 4)

Electrophoretic deposition (EPD) is regarded as a promising technique for obtaining homogeneous coatings by deposition of charged particles in dispersions.151–154 While different processes can be used to obtain such coatings,155 EPD has proven very powerful due to its simplicity, cost-effectiveness, the ability to coat surfaces of random shapes and the broad range of materials which can be deposited.156

The stability of a colloidal dispersion of solid particles in a liquid medium generally depends on the used solvent, the dispersed particles and their concentration, as well as additional chemical stabilizing agents. According to the theory of Derjaguin, Landau, Verwey and Overbeek (DLVO), particle-particle interactions in colloidal dispersions are governed by the balance between attractive Van der Waals forces between neighboring particles and the repulsive electrostatic interactions between the interfacial double layers at their particle surfaces.157–159 Most studies on colloidal particle dispersions use diluted systems with particle concentrations of 0.5 mg/L - 5 mg/L to suppress the rates of aggregate and agglomerate formation.160,161 However, high oxide NP concentrations are required to obtain micrometer-thick, nanoporous oxide layers through a fast and easy scalable EPD process.162

Therefore, the properties of concentrated (500 up to 5000 mg/L), non-aqueous CuO NP dispersions were systematically investigated in this study. Dispersion parameters were tuned

to achieve fast EPD of micrometer thick, nanoporous CuO films. To further understand the behavior of the NPs with regard to the fabrication of nanostructured scaffolds, this study provides details on adjusting oxide NP dispersions for EPD processes.

Electrophoretic Deposition of Cupric Oxide Coatings with Tailored Nanoporosity by Nanoparticle Aggregate Design (Chapter 5)

Porous structures with high effective surface area have unique properties compared to their dense counterparts, which can be tuned for specific applications. Macroporous materials are used in various forms and compositions in everyday life, including polymeric foams for packaging, aluminum lightweight structures in buildings and airplanes.

Porous coatings can be fabricated by deposition of particles from dispersions using EPD.151– 154 The deposition process can be controlled by the applied field strength while the porosity of the film strongly depends on the particle morphology. Our goal was to develop a green and cost-effective process to fabricate nanoporous CuO coatings by EPD from non-aqueous CuO NP dispersions.

The first fabrication of CuO thin films by EPD was reported in 2007 by Chang and Wei using nanofluids (colloidal dispersions) for deposition on a stainless-steel substrate. The influence of the concentration and deposition parameters on the nanofilm morphology, as well as the influence of sintering on compactness and hardness, was demonstrated.163 Investigations focusing on the current-voltage characteristics of CuO/ZnO heterojunctions were also conducted using films produced by EPD.164 In addition, a binder-free CuO nanosheet composite containing multi-wall carbon nanotubes has also been prepared by EPD.165

Previous studies on porous coatings have mainly investigated the influence of the EPD parameters; only few investigations on the effect of the nanoparticle and aggregate sizes and shapes on the morphology and nanoporosity have been reported. The present study fills this gap and shows how electrophoretically deposited CuO films can be further tailored. With the goal to fabricate a CuO NP scaffold for subsequent Al infiltration, this chapter highlights the correlations between the NP aggregate characteristics (e.g. size, shape, surface area) and the resulting morphology of the fabricated nanostructured layer.

Advanced manufacturing of energetic metal-matrix Al/CuO thermites nanocomposites with pristine interfaces by CuO electrophoretic deposition and Al electrodeposition infiltration (Chapter 6)

Growing interest in nanotechnology also motivated investigations in the field of metal matrix nanocomposites. Several methods were developed for producing MMNCs, which are often complex and expensive, thereby limiting their broad application.

One special class of metal matrix composites are thermites, consisting of at least one metal component (also called fuel), and one oxidizing component, or oxidizer.166,167 After initiation (i.e. thermal activation by ignition), a highly exothermic self-sustaining and self-propagating redox-reaction between oxidizer and metal occurs. Increasing the interfacial contact area between metal component and oxidizer decreases the diffusion distance between the educts, yielding a significantly enhanced reactivity.125,138,168–170 The reduction to the nanoscale results in lower ignition temperatures, shorter ignition delays and higher reaction rates compared to conventional micron-sized thermites.112,124

The simplest approach to make nanothermites is physically mixing nanopowders of the fuel and oxidizer. In addition, nanothermites can be produced by sol–gel synthesis,171,172 arrested reactive milling,130,173,174 as well as sputtering.136,137,175 Electrostatic self-assembly based on charging nanoparticles in aerosols176 and functionalization with charged ligands141 have also been employed for nanothermite fabrication.

Aluminum is used as a fuel in many nanothermites, forming highly caloric redox systems with 177,178 several oxidizers such as WO3, CuO, Co3O4 and Fe3O4. due to its high combustion enthalpy (80 kJ/cm3 in oxygen). One of the main problematics in the production of Al- composites is the inevitable formation of a thin native aluminum oxide layer (2-4 nm) around the aluminum particles,179,180 which hinders the propagation and completion of the thermite reaction.181

This chapter combines the previous findings and presents a novel method to produce Al based MMNCs, which circumvents the formation of a native oxide shell between the Al fuel and its CuO oxidizer. To this end, a CuO NP scaffold is fabricated through EPD and electrochemically infiltrated with Al from an ionic liquid. As such, a highly energetic nanoparticle thermite composite is obtained.

Chapter 2. Methods and Techniques

2.1 Preparatory methods

Electrophoretic deposition

Electrophoretic deposition (EPD) is a preparatory technique, which allows the deposition of charged particles from a dispersion onto a conductive substrate. When an electric field is applied to the dispersion, particles migrate through the liquid to the oppositely charged substrate, which serves as an electrode. A variety of different structures can be produced by EPD: thin films, thick films, porous scaffolds as well as compact coatings.182 Materials deposited by EPD include polymers, metals and their alloys, pigments, ceramics and many more. EPD is a highly versatile, fast and cost-effective method with a simple setup.156 In this work, electrodes firmly positioned in parallel by a holder were submerged in a CuO NP dispersion as depicted in Fig. 2.1a.

EDP is commonly performed with direct current electrical fields, however alternating current can also be used.183 The process can be manipulated by different parameters such as the state of the particles, the composition of the dispersion (e.g. additives), the applied electrical field, the distance between the electrodes, the temperature as well as the coating time.

Electrochemical deposition

Electrochemical deposition a allows the growth of metals and metal oxides onto a conductive surface using an electrolytic cell.184 Electrolysis is performed with a solution containing the desired metal ions or chemical complexes. At the cathode, metal cations are reduced into the zero-valence state and thereby deposited. At the anode surface oxides, including dissolution through oxidation, and salts can be formed. Changing the electrochemical parameters allows precise tuning of thickness and morphology of the growing layer (e.g. substrate, concentration of the electrolyte conductance, pH, additives, current density, conductivity of the electrolyte, temperature).185 Most often an aqueous electrolyte is employed, however some metals, such as aluminum, can only be deposited from ionic liquids, or organic electrolytes (Fig. 2.1b).

Figure 2.1 a) Electrophoretic deposition setup used in this work. b) Electrochemical infiltration setup used in this work.

Ion-Milling

Ion milling is a physical polishing process in which a thin layer is removed from the top of a material to reveal a clean pristine sample surface, which can then be used e.g. for high resolution microscopy. Ions of an inert gas, often Argon, are accelerated by an ion gun in vacuum. The ion beam then sputters material from a surface to a desired depth or layer (Fig. 2.2). The quality of the process can be optimized by adjusting the energy of the beam, the incident angle and the preparation time.

In general, both flat surfaces and cross sections can be polished by ion milling. In this work, cross section polishing was applied to prepare materials for analytical methods. Conventional cutting or mechanical polishing techniques would result in cross-section surface artefacts such as scratches, smears or delamination. However, the ejection of atoms from the target material by bombardment with an ion beam is physically stress-free and allows the preparation of a pristine surface.

Focused Ion Beam (FIB) also uses ions, usually from a gallium source, to allow site specific analysis, deposition and ablation of a material. FIB systems operated a low beam currents easily allow 5 nm resolution.186 Here, a FIB system was used to produce a thin lamella for TEM imaging, by sputtering atoms from the surface.

Figure 2.2 Schematic representation of the ion milling process.

2.2 Analytical Techniques

Transmission electron microscopy

Overcoming the restriction limits of optical microscopes, the first Transmission Electron Microscope (TEM) was built in the 1930s.187 Nowadays, high-resolution TEM (HRTEM) is a major analysis tool, facilitating investigation of structure, morphology, topology and composition of materials up to atomic scale.188,189

In the microscope, electrons generated by the electron gun are accelerated using high energies between 100-300 kV (Fig. 2.3). A condenser system, consisting of magnetic lenses and apertures then focusses the electrons into a beam, which passes through the probe. While some electrons travel through the material, others are scattered as they interact with the specimen. Internal material properties (e.g. density, thickness, composition) influence the extent of electron scattering. A first intermediate image and the first diffraction pattern are generated by the objective lens below the sample. A diffraction lense system and projection lenses further magnify image or diffraction pattern, which can be observed on a viewing screen, a monitor or a CCD camera mounted below the microscope column. To reduce unwanted electron scattering TEMs are maintained under high vacuum.

Figure 2.3 a) Schematic representation of imaging and diffraction mode of a TEM microscope. b) TEM image of CuO nanoparticles.

Scanning Electron Microscopy

A scanning electron microscope (SEM) produces an image of the surface of a probe by scanning it with a beam of focused electrons. It therefore allows investigation of the surface topology, morphology and composition of a sample, in contrast to the analysis of internal structures by TEM.

When the electron beam interacts with atoms of the investigated specimen, elastic and inelastic interactions with the sample occur, which can result in different effects based on the material including the formation of secondary electrons, back scattered electrons, cathodoluminescence, X-rays, phonons etc. (Fig. 2.4).190

Secondary electrons are ionization products with very low energy and can thus travel only limited distances in solids which is the basis for the resolution achieved by SEM. As the electron beam moves across the sample in a raster scan pattern, secondary electrons are emitted by excited atoms in the top few nanometers of the surface and are observed by a detector.190

Figure 2.4 a) Overview of different effects occurring upon the interaction of an incident electron beam with a specimen. b) SEM image of a cross section of an Al/CuO nanocomposite.

Energy dispersive X-ray spectroscopy (EDX)

Energy dispersive X-ray spectroscopy (EDX) allows the qualitative analysis of the elemental composition of a sample based on interactions of the electron beam with the sample. If energy from an incident electron is transferred to an electron of the inner shell of an atom, it is ejected from its shell (Fig. 2.5). As a result, an electron hole is generated at a low energy level, which is filled by an electron dropping down from an outer shell. The difference in energy is emitted as electromagnetic radiation (X-ray quantum) which can be recorded by an energy-dispersive spectrometer in an X-ray spectrum. Electron shells have discrete energy levels and the amount of energy released is characteristic for a particular element, which allows EDX to reveal the composition of the sample.191

Figure 2.5 a) Schematic representation of the emergence of X-rays by interaction of an electron beam with the sample. b) EDX Graph of Al/CuO nanocomposite.

Powder X-ray diffraction (XRD)

X-ray powder diffraction (XRD) allows the quick determination of the composition of a powder.192 In a crystalline sample atoms are arranged in a periodic array. As their lattice distance is approximately the size of the wavelength used in XRD, elastic scattering occurs which can be described by Bragg’s law (equation 2.1).

2 × × sin = × (2.1) d is defined as the crystal planar spacing,𝑑𝑑 θ𝜃𝜃 as 𝑛𝑛the𝜆𝜆 x-ray incident angle and λ as the wavelength.

The intensities detected as a function of the scattering angle produce a diffractogram containing information on the atomic arrangement within the crystal (Fig. 2.6). For phase identification the diffractogram is compared to a database of reported structures. Different methods (e.g. Rietveld refinement) allow the determination of crystal structures, lattice parameters, thickness and defect concentration.193,194 Using the Debye-Scherrer (equation 2.2) and Williamson-Hall formula (equation 2.3) the crystallite size (D) can be estimated.

× λ = (2.2) β × cos 𝐾𝐾 𝐷𝐷 × × cos = 4 × sin 𝜃𝜃+ (2.3) 𝐾𝐾 𝜆𝜆 𝛽𝛽 𝜃𝜃 𝜀𝜀 𝜃𝜃 𝐷𝐷 where λ is the X-ray wavelength and β is the full width at half the maximum in radians of the X-ray diffraction peak and θ is the Bragg’s angle,195 K is the shape factor (K = 0.9, is a good approximation for spherical particles in the absence of detailed shape information196–198), ε a factor for the strain induced peak broadening.199,200

Figure 2.6 a) Constructive and destructive interference of X-rays are the basis of XRD measurements. b) Typical XRD graph.

Attenuated total reflection Fourier transform infrared spectroscopy

Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) allows quick investigation of solid or liquid samples. A beam of infrared light is reflected multiple times inside a crystal with high refractive index (e.g. diamond) before it is measured by a detector (Fig. 2.7). Because of the different refractive indices of sample and crystal, total internal reflection occurs, which forms an evanescent wave, penetrating the sample for typically 0.5 to 2 µm.201 Based on the sample properties a small portion of the IR light is absorbed, allowing the investigation of the chemical structure. In particular, signals at specific wavenumbers indicate the presence or absence of functional groups.

Figure 2.7 Schematic representation of the principle of an ATR-FTIR spectrometer.

Determination of the specific surface area based on BET theory

The specific surface area of a material can be determined based on the BET theory which was first developed by Brunauer, Emmett and Teller in 1938.202 The analytical measurement allows the determination of the internal and external surfaces of a dispersed or porous solid material

based on the adsorption of gas molecules, often nitrogen. At the boiling temperature of the adsorbate, the adsorption isotherm is determined. The BET equation then allows the calculation of the specific surface area203 (equation 2.4)

1 1 1 = × + × [( ) 1] × × (2.4) 𝑐𝑐 − 𝑝𝑝 0 𝑝𝑝 𝑉𝑉𝑚𝑚 𝑐𝑐 𝑝𝑝0 𝑉𝑉𝑚𝑚 𝑐𝑐 𝑉𝑉 𝑝𝑝 − where V is the amount of adsorbed gas, Vm is the monolayer adsorbed gas quantity, p and p0 are the equilibrium and saturation pressure of the adsorbate at the adsorption temperature and c is the BET constant.

Dynamic and static light scattering

Using a laser as a monochromatic light source, light scattering allows the determination of different properties of particles in solution including diffusion speed, size and molecular weight. As the molecules in the solution are hit by light, they diffract it in different directions (Rayleigh Scattering).204–206 The scattered intensity is then probed at a certain angle θ (Fig. 2.8). While dynamic light scattering (DLS) evaluates the fluctuations of the intensities over time using a speckle pattern, static light scattering (SLS) analyzes the absolute mean intensity at different angles.

For larger particles SLS allows the determination of molecular weight, size and concentration of particles in the dispersion. For smaller particles size estimation based on diffusion measured by DLS is more accurate: As the particles move randomly in the solution (Brownian Motion), intensities vary with time and which can be used to measure the diffusion coefficient of the particles.207 Smaller particles move faster than larger particles. Based on the diffusion coefficient the hydrodynamic radius of particles can be calculated. The Stokes-Einstein equation describes the relation between particle size and their diffusion (equation 2.5).208–210

× = 6 × × × (2.5) 𝑘𝑘𝐵𝐵 𝑇𝑇 𝑓𝑓 𝐷𝐷 𝐻𝐻 𝜋𝜋 𝜂𝜂 𝑅𝑅

where Df is the diffusion coefficient, kB the Boltzmann constant, T the temperature of the dispersion, η the viscosity and RH the hydrodynamic radius.

Importantly, as light scattering directly characterizes particles in a dispersion it allows the investigation of dispersion effects e.g. influence of pH on colloidal stability.

Figure 2.8 a) Schematic representation of the light scattering setup. b) Exemplified DLS curves for small and large particles.

Zeta-Potential

A particle in an electrolyte typically carries an electric charge, giving rise to an electric potential. If particles move in a solution the outermost loosely bound solvent layer is sheared off and an interface is formed, which separates the mobile fluid from the fluid bound to the surface, this is called the slipping plane. The zeta potential ζ is the electric potential at the slipping plane of a particle moving in a dispersion (Fig. 2.9).211 It can be determined by measurement of electrokinetic phenomena such as the electrophoretic mobility Ue of the charged particle in an applied electric field (equation 2.6).

2 × × × ( ) = (2.5) 3 × 𝜀𝜀 𝜁𝜁 𝑓𝑓 𝑘𝑘𝑘𝑘 𝑈𝑈𝑒𝑒 𝜂𝜂 where ε is the dielectric constant of the probe, f(ka) is the Henry function, which depends on the polarity of the solvent and η is the dynamic viscosity of the solution.

The zeta potential indicates the electric repulsion of particles and is thus a key indicator of the stability of colloidal dispersions. Low zeta potentials indicate that there is no force preventing particles from aggregating and that the dispersion is therefore unstable.212

Figure 2.9 Illustration of the zeta potential.

Differential scanning calometry

Thermal analysis investigates the changes of a material depending on the temperature. For differential scanning calometry (DSC) the temperature of a sample holder is continuously increased, while the heat flow for a sample and a reference is measured. Recording their difference in heat flow as a function of time or temperature, allows the detection of phase transitions or chemical reactions of the sample.213 Due to physical or chemical transformations more or less heat is required for the sample depending on the enthalpy of the process. Crystallization for example is an exothermic process, therefore the sample will require less heat to rise in temperature than the reference (Fig. 2.10). The opposite is true for endothermic processes such as melting.

Some DSC instruments also allow thermal gravimetric analysis or TGA. The working principle is similar: as the temperature of the sample holder is increased the mass of a sample is measured. Physical and chemical phenomena such as phase transitions or adsorption, thermal decomposition as well as solid-gas reactions can be analyzed.

Figure 2.10 Examples of possible transitions in a DSC curve.

Profilometry

Profilometry allows the determination of the surface profile (morphology, step height, surface roughness) of a material. A stylus profilometer physically moves a probe across the surface monitoring the force from the sample pushing against the probe in a feedback loop. Changes in the Z-position of the armholder are used to gather topological information about the sample. This type of profilometry provides good z-resolution and is extremely sensitive, however it is slower than optical techniques. In this study profilometry was used to determine the height of a deposited layer of nanoparticles (Fig. 2.11).

Figure 2.11 Surface profile of a CuO nanoparticle scaffold.

Chapter 3. Cost-effective sol-gel synthesis of porous CuO nanoparticle aggregates with tunable specific surface area

3.1 Introduction

Advanced nanotechnologies in the fields of catalysis, energy conversion, storage and sensing devices rely on the accurate control of the shape and the size of materials from the nano- up to the micrometer scale. This requirement has boosted the development of a wide range of synthesis techniques for producing metallic, insulating and semiconducting nanoparticles (NP) of controllable sizes and shapes (cf. reviews 148 and 149). Reported studies on engineered and environmental NP-based systems generally focus on the size and shape of the smallest undividable entity (or building block), commonly referred to as the primary particle (or crystallite). However, successive manufacturing and processing steps (or environmental exposure) generally induce aggregation and/or agglomeration of primary NPs into larger entities with sizes of up to several microns. NP aggregates (or secondary particles) consist of strongly bonded or fused primary NPs, which cannot be separated by subsequent handling and processing steps (i.e. the aggregation process is irreversible). NP agglomerates comprise assemblies of more weakly bound primary NPs and NP aggregates (and/or a mixture thereof), which can be separated into their individual constituents by providing sufficient external energy and stabilized through the addition of suitable dispersion agents.214 For practical applications, the actual properties of the nanomaterial (e.g. specific surface area, chemical reactivity, dispersibility and toxicity) will be governed by the size, shape and density (i.e. nanoporosity) of the NP aggregates and/or agglomerates and not solely by the primary particles.215,216 For example, the extent to which the internal surface of a loosely clustered (and thus nanoporous) NP aggregate is accessible to interpenetrating gaseous or liquid species will critically influence its dispersibility, chemical reactivity and sintering behavior, which are of key importance for the development of e.g. catalysis, printed electronics and joining technologies.168,217 Notably, submicron sized nanoporous NP aggregates also have the advantage that they can be more easily (i.e. both from handling and safety point of view) processed than individual nanoparticles, while still offering the same dimensionality-enabled properties and performance due to their nanoporous architecture. Hence it is crucial to evaluate and tune the existing NP synthesis routes for accurate control of size, shape and cluster density of the NP aggregates, which has been largely disregarded up to date. The present study addresses the fabrication of cupric (CuO) NP aggregates by cost-effective, environmental-friendly and scalable chemical synthesis methods with a particular focus on the controlled variation of size, shape and cluster density (nanoporosity) of the primary crystallites constituting the NP aggregates. It is

demonstrated that the default synthesis route can be optimized to enlarge the specific surface area (SSA) of the resulting CuO NP aggregates and thereby enhance their reactivity and sintering ability when processed in the form of a dispersion, paste or nanocomposite 218. Various synthesis routes for the production of monodisperse CuO NPs and micro-sized spheres have been established in the last decades, but to our knowledge, no reports concern the chemical synthesis of nanoporous CuO NP aggregates in the range of 100 nm.

Copper oxide finds broad applications in a wide range of different technologies, such as catalysis, energy conversion, magnetic storage, energy storage, thermites, as well as superconductors. Notably, the copper-oxygen system contains two stable stoichiometric oxides, cuprous (Cu2O) and cupric (CuO) oxide. Cuprous oxide has a cubic crystal structure with a direct band gap in the range of 2.0 – 2.5 eV, whereas cupric oxide has a monoclinic crystal structure with a lower band gap in the range of 1.3 eV – 1.7 eV.219 For our envisioned applications in the field of nanojoining,220–222 the use of single-phase cupric CuO NPs is preferred,223,224 since it presents the most stable Cu oxide phase according to bulk thermodynamics.225 Over the years, a wide variety of techniques have been developed and evaluated for synthesizing single-phase CuO NPs with controllable size and shape, including nanoparticles (0D), nanowires (1D), nanoplatelets (2D), thin films (2D), as well as their respective 3D hierarchical structures; see review papers 148 and 149 and references therein. Commonly used CuO synthesis methods include milling,226 electrodeposition,227 sonochemical synthesis,228 ultrasonic spray pyrolysis 229 and hydrothermal synthesis 230,231 (see also reviews 148 and 149). Solution-based methods, including sol-gel synthesis, have proven to be the most effective method for easy and cost-effective production of CuO NPs.232 For example, a Cu- hydroxide precursor can be precipitated from an aging Cu(II)-salt solution, which is subsequently transformed into CuO by calcination of the extracted precipitate at elevated temperatures.233 The size and shape of the precipitated precursor phase strongly depends on the chemical speciation of the Cu(II) cation complexes in the ageing solution, which can be 2- - - tailored by variation of the type and concentration of complexing anions (e.g. SO4 , Cl , NO3 ; in addition of OH-) and the pH.234,235 Inorganic or organic additives, such as urea, polyethylene glycol or polyvinylpyrrolidone can be added to steer the precipitation and aggregation of the precursor phase, thus enabling the formation of specific hierarchical CuO nanostructures.232,236

For example, Cu(NO3)-salt solutions in the presence of urea were aged at 90 °C to yield spherically-shaped malachite (CuCO3·Cu(OH)2) precursor particles, which after calcination at 700 – 800 °C transform into micro-sized spherical CuO particles.237 Reproducible results can only be obtained if key factors such as the pH, type and concentrations of the reactants are well controlled.232

In the present study, a simple, green and low-cost sol-gel synthesis method based on a copper-carbonate species containing precursor phase, using copper acetate and ammonia carbonate salts without the addition of any additives, was selected and optimized to produce loosely clustered (and thus nanoporous) CuO NP aggregates with an average size in the range of 100 - 140 nm and a resulting SSA that is significantly higher than typical SSA values in the range of 10 - 15 m²/g, as reported for commercially available high-purity (i.e. ≥ 99.99%) CuO nanopowders. Sol-Gel processes are usually used to synthesize nonmetallic inorganic materials from particle dispersions. They are easily up scalable and can be conducted with cheap and non-toxic chemicals.238 Importantly, the synthesis was performed without organic additives (which contaminate the product phase and complicates the complex forming process of precursor phases). The evolution of the crystal structure, size, and shape of the primary crystallites, which develop from the precursor phase during the calcination treatment, were monitored by measuring the peak broadening through high temperature in-situ XRD. The size, shape and cluster density of the resulting CuO aggregates, as constituted of individual clusters of firmly bonded primary CuO crystallites, was investigated by complementary analytical techniques, including Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Dynamic Light Scattering (DLS) and Brunauer-Emmett-Teller (BET) analysis. Key parameters in the sol-gel synthesis procedure were identified (e.g. the supersaturation level, carbonate concentration and the resulting pH of the mixed solution) and tuned to obtain an enhanced SSA of the synthesized CuO nanopowder for the targeted applications.

3.2 Experimental section

Material Synthesis

Synthetic malachite can be prepared by reacting a solution of copper(II) nitrate with a solution containing the equivalent amount of sodium carbonate at room temperature; i.e. the copper- 2- 2+ 239 to-carbonate concentration ratio is fixed at [CO3 ]/[Cu ] = 1.0. Accordingly, solutions were prepared by mixing stoichiometric amounts of fresh aqueous 15 mM copper acetate (Sigma Aldrich) and 15 mM ammonia carbonate (Alfa Aesar) solutions at room temperature, while continuously stirring the mixed solution.240 This resulted in a pH of 5.8 for the mixed solution, which remained stable during a stirring duration of 2 h, as monitored using a pH-meter (Metrohm 914 pH/Conductometer). Upon combining the starting solutions at room temperature (further referred to as mixed solution), precipitation of particles (the gel) from the blue-greenish solution was immediately observed. In an acidic environment, copper(II) ions would remain in

solution without forming precipitates over the described time period. For more neutral environments of a pH above 5.6 (as is the case for the present study; see above), complexation of Cu2+ leads towards the formation of precipitates. Due to the supersaturation of the solution with respect to the formation of malachite, successive precipitation of the copper(II) complexes and gel formation occurs, and the composition of this precursor phase moves towards the composition of malachite. The chemical reaction to malachite can be written as

2+ 2- 2Cu + 2CO3 + H2O  CuCO3·Cu(OH)2 + CO2. (3.2.1)

When the pH exceeds 8.5, the copper-carbonate-hydroxide precursor phase complexes would gradually dissolve over time by ammonia leaching (resp. they would not even be formed), eventually leading to the formation of primarily copper(II) tetra ammine complexes,241 i.e.

CuCO3·Cu(OH)2 + 6NH4OH + (NH4)2CO3  2Cu(NH3)4CO3 + 8H2O. (3.2.2)

The stability window for the formation of malachite in the mixed solution is therefore between pH 5.6 and 8.5. To evaluate the effect of the pH of the mixed solution on the size and shape of the copper-containing precursor phase (and thus on the final CuO end product), additional synthesis routes were performed at a fixed pH value of either 5.6 or 7.0 by adjusting the added 2- 2+ volume of the ammonia carbonate solution, resulting in [CO3 ]/[Cu ] ratios of 0.4 and 2.5, respectively. Depending on the regulated pH, either an ammonium carbonate deficiency (i.e. 2- 2+ 2- 2+ [CO3 ]/[Cu ] < 1 for pH < 5.83) or surplus [CO3 ]/[Cu ] > 1 for pH > 5.83) is established, which affects the supersaturation level of the mixed solution with respect to the nucleation of the targeted malachite precursor phase. Unless stated otherwise, the mixed solution was continuously stirred over the defined duration time of tstirring = 2 h. Afterwards, the gel precipitate was collected by centrifugation, washed with ethanol and distilled water. The freshly washed precipitate was then dried in a muffle furnace in air at a temperature of 60 °C for a fixed duration of tdrying = 6 h. The resulting (largely) dehydrated precursor phase was decomposed into CuO by annealing in a muffle furnace in air at 400 °C for a fixed duration of tcalcination = 4 h (further referred to as calcination), i.e.

CuCO3·Cu(OH)2  2CuO + CO2 + H2O (3.2.3) A schematic of the above-described synthesis procedure is depicted in Fig. 3.1.

Figure 3.1 Schematic of the executed steps in the sol-gel synthesis and subsequent calcination process.

Material Characterization

The crystallinity of the gel precursor, as well as the phase purity and average primary crystallite size of the synthesized CuO nanopowder, were investigated by X-ray diffraction (XRD) using a PANanalytical X’Pert Pro Multi-Purpose (MPD) X-ray diffractometer. The XRD data were collected in the 2Θ range of 10 - 100° 2θ with a step size of 0.026° using Cu-Kα1–2 radiation

(λaverage= 0.15418 nm, 45 kV and 40 mA). A time-resolved XRD study of the precursor-to-CuO transformation during calcination was conducted using a PANalytical X'Pert PRO MPD X-ray diffractometer (same measurement parameters) with a gas-tight Anton Paar XRK-900 heating chamber equipped for heating and gas feeding (5850 TR, Brooks instrument) in static air. Thermo-gravimetric analysis (TGA) combined with differential scanning calorimetry (DSC) was conducted using a Netzsch STA449 F3 Jupiter with a low-temperature silver oven. The sample (mass: ~31.6 mg) was handled in an Al sample pan (85 μl) and heated from room temperature to 400 °C at a rate of 5 K/min under flow of synthetic air (60 ml/min). The data were corrected by an empty pan scan measured under identical conditions. The morphology and elemental composition of the calcinated nanopowder was investigated using a Hitachi S-3700N scanning electron microscope (SEM), equipped with an energy-dispersive X-ray detector (EDX) (Ametek EDAX, Octane Pro). In addition, high-resolution SEM investigations were conducted using a FEI Nova NanoSEM 230. For the analysis by transmission electron microscopy (TEM; JEOL JEM-2200FS operated at accelerating voltage of 200 kV), the synthesized particles were dispersed in ethanol and transferred onto a gold grid (300 mesh, TED PELLA, INC). ATR-FTIR

analysis of the different precursor samples were performed with a Cary 640 FTIR spectrometer (Agilent). The diamond ATR accessory with a type IIa synthetic diamond crystal has a penetration depth of ~2 µm. The spectra were recorded in a frequency range of 4000 – 600 cm- 1 with a spectral resolution of 2 cm-1. A total of 128 scans were co-added for every spectrum. The background was measured with the same settings against air. The spectrometer was controlled by Agilent Resolutions Pro software 5.2.0. DLS experiments were conducted to determine the size distribution of the CuO NP aggregates. To this end, the synthesized nanopowder was dispersed in a water-based solution with 0.5 % sodium dodecylsulfat (SDS) as a detergent and ultra-sonicated (UP200ST with VialTweeter, hielscher) to disrupt the weakly linked agglomerates. The DLS measurements were performed with a Zetasizer Nano ZS (Malvern Instruments Ltd., Malvern, UK) equipped with a max 4 mW He–Ne laser (emitting at 633 nm). Each measurement was performed at the non-invasive backscatter angle (NIBS) of 173° at a temperature of 25 °C and was preceded by a 30 s equilibration time. The ultrasonic treatment procedure was optimized to yield a stable minimal particle size after successive DLS measurements of the dispersion (thus ensuring near-complete disruption of the agglomerates). The specific SSA of the synthesized CuO nanopowders after calcination, as well as after ultrasonic treatment and subsequent drying in air, was determined from a 5-point N2 adsorption BET isotherm, as measured with a Beckman-Coulter SA3100 instrument (Switzerland). Before the BET analysis, the powder samples were dried for 2 h at 180 °C in synthetic air.

3.3 Results and discussion

Transformation of the precursor phase into CuO by calcination

2- 2+ The nature of the freshly-washed blueish-greenish precipitate collected for [CO3 ]/[Cu ] = 1.0 at pH = 5.83 (step 5  6 in Fig. 3.1) to CuO was first investigated by XRD (Fig. 3.2). The measurement indicates that the precipitated gel is XRD-amorphous, see Fig. 3.2a. Only a very broad intensity hump characteristic of an amorphous phase was detected in the 2-theta region of the expected principal (10-2) reflection of crystalline malachite, but no indications of crystalline CuO were found. To confirm the presence of a malachite-like precursor phase, the obtained blue-greenish precipitate was slowly dried to completion over 48 h at room temperature (RT) in air (note: for the standard synthesis route, the precipitate is dried at an elevated temperature for much shorter times). The XRD pattern after drying indeed matched the crystalline structure of malachite, which crystallizes in a monoclinic space group P21/a1 with lattice parameter a = 9.502 Å, b = 11.974 Å, c = 3.24 Å, alpha = 90.00°, beta = 98.75° and gamma = 90.00° 242: see Fig. 3.2b. These findings suggest that the amorphous precursor

phase is chemically and structurally similar to crystalline malachite. Subsequent calcination of the thus-obtained crystalline malachite phase (as obtained by slow drying at RT in air), as well as of the amorphous precursor phase (obtained using the default synthesis route), both lead to the formation of CuO: see

Figure 3.2 Recorded XRD diffractograms of (a) the freshly washed precipitate (i.e. the precursor phase) from a stoichiometric mixture, (b) the precursor phase after long drying at room temperature in air, which matches the reference pattern of malachite242 and (c) the final CuO product phase after calcination, which matches the reference pattern of CuO.243

Figure 3.3 In-situ XRD analysis of the calcination process of the amorphous copper- carbonate-hydroxide precursor phase into CuO upon annealing in air. (a) Temperature profile. (b) Intensity of the (102) reflection over time (temperature). (c) Size of the coherent scattering domains of CuO as extracted from the CuO (11-1) and CuO (111) reflections using either the Debye-Scherrer or the Williamson-Hall equation.

Fig. 3.2c and Eq. (3). CuO crystalizes in the monoclinic space group C12/c1 with lattice parameters a = 4.6837(5) Å, b = 3.4226(5) Å, c = 5.1288(6) Å, alpha = 90.000°, beta = 99.54(1)° and gamma = 90.000° 243.

In a next step, the calcination of the amorphous precursor gel, as obtained from the standard synthesis procedure, was studied by in-situ HT-XRD: see Figs. 3.3 and 3.4. To this end, a drying step was performed first for 12 h at 75 °C (i.e. 15 K higher than the default drying step), after which the temperature was step-wise increased with a rate of 1 °C/min to 250 °C, followed by an isothermal annealing step of 8 h at 250 °C (see Fig. 3.3a). In parallel, the reflections of the 2Θ region from 20 - 40°, which contains the principle reflections of crystalline malachite,

Cu(OH)2, CuCO3 and CuO (cf. Fig. 3.2), were recorded by XRD. During the drying step at

75 °C, only a constant broad intensity hump, typical for the amorphous precursor phase (cf. Fig. 3.2a), was observed: see Fig. 3.3b. Upon heating to 250 °C, this diffuse intensity hump decreases, but no principle reflections of crystalline malachite were detected. Only when the temperature reached 250 °C, sharp (111) and (11-1) (and to a lesser extend (110)) reflections of CuO started to appear in the recorded diffractograms. The average size (D) of the developing CuO nanocrystallites during calcination at T = 250 °C can be estimated from the peak broadening change of the CuO(111) and CuO(11-1) reflections using the Debye-Scherrer (D-S) equation (1) and the Williamson-Hall formula (W-H) (2), i.e.

= (3.3.1) cos( ) 𝐾𝐾 𝜆𝜆 𝐷𝐷 𝛽𝛽 𝛩𝛩

cos = 4 sin + (3.3.2) 𝐾𝐾 𝜆𝜆 𝛽𝛽 𝛩𝛩 𝜀𝜀 𝛩𝛩 𝐷𝐷 where β is the full width at half maximum of the respective reflection at the Bragg angle 2Θ, K is a numerical factor (here: K = 0.9, which is a good approximation for spherical particles in the absence of detailed shape information196–198), ε a factor for the strain induced peak broadening and λ is the incident X-ray wavelength (here Cu-Kα).199,200

As evidenced by Fig. 3.3c, the average size of the CuO nanocrystallites synthesized at pH = 5.8 initially increases rapidly with increasing annealing time at T = 250 °C, reaching an average final size of roughly 17 ± 2 nm (by D-S) and 17.4 ± 0.4 nm (by W-H) within a few hours. Here it is emphasized that the XRD analysis probes the average size of the coherent scattering domains and therefore presents a measure of the smallest CuO crystalline building block only (and not of the CuO NP aggregate size).

Notably, the Debye-Scherrer analysis on the basis of the CuO(111) and CuO(11-1) reflections gives similar crystallite sizes, which indicates that roughly equiaxed CuO crystallites are formed (i.e. single crystallites with a platelet or needle morphology are of minor importance).

After complete calcination, only reflections that match the reference pattern of CuO remain (see Fig. 3.2c), which suggests that the amorphous precursor phase is fully transformed into single-phase CuO within several hours of calcination at T ≥ 250 °C, in accordance with Ref.240

Figure 3.4 In-situ XRD patterns of the calcination process of the amorphous copper- carbonate-hydroxide precursor phase into CuO upon annealing in air including time and temperature steps.

Differential scanning calorimetry (DSC) coupled with thermal gravimetric analysis (TGA) was carried out in synthetic air (60 mL/min) and at a heating rate of 5 K/min to 400 °C as shown in Fig. 3.5. An exothermic effect was detected at ~190 °C with a subsequent endothermic effect at ~260 °C, associated with a pronounced weight loss. The exothermic effect can be attributed to the crystallization of the amorphous precursor phase, as formed for the default synthesis route at pH = 5.8. The following endothermic effect is caused by the subsequent thermal decomposition of the crystallized precursor phase to CuO. The relative weight loss of 29 %, as detected with TGA during the thermal decomposition, is in good agreement with the theoretical value of malachite decomposition: i.e. 1 - (2×MCuO)/Mmalachite, where MCuO and Mmalachite correspond to the molar masses of CuO and malachite, respectively. This corroborates the findings from XRD that the thermal decomposition of the precursor gel into CuO (in static air) becomes thermally activated at around 250 °C. A somewhat lower transformation temperature of 180 °C was reported in Ref. 244, which might be due to a slightly different nature of the precipitate phase and/or the much longer annealing time of 48 h.

Figure 3.5 Differential scanning calorimetry coupled with TGA of the thermal decomposition and calcination of the amorphous copper-carbonate-hydroxide precursor phase into CuO. The mass loss and the time differential mass loss are included in this graphic.

Noteworthy, DSC-TGA shows a clear crystallization peak upon heating whereas no distinct crystalline malachite reflections could be detected during heating by in-situ XRD (see Figs 3.3 and 3.4). This can be attributed to the overlap of the crystalline malachite peaks in XRD with the broad peak of the amorphous as-prepared gel (cf. Fig. 3.2), which hinders unique identification of the malachite phase as long as the amorphous gel is still present.

2- 2+ Effect of pH and [CO3 ]/[Cu ] -ratio on the formation of the precursor phase

2- 2+ To evaluate the influence of different pH-values and [CO3 ]/[Cu ]-ratios on the synthesis reaction, the mixed solution was regulated to a specific pH value of either 5.6 or 7.0 by adjusting the added volume of ammonia carbonate solution, which corresponds to an 2- 2+ 2- ammonium carbonate deficiency (i.e. [CO3 ]/[Cu ] < 1 for pH < 5.83) or surplus (i.e. [CO3 ]/[Cu2+] > 1 for pH > 5.83), respectively. To provide a better insight into the precursor composition, the chemical speciation of Cu in aqueous solution, as well as the thermodynamic equilibrium with possible solid precipitate species (i.e. malachite, azurite, copper carbonate, copper hydroxide and copper oxide), were assessed as a function of pH for different carbonate concentrations using the MEDUSA software and the respective equilibrium and solubility constants from the HYDRA database.245 The predictions were performed for various ammonia carbonate and copper acetate starting concentrations, as used in the experiments. The 2- 2+ calculation results are plotted in Figs. 3.6a, b and c for the experimentally studied [CO3 ]/[Cu ]

2- 2+ 2- 2+ ratios (and corresponding pH's) of [CO3 ] /[Cu ] = 0.4 (pH = 5.6), [CO3 ] /[Cu ] = 1.0 (pH = 2- 2+ 5.8) and [CO3 ] /[Cu ] = 2.5 (pH = 7.0), respectively. Since the solubility of the precipitating species is relatively low, they dominate the calculation results (see green colored bars in Figs. 3.6a-c). Therefore, a second set of calculations was performed, which only considered the species remaining in solution (orange colored bars in Figs. 3.6a-c). The respective XRD patterns which were experimentally collected for the precipitate gels after 2 h of stirring are plotted for comparison in Figs. 3.6d-f.

Figure 3.6 Theoretical fractions of Cu solution and precipitation species for different 2- 2+ [CO3 ] /[Cu ] concentration ratios and pH's of the mixed solution, as calculated including 2- 2+ (green) and excluding precipitation species (orange). Predictions for (a) [CO3 ] /[Cu ] = 2- 2+ 2- 2+ 0.4 and pH = 5.6, (b) [CO3 ] /[Cu ]= 1.0 and pH = 5.8 and (c) [CO3 ] /[Cu ] = 2.5 and pH = 7.0. The respective XRD patterns of the experimentally collected precipitates after 2- 2+ 2 h of stirring pertaining to the [CO3 ] /[Cu ] concentration ratios and pH's of (a), (b) and (c) are shown in (d), (e) and (f) respectively including reference pattern for CuO (red)243 and malachite (blue).242

For a carbonate deficiency of the mixed solution (Fig. 3.2a, pH = 5.6), [Cu2+∙(OAc)-]+, 2+ - 2+ - + [Cu ∙2(OAc) ] (with OAc = CH3COO) and [Cu ∙(HCO3) ] are the dominant Cu complexes in solution. Due to the low solubility of malachite, the equilibrium is largely shifted towards the

solid malachite phase (compare calculation with and without precipitation species in Fig 3.6). According to the thermodynamic equilibrium assessment, Cu can to some extend also precipitate as CuO. Indeed, as predicted both malachite and CuO are being detected by XRD in the (freshly washed) precipitated gel, as collected after the default stirring duration of 2 h (see step 4  5 in Fig 3.1). The CuO signal appears to be much more dominant than that of malachite in the recorded diffractograms, which would implicate that the formation of malachite is suppressed compared to CuO under carbonate-deficient conditions, in contrasts to the thermodynamic assessment. However, the crystalline reflections of malachite and CuO are superimposed on a very broad intensity hump indicating the presence of an amorphous precipitate phase. In this case, the summed-up signal intensity from crystalline malachite plus the amorphous malachite precursor clearly dominates over that of CuO, in accordance with 2- 2+ the model predictions. For the [CO3 ]/[Cu ] ratio equal to 1.0, which corresponds to a slightly higher pH of 5.8, similar calculation results are obtained, although the CuCO3-complexes get slightly more dominant and the equilibrium further shifts to malachite, being by far the dominant precipitating species (note: the predicted fraction of CuO becomes negligible, Fig. 3.6b). The freshly washed precipitate collected for the 1:1 ratio mixture is fully XRD-amorphous (Fig. 3.6e), but transforms into crystalline upon complete drying in air (Fig. 3.2b). Finally, the 2- 2+ calculations for a carbonate surplus of [CO3 ]/[Cu ] = 2.5 (pH = 7.0) predict CuCO3 as the most dominant solution species and malachite as the only precipitation species; the acetate- 2+ - + containing copper complexes have only a minor contribution and the [Cu ∙(HCO3) ] contribution is increased (Fig. 3.6c). In this case, the XRD analysis of the freshly-washed precipitate indeed only shows crystalline malachite, as well as the amorphous copper- carbonate-hydroxide (malachite-like) precursor phase (Fig. 3.6f).

2- 2+ The three different wet precursors with [CO3 ]/[Cu ] = 0.4, 1.0 and 2.5 were also analyzed by ATR-FT-IR to disclose the differences in their molecular compositions. The recorded ATR-FT- IR spectra are shown in Fig. 3.7. In all cases, vibration bands at 3311 cm-1, 2400 – 1900 cm-1 -1 and 1637 cm , corresponding to vibrations of the H2O solvent were identified. The FTIR spectra do not show any characteristic vibration bands for copper acetate246 or acetate ions,247 which indicates that acetate is not contributing to the precursor phase and is removed during -1 2- 2+ the washing process. The vibration detected at 880 cm for [CO3 ]/[Cu ] = 1.0 and 2.5 2- corresponds to the non-planar rocking of bonded CO3 , which does not appear for the sample 2- 2+ 248 with carbonate deficiency (i.e. [CO3 ]/[Cu ] = 0.4). Also the absorption bands for the symmetric C-O stretching at 1045 cm-1 and 1085 cm-1 appear less intense for the sample with carbonate deficiency. The largest differences in FTIR spectra for the three synthesis conditions -1 are detected in the region of 1300 – 1530 cm , in which asymmetric C-O stretching and CO2

stretching vibrations of carbonate species appear.248 The precursor obtained from the carbonate surplus reaction shows an absorption at ~1510 cm-1, corresponding to asymmetric 2- 248 C-O stretching in basic conditions of complexated carbonates (fully deprotonated CO3 ) and -1 -1 at ~1400 cm (CO2 stretching in carbonates). Its small shoulder at 1420 cm coincides with 2- 2+ 248 249 the broad absorption of the [CO3 ]/[Cu ] = 0.4 sample. In Refs. and it was shown that the carbonate vibrations in acidic environments and in bicarbonate compounds shift as compared to their carbonated counterparts. The asymmetric C-O stretching vibrations in acidic environments shift towards 1620 – 1660 cm-1 and are thus covered by the absorption band of - -1 the solvent. The CO2 stretching vibrations in HCO3 compounds appear at ~1410 cm and -1 - ~1475 cm . Hence, the FTIR analysis reflects a dominant contribution of HCO3 species (1410 -1 -1 2- -1 cm and 1475 cm ) and only a minor contribution of CO3 species (visible at 1045 cm ) at a carbonate deficiency, in agreement with the theoretical assessment of the solution species. 2- -1 -1 Accordingly, the CO3 vibrations (1510 cm and 1400 cm ) in basic/neutral environments are 2- 2+ dominant in the sample prepared with [CO3 ]/[Cu ] = 2.5. The precursor obtained from a 2- 2+ starting solution of [CO3 ]/[Cu ] = 1.0 shows no dominant carbonate vibrations in the 1300 - -1 2- 1530 cm region. Weaker absorption bands that coincide with the absorption bands for CO3 - 2- 2+ and HCO3 , as expected for [CO3 ]/[Cu ] = 2.5 and 0.4, can be identified. The FTIR analysis thus indicates that the amorphous precursor phase, as formed for the default synthesis route at pH = 5.8, is predominantly constituted of copper carbonate and bicarbonate species and can thus be designated as an "amorphous malachite-like precursor phase". In conclusion, the experimental findings in combination with the thermodynamic calculations indicate that the observed amorphous phase is composed of randomly-packed clusters and chains of the - 2- predicted copper-complexes with HCO3 , CO3 and H2O ligands (see Fig. 3.6). For the 2- 2+ stoichiometric ratio of [CO3 ]/[Cu ] = 1.0, this amorphous precursor phase is the dominant product phase of the complex forming reaction and preferably convert into crystalline malachite upon slow drying and/or subsequent calcination. For deviations from the ideal ratio (and its corresponding pH-value), the crystallization of malachite from the amorphous precursor phase seems to be accelerated, but also the crystallization of CuO can then be observed.

Figure 3.7 ATR-FTIR spectra of the precursor prepared under different conditions.

2- 2+ Effect of pH, [CO3 ] /[Cu ] -ratio and precipitation time on the morphology and size of the calcined CuO nanopowder

In order to tailor the crystallite and agglomerate sizes of the CuO nanopowder, the influence of the solution concentrations and resulting pH on the size and shape of the synthesized CuO NP aggregates as function of precipitation time was investigated in more detail. Since the hierarchical structures of the Cu precursor phase are generally largely preserved upon thermal decomposition into CuO by calcination,232 the effect of the calcination treatment on the synthesized CuO product was not specially considered in the present study. Therefore, all calcinations were performed for 4 h at 400 °C.

Calcination of the precipitate collected after different stirring times of 1 min, 1 h, 2 h and 72 h leads to a clear difference in shape and compactness of the primary CuO crystallites and 2- 2+ aggregates for the two [CO3 ]/[Cu ]-ratios considered, as becomes apparent from the SEM analysis of the CuO nanopowder (Fig. 3.8). For a very short stirring time of 1 min, the aggregated NPs and agglomerates produced at both pH values are predominantly constituted of large crystallites with needle- and platelet-like morphologies. This anisotropic crystallite shape found at the onset of mixing hints at the presence of an intermediate precursor phase which differs from both the above discussed copper-containing amorphous malachite-like precursor phase and crystalline malachite, which can be found after 2 h of stirring. A likely

explanation is the formation of a precipitating phase similar to the amorphous malachite-like precursor phase, but with an increased hydroxide content, which is typical for the formation of needle- and platelet-shaped Cu-hydroxides.240,250 Indeed, it may be assumed that the 2+ 2- - complexation of Cu by (larger and less mobile) carbonate CO3 and bicarbonate HCO3 ions, as associated with the nucleation and growth of a malachite precursor phase, is relatively sluggish as compared to complexation of Cu2+ by OH-. Upon further stirring, this intermediate precursor phase gradually dissolves again, as the more sluggish complexation of Cu2+ by the 2- - larger carbonate CO3 and bicarbonate HCO3 ions progresses, leading to the formation of the amorphous malachite-like precursor phase. As follows from the structural analysis of malachite in Ref. 234, malachite itself shows not only selective bonding along [001] crystallographic directions by the interconnection of Cu(OH)2 building blocks, but also produces strong Cu-O with the carbonate ions in the (001) planes.234 Assuming a similar local ordering for the 2+ 2- amorphous malachite-like precursor, the progressive complexation of Cu by carbonate CO3 ions 251 then results in the observed change in the crystallite shape of the CuO NPs from anisotropic to equiaxed morphology with increasing stirring time: see Fig. 3.8. As follows from a comparison of Figs. 3.8c with 3.8g, the (agglomerated) CuO aggregates synthesized for stirring times of 2 h appear much less densely clustered for pH = 7.0 as compared to pH =5.6. For longer stirring times, the degree of NP aggregation increases for both pH-values,

Figure 3.8 SEM images of CuO nanoparticles synthesized at different pH-values and precipitation (i.e. aging) times of the solution. The aging time of 2 h corresponds to the optimum aging time.

hinting at increasing densification of the amorphous precursor phase. Hence, a stirring time of 2 h can be considered as the optimum aging time for production of nano-porous nanopowders.

The TEM micrographs of the calcinated CuO nanopowders obtained at pH = 5.6 and 7.0 for the optimum stirring time of 2 h are shown in Fig. 3.6. Deposition of the nanopowder dispersions on the electron-transparent TEM grid leads to a mixture of CuO aggregates and their agglomerates, which hinders a determination of the true CuO NP aggregate size (which is obtained by DSL in the present study). However, the TEM analysis clearly evidences that the agglomerated aggregates are constituted of clusters of much smaller primary crystallites. As is evident from comparison of Figs. 3.9c and 3.9d, the average size of the primary crystallites increases with increasing pH. The primary crystallite size of 23 ± 6 nm for pH = 5.6, as determined by TEM (see Fig. 3.9a), complies well with the CuO crystallite sizes of 20 ± 6 nm (from D-S) and 23 ± 9 nm (from W-H), as determined by XRD. Notably similar crystallite sizes were obtained in the in-situ HT XRD study of the calcination process (for pH = 5.8). For pH = 5.6, CuO particles with considerably larger crystallite and aggregate sizes could be observed by TEM in very few occasions. These much larger particles may be attributed to the observed formation of few primary CuO crystallites during the synthesis step. Investigation of the obtained particles from pH = 7.0 show a larger average crystallite size of 38 ± 8 nm which also complies reasonably well with the corresponding XRD values of 25 ± 7 nm (for D-S) and 28 ± 13 nm (for W-H). Notably, for the synthesis at pH = 7.0 the shape of the primary crystallites appears smoother and more spherical, and the resulting (agglomerated) CuO aggregates are more loosely packed, corroborating the observations made by SEM: compare Figs 3.9a+c and 3.9b+d.

A possible explanation for the observed difference in primary crystalline as well as in aggregate size and morphology between pH = 5.6 and pH = 7.0 is the following. For the pH = 5.6 solution, 2- 2+ 2- 2+ a [CO3 ]/[Cu ] = 0.4 ratio induces a deficiency of CO3 ions with respect to Cu ions (see FTIR analysis). It may be assumed that upon gel formation, i.e. condensation of the Cu- complexions towards the nominal malachite composition, a much denser network of Cu2+ and 2- 2+ 2- CO3 is developed than in case of an equimolar ratio of Cu and CO3 , i.e. more Cu- carbonate-Cu-bridges are formed. As a consequence the formed gel is much more compact, and calcination of the gel then leads to larger primary CuO crystallites with higher cluster density, i.e. denser aggregate morphology.

Figure 3.9 TEM images of the agglomerated CuO aggregates, as obtained after synthesis at (a,c) pH = 5.6 and (b,d) pH = 7.0.

The observed difference in primary crystalline and aggregate size between pH = 5.6 and pH = 7.0 can be rationalized as follows: upon mixing of the starting solutions, the concentrations of the competing Cu complexation species practically instantaneous reach critical supersaturation, which for the ideal case of a homogeneous mixed solution under thermodynamic equilibrium, would result in the instantaneous homogeneous nucleation of the most stable precursor phase (i.e. crystalline malachite). These initial nuclei can grow upon aging of the mixed solution by a combination of diffusion-limited growth and aggregation (i.e., by Ostwald ripening through dissolution, growth and impingement of existing nuclei) 252. The 2- 2+ mixed solution at pH = 5.6 has a much lower [CO3 ]/[Cu ]-ratio and thus a much lower degree - - of supersaturation (see Eq. [1]). Moreover, Cu complexes with HCO3 and (OAc) ligands 2- 2+ dominate at [CO3 ]/[Cu ] = 0.4 and pH = 5.6, whereas [CuCO3] complexes become more 2- 2+ dominant at [CO3 ]/[Cu ] = 2.5 and pH = 7.0 (compare Figs 3.2a and 3.2c). The CuO aggregates (as obtained after calcination), as synthesized from a carbonate deficient solution at pH = 5.6, are much more compact than the ones synthesized in a carbonate enriched solution at pH = 7.0 (compare Figs. 3.9d and 3.9f, as well as Figs 3.8a+c and 3.8a+d). Here we propose the following explanation for the much higher compactness of the CuO aggregates synthesized at pH = 5.6. The precipitating amorphous precursor phase consists of randomly- - 2- packed clusters and chains of the predicted copper-complexes with HCO3 and CO3 ligands 2- 2+ (see Fig. 3.6), resulting in an amorphous precursor phase. The lower the [CO3 ]/[Cu ]-ratio,

the closer the proximity between neighboring copper cores in the precipitated amorphous precursor gel, which upon calcination result in a more dense CuO aggregates. Finally it is noted that, according to LaMer’s-Model, larger primary crystallites are formed at a lower supersaturation (i.e. pH = 5.6), which is not observed in this study: the primary crystallites formed at pH = 5.6 are smaller than those grown at pH = 7.0 (as evidenced by XRD and TEM). In this regard it is emphasized that a variation of the carbonate molarity not only affects the supersaturation, but also the pH of the solution and thereby the stability (i.e. solubility) of the solid precursor phase in the mixed solution as well as its composition (thus affecting its final size resulting from Oswald ripening during continuous stirring). Both the higher carbonate molarity and the higher stability of the malachite phase promote diffusion-limited growth of the primary malachite nuclei at pH = 7.0.

Determination of the CuO aggregate size by DLS

DSL was applied to determine the average size of the CuO aggregates, as dispersed in a water-based solution with 0.5% sodium dodecyl sulfate (SDS) following an ultrasound treatment. In this regard, it is emphasized that DLS records the intensity of the scattered light at very high temporal resolution from which the hydrodynamic diameter is calculated, which is the diameter of the particle or aggregate plus any ligands, ions or molecules that are attached to their surface (here: SDS). The ultrasonic treatment procedure was optimized to yield a stable minimal particle size after successive DLS measurements of the same solution. Typical measurements of the number distribution (i.e. the number of particles in different size bins) of the CuO nanopowders synthesized at pH = 5.6 and 7.0 are plotted in Figs. 3.10a and 3.10b, respectively.

The DLS analysis gives an average CuO aggregate size of 135 nm ± 43 nm (PDI = 0.301) at pH = 5.6 and of 93 nm ± 40 nm (PDI = 0.167) at pH = 7.0 based on the analysis of the number size distribution. Hence the compact CuO aggregates formed at pH = 5.6 are, on average, larger than the loosely-clustered aggregates synthesized at pH = 7.0. Notably, both aggregate sizes are in the sub-micron range, as required for the targeted applications.

Figure 3.10 Size distributions of CuO aggregates synthesized at (a) at pH = 5.6 and (b) pH = 7.0, as measured by DLS. The synthesized CuO nanopowders were dispersed in a water-based solution with 0.5% sodium dodecyl sulfate (SDS) using ultrasound waves and subsequently measured by DLS. Colored bars indicate single measurement; black line is the average of these measurements and blue line Gaussian fit of the average values.

Determination of the specific (SSA) surface area of the CuO nanopowder by BET analysis

The specific surface area (SSAs) of the synthesized CuO nanopowders after calcination, as well as after ultrasonic treatment and subsequent drying in air, were determined by BET analysis. The compact CuO aggregates synthesized at pH = 5.6 have an SSA of 16 m²/g, which can be compared with typical SSA values in the range of 10 – 15 m²/g, as indicated for commercially available high-purity (i.e. ≥ 99.99%) CuO nanopowders (e.g. US research Nanomaterials©, Plasmachem©, GetNanoMaterials©, Nanografi© and Nanoshel©). In a next step, the same CuO nanopowder (i.e. synthesized at pH = 5.6) was dispersed in a water-based solution with 0.5% SDS using ultrasound waves and dried in air. Strikingly, a similar SSA of 15.33 m²/g was determined after the ultrasonic treatment and subsequent drying. This indicates that the ultrasonic treatment of the nanopowder dispersion is not affecting the effective surface area. In other words, although the weaklier linked agglomerates will be

dispersed during the ultrasonic treatment, this has no distinct effect on the effective available surface area of compact aggregates.

The loosely-clustered CuO aggregates synthesized at pH = 7.0 (with an average size of 93 nm; see Fig. 3.10a) have an SSA of 18.73 m²/g before and 18.92 m²/g after the ultrasonic treatment, which is about 20% larger than the SSA of the compact CuO aggregates (with an average size of 135 nm; see Fig. 3.10a).

The maximum theoretical SSA that can be achieved for spherical nanoparticles is plotted as function of the particle diameter in Fig. 3.10. The SSA's of the compact and nanoporous CuO aggregates, as synthesized in this study are compared with the indicated SSAs for commercially available CuO nanopowders. It follows that the SSA of ≈ 19 m²/g, as obtained for the nanoporous CuO NP aggregates formed from pH 7 solution in the present study, is not only significantly higher than for most commercial CuO nanopowders, but also much closer to the theoretical value of ≈ 25 m²/g for the respective primary crystallite size (by TEM) of 38 ± 8 nm. Strikingly, the SSA for the compact CuO aggregates with a smaller primary crystallite size of 23 ± 6 nm, as synthesized at pH = 5.6, falls far below the respective theoretical SSA: see Fig. 3.11. Although a smaller primary crystallite size should result in a higher SSA (see Fig. 3.11), this was not observed in the present study. It is thus concluded that the BET analysis effectively probes the enhanced nanoporosity of the loosely-clustered CuO aggregates synthesized at pH = 7.0: i.e. the nanoporosity of the CuO aggregates at pH = 7.0 is much better accessible (permeable) to the infiltration by a gas (or liquid) than in case of the denser aggregates for pH = 5.6.

These findings underline the importance of tuning the cluster density of the primary crystallites in stable NP aggregates (and not solely the primary crystallite size) for achieving a high SSA and thereby an enhanced chemical reactivity (often the main property aimed at with the use of nanoparticles) and sinterability of the nanopowder when processed in the form of a dispersed solution, paste or nanocomposite. First trials of low temperature joining with the less dense CuO NP aggregates processed as a nanopaste have confirmed that the sintering temperature and time for the bonding process can both be effectively lower by tuning the SSA of the CuO NP aggregates (work in progress).

Figure 3.11 Calculated theoretical SSA for CuO particles of different diameters and experimental results obtained in the present study different synthesis conditions. Indicated are the theoretical SSAs for particles obtained from the measured crystallite size as well as the SSAs measured with BET. For comparison the SSA indicated for typical commercial products is shown.

3.4 Conclusion

The cost-effective and green sol-gel synthesis of CuO nanopowders via thermal decomposition of an amorphous malachite precursor phase was successfully implemented to tune size, shape and cluster density of the primary crystallites in the CuO NP aggregates. In- situ heating XRD measurements showed that the transformation of the amorphous malachite- like precursor phase into single-phase CuO upon heating in air becomes thermally activated at T ≥ 250 °C. The resulting CuO nanopowder is composed of (agglomerated) CuO aggregates, which are constituted of clusters of much smaller primary CuO crystallites. The size, shape and nanoporosity (i.e. aggregate cluster density) of these primary CuO crystallites can be tuned by controlled adjustment of the pH and the degree of supersaturation of the mixed solution with respect to the nucleation of malachite. To this end, the mixed solution was regulated to a specific pH value of either 5.6 or 7.0 by adjusting the added volume of ammonia 2- 2+ carbonate solution, which resulted in an carbonate deficiency (i.e. [CO3 ]/[Cu ] < 1 for pH < 2- 2+ 5.83) or surplus (i.e. [CO3 ]/[Cu ] > 1 for pH > 5.83), respectively. This resulted in an average CuO aggregate size of 135 nm ± 43 nm at pH = 5.6 and of 93 nm ± 40 nm at pH = 7.0. The loosely clustered (and thus nanoporous) CuO aggregates synthesized at pH = 7.0 have a specific surface area of 18.73 m²/g, which is about 20 % larger than the SSA of 15.97 m²/g for the compact CuO aggregates, despite a smaller NP crystallite size of the latter structure. It

follows that the cluster density of the primary crystallites in the synthesized CuO NP aggregates can be tailored to enhance the specific surface area of the resulting CuO nanopowder for targeted applications in the field of e.g. catalysis, nanojoining, energy conversion and energy storage.

Reproduced with modifications from:

Dörner L., Cancellieri C., Rheingans B., Walter M., Kägi R., Schmutz P., Kovalenko M.V., Jeurgens L.P.H. Cost-effective sol-gel synthesis of porous CuO nanoparticle aggregates with tunable specific surface area. Scientific Reports, 2019, 9, 11758.

Chapter 4. Electrophoretic deposition of nanoporous oxide coatings from concentrated CuO nanoparticle dispersions

4.1 Introduction

Particle aggregation and coagulation in colloidal systems are crucial phenomena for a broad range of applications.253–256 For example, suppressing particle aggregation and coagulation processes in colloidal dispersions is decisive to extend the shelf-life of nanoparticle (NP) suspensions and pastes, as applied in different industrial and consumer products (e.g. cosmetics,257,258 paint,259,260 food,261 Ag nanopaste for joining262). The stability of a colloidal dispersion of solid particles in a liquid medium principally depends on the applied solvent and the types and concentrations of dispersed particles and chemical stabilizing agents. According to the theory of Derjaguin, Landau, Verwey and Overbeek (DLVO), particle-particle interactions in colloidal dispersions are governed by the balance between the attractive Van der Waals forces between neighboring particles and the repulsive electrostatic interactions between the interfacial double layers at their particle surfaces.157–159 The 'true' potential of the interfacial double layer can hardly be assessed by the experiment and is therefore usually approximated from the so-called Zeta-potential, defined as the potential difference between the dispersion medium and the outer boundary of the interfacial double layer. The Zeta- potential can be deduced from the measured electrophoretic mobility of the dispersed particles in the solution.263,264 In aqueous systems with high salt concentrations and weakly charged particles, the electrostatic repulsion between neighboring particles is relatively weak; hence the attractive van der Waals forces dominate, resulting in fast aggregation kinetics. On the contrary, for highly charged particles and low salt concentrations, the strong repulsive double layer forces between the charged particles obstruct particle aggregation, thus stabilizing the colloidal suspension. The interaction between particles in a colloidal dispersion can be tailored by adding so-called surfactants, which specifically interact with the particle surface and thereby alter the interacting forces between the diluted particles to promote or hinder aggregation.254

Evidently, the aggregation rate is suppressed in highly diluted particle dispersions, since the average distance between the dispersed particles is relatively large. With increasing particle concentration, aggregation starts by the initial formation of small particle dimers, which gradually coalesce into larger aggregates.265,266 In concentrated particle dispersions, the individual aggregates can agglomerate with time to form even larger irregular, reversible clusters of aggregates; such agglomerated aggregates should not be confused with the irreversible formation of more strongly bonded aggregates from individual colloidal particles.

Sedimentation of larger aggregates and/or agglomerates can occur in parallel under the influence of gravitational forces. 1 For high particle concentrations, strong interlinking of aggregated clusters may result in the formation of a stable colloidal gel.267,268 Most studies on colloidal particle dispersions use diluted systems with particle concentrations of 0.5 mg/L – 5 mg/L to suppress the rates of aggregate and agglomerate formation.160,161 For similar reasons, most particle aggregation theories have been developed for low concentrations of dispersed single particles in water with various salt concentrations.

In this study, the properties of concentrated (500 up to 5000 mg/L), non-aqueous CuO NP dispersions were systematically investigated and tuned to achieve fast electrophoretic deposition (EPD) of micrometer thick, nanoporous CuO films. Copper oxide finds applications in a wide range of different technologies, such as catalysis (electrochemical reduction of 269 CO2), magnetic storage, printable electronics, energy conversion and storage, joining and thermites.270 Notably, the copper-oxygen system contains two stable stoichiometric oxides, cuprous (Cu2O) and cupric (CuO) oxide. For our envisioned application in the field of Al/CuO nanothermites for joining, the use of single-phase cupric CuO NPs is preferred,116,224 since it presents the most stable Cu oxide phase according to bulk thermodynamics and has the highest caloric effect upon reduction.225 Over the years, a wide variety of methods (e.g. sol-gel synthesis,271 milling,226 electrodeposition,227 sonochemical synthesis,228 ultrasonic spray pyrolysis,229 hydrothermal synthesis230,231) have been developed for synthesizing single-phase CuO NPs with controllable size and shape.148,149 We recently developed an economic green sol-gel synthesis route for easy production of submicron-sized, porous CuO NP aggregates with a very high specific surface area (>18 m²/g), which exhibit enhanced reactivity when processed in the form of a dispersion, paste or nanocomposite for the targeted application.271

The first part of this work presents a systematic investigation of the size distribution, mobility and agglomeration behavior of CuO NP aggregates, dispersed in different primary organic solvents with and without surfactant for CuO NP concentrations in the range of 50 - 5000 mg/L. Very high CuO NP aggregate concentrations up to 5000 mg/L (i.e. much higher than the typically particle concentrations applied in oxide-NP dispersion studies in the range of 0.5 mg/L - 5 mg/L),160,161 are required to achieve micrometer-thick, nanoporous oxide layers through a fast and easily scalable EPD process.162 Our aim was to develop a green, time- and cost- effective EPD process. We have chosen primary alcohols as suitable inexpensive and green solvents. Notably, aqueous-based dispersions cannot be used for EPD, since the external

1 Notably, dispersions of particles and particle aggregates sufficiently large for sedimentation are generally called suspensions, whereas dispersions of much smaller nanoparticles are usually denoted as colloids.

voltages applied in these processes by far exceed the equilibrium potential for the splitting of 182 water into its elemental components H2 and O2. The type and concentration level of surfactant in the CuO NP dispersions were selected on the basis of the following criteria: (i) sufficient mobility of the NP aggregates in the dispersion, (ii) sufficient interaction between the dispersed NP aggregates to promote layer formation during EPD, while maintaining a practical stability of the concentrated CuO NP dispersion throughout the synthesis procedure; (iii) minimization of carbon residue in the electrophoretically deposited CuO coating. Zeta-potential measurements were applied to determine surface charge, effective mobility and conductivity of the dispersed particles and the solvent for each combination of solvent and surfactant. The initial increase in agglomerate size with time was investigated by time-resolved dynamic light scattering analysis (DLS). Static light scattering characterization was conducted to evaluate the stability of the dispersions after aging up to 24 hrs. The desired properties of the concentrated, nonaqueous CuO NPs dispersions could be tuned for the targeted EPD step.

The second part of this work demonstrates easy and fast electrophoretic deposition of micrometer thick, nanoporous CuO coatings on Ti-coated glass substrates from the tuned CuO NP dispersions. EPD is known since the early 19th century but has gained more attention recently since it enables facile and rapid deposition of nanostructured materials.162 EPD is based on the directional migration of colloidal charged particles under an applied electric field between two electrodes for fast coating deposition.272,162 The EPD process involves two principle steps; the dispersed (charged) particles first move towards the oppositely charged electrode and subsequently accumulate on the surface of a (conducting) substrate.182,273,162

Noteworthy, systematic studies on the optimization of concentrated nonaqueous oxide NP dispersions for EPD, which is the main focus of this work, have very rarely been reported up to date. To the best of our knowledge, no systematic study on the dispersibility, stability and mobility of CuO NP aggregates dispersed in primary organic solvents with different types and concentrations of surfactants for coating deposition by EPD has yet been reported. First studies on the electrophoretic deposition of CuO from nanofluids date back about a decade ago.163 In recent years, there is an ever-increasing research interest in the electrophoretic deposition of CuO in combination with other particles, targeting at the production of nanocomposite materials, such as Al/CuO thermites274 and CuO/Carbon nanocomposites (with Carbon added in the form of nanotubes or graphene) for battery applications165 and antibacterial coatings.275 However, these studies typically use a predefined combination of solvent and surfactant for producing one specific functional nanocomposite deposit. Hence mainly the surfactant concentration, pH and/or EPD deposition parameters can be systematically varied to optimize the resulting nanocomposite deposit.276,277 Such an

experimental strategy for producing a specific functional nanocomposite differs from the systematic approach presented here, which uses different combinations of organic solvents and surfactants (while also varying the concentrations of surfactants and CuO NPs) to reveal fundamental differences in the resulting dispersion properties (i.e. the kinetics of aggregation and agglomeration, the effective particle mobility, the solvent viscosity and conductivity). Previous aggregation studies have mainly been performed using polystyrene latex particles.160,161,278 In the current study, the deposition parameters of the EPD step were fixed to disclose the effect of the dispersion properties on the EPD process and resulting CuO deposit. Such a systematic approach by clearly separating dispersion- from deposition-related effects is generally not provided in previous works. Notably, the CuO dispersions in our work were optimized to minimize the carbon contamination from the surfactant in the EPD deposit; a fact that is often disregarded in other studies.

4.2 Experimental section

Materials and chemicals

In this study, commercial CuO NP powder from AlfaAesar was used with an indicated mean primary NP size in the range of 20-40 nm and an indicated specific surface of 13 m²/g. Our own TEM and BET analyses of the commercial CuO NP powder indicated a slightly larger mean primary particle size of 60 ± 20 nm and a significantly lower specific surface area of 7 m²/g (r = 0.99995). The following primary alcohols were used as dispersant and solvent:

Ethanol (99.8% C2H6O from Merck / Fluka Analytical), 1-Propanol (99.0% C3H8O from AnalaR NORMAPUR), 1-Butanol (99.9% CH3(CH2)3OH from Merck), 1-Pentanol (>98% C5H12O from Merck), 1-Hexanol (>98.0% C6H14O from Merck). The following commonly used surfactants of different chemical nature were selected for this study: acetylacetone (AcAc; a bidental aprotic ligand with formula C5H8O2 from VWR), sodium dodecylsulfate (SDS; an aprotic polar ionic ligand with formula C12H25NaO4S from VWR Chemicals), polyethyleneglycol

1450 (PEG-1450; a short polar protic polymer with formula HO(C2H4O)nH from Acros Organics), PEG-4000 (a longer chained protic polymer from Merck), Polyvinylpyrrolidone K12

(VP-K12; a short aprotic polymer with formula (C6H9NO)n from Acros Organics) and PVP-K15 (a long aprotic polymer from PanReac).

Table 4.1 Used chemicals in this study, their purity and supplier.

Chemical Formular Purity Distributor

Ethanol C2H6O 99.8% Merck / Fluka Analytical

1-Propanol C3H8O 99.0% AnalaR NORMAPUR

1-Butanol CH3(CH2)3OH 99.9% Merck

1-Pentanol C5H12O >98% Merck

1-Hexanol C6H14O >98.0% Merck

Acetylacetone C5H8O2 99% VWR

Sodium dodecyl sulphate C12H25NaO4S Solid VWR Chemicals

Polyethylene glycole 4000 HO(C2H4O)nH Solid Merck

Polyethylene glycole 1450 HO(C2H4O)nH Solid Acros Organics

Polyvinylpyrrolidone K12 (C6H9NO)n Solid Acros Organics

Polyvinylpyrrolidone K15 (C6H9NO)n Solid PanReac

Oxide NP dispersions: preparation and analysis

To prepare the CuO NP dispersions, the solvent and the surfactant (if applicable, see Table 4.2 and 4.3) were mixed by stirring. Next, a weighted amount of the CuO NP powder was dispersed in the solution which was subsequently ultrasonicated to disrupt the weakly linked agglomerates in the original powder (using an UP200ST with VialTweeter from Hielscher). Unless indicated otherwise, all CuO dispersions were prepared with a default CuO NP concentration of 500 mg/L (0.06 wt.%) and a surfactant concentration of 4 g/L. Time-resolved DLS analysis was conducted directly after ultrasonification to trace the size distribution(s) of CuO NP aggregates and agglomerates during the first 15 minutes (using a Zetasizer Nano ZS from Malvern Instruments Ltd., Malvern, UK; equipped with a max 4 mW He–Ne laser emitting at 633 nm). Each DLS measurement was performed at the non-invasive backscatter angle (NIBS) of 173° at a temperature of 25 °C and was preceded by a 30 s equilibration time. The

applied ultrasonic treatment procedure was optimized such that diluted dispersions yielded a stable minimal particle size (as verified by DLS). The optimized settings for the ultrasonic treatment were as follows: a six fold repetition of ten cycles of a 1 s bursts at 30% of the device capabilities with a subsequent 1 s break, followed by a 10 s break. Next, the dispersion was equilibrated for 60 s to reduce its temperature (to avoid boiling). The treatment described above was repeated three times in total. Zeta-Potential measurements were performed to determine the effective mobility of the dispersed CuO aggregates/agglomerates and the conductivity of the dispersion. To this end, the same Zetasizer Nano ZS device equipped with a ZEN1002 dip cell was used, employing automatic voltage selection. The standard deviations as well as their respective mean sizes, effective mobilities and conductivities were calculated from 10 successive measurements. Static light scattering experiments were conducted after a prolonged saturation time of more than 24 h (LS 13 320 instrument with a micro-liquid module from Beckman-Coulter) to evaluate the agglomerate size after ageing. For the analysis by transmission electron microscopy (TEM; JEOL JEM-2200FS operated at accelerating voltage of 200 kV) the particles were dispersed in ethanol and transferred onto a gold grid (300 mesh, TED PELLA, INC).

Table 4.2 Dispersion compositions for the investigations with different organic solvents without surfactant.

Weighted CuO # Solvent Volume DLS Zeta SLS

1 Ethanol 10 mL 5 mg 5 mg 5 mg

2 Propanol 10 mL 5mg 5 mg 5 mg

3 Butanol 10 mL 5 mg 5 mg 5 mg

4 Pentanol 10 mL 5 mg 5 mg 5 mg

5 Hexanol 10 mL 5 mg 5 mg 5 mg

Table 4.3 Dispersion compositions for the investigations with ethanol solvent with different surfactant.

Weighted CuO Surfactant Surfactant Wt.% of Solvent Volume Surfactant DLS Zeta SLS Type Weighted

EtOH 10 mL 5 mg 5 mg 5 mg - - -

EtOH 10 mL 5mg 5 mg 5 mg SDS 41.6 mg 0.5

EtOH 10 mL 5 mg 5 mg 5 mg AcAc 41.6 mg 0.5

EtOH 10 mL 5 mg 5 mg 5 mg PEG 1450 41.6 mg 0.5

EtOH 10 mL 5 mg 5 mg 5 mg PEG 4000 41.6 mg 0.5

EtOH 10 mL 5 mg 5 mg 5 mg PVP K12 41.6 mg 0.5

EtOH 10 mL 5 mg 5 mg 5 mg PVP K15 41.6 mg 0.5

Electrophoretic deposition procedure

Electrophoretic deposition of the CuO nanostructures from the tuned CuO NP dispersions was conducted using a Keithley Sourcemeter 2400. Ti-coated and Au-coated float glass cuvette slides with sizes of 7×50 mm2 (coated using physical vapor deposition; PVD) were used as a counter electrode and working electrode, respectively. Electrodes were placed parallel at a 1 mm distance, while immersing an electrode area of 7×7 mm2 into the dispersion. The EPD step was performed potentiostatically using successive pulses at 75 V with a duration of 120 s, which each precedes a ramp from 0 V to 75 V taking 30 s. Between, the pulses, a 60 s resting period with a fixed potential of 1 V was inserted. After the EPD step, the electrodes were carefully removed from the dispersion and gently rinsed with ethanol.

Characterization of the electrophoretic deposits

The substrate surfaces after electrophoretic deposition were analyzed by optical light microscopy. Moreover, the morphology and elemental composition of the oxide deposits were investigated using a Hitachi S-3700N scanning electron microscope (SEM), equipped with an energy-dispersive X-ray detector (EDX) (Ametek EDAX, Octane Pro). Cross-sections of the deposited nanoporous oxide layers were prepared by fracturing the samples and milling the fractured edge with an IM4000 Ion Milling System (Hitachi) using an Ar ion beam (6 kV

accelerating voltage, 1.5 kV discharge and 0.09 cm3/h Ar gas flow). The thickness of the deposited layers was determined using a profilometer (Bruker Dektak XT) with a stylus radius of 2 μm, stylus force of 3 mg and trace resolution of 0.833 μm/pt.

4.3 Results and discussion

Initial CuO nanoparticle aggregate size in ethanol solvent

The main goal is to develop a green and cost-effective electrophoretic deposition process, which is transferrable to an industrial scale. Therefore, only non-toxic primary alcohols with a successively increasing hydrocarbon chain length were considered as dispersant and solvent (the use of aqueous dispersions is not possible; see Introduction).

As a first step, the effect of the ultrasonic treatment on the initial CuO aggregate size distribution in primary organic solvent without surfactant was investigated by time-resolved DLS. We focused on the dynamic light scattering technique over static light scattering to start our investigation due to its compatibility with Zeta-potential measurements. Additionally, DLS measures intensity fluctuations due to particle movement which allows better assessment of the dynamics in the dispersions. Among the primary organic solvents (Table 4.4) employed in this study ethanol has the lowest viscosity, consequently, the ultrasonic treatment is expected to be most effective in disrupting initial CuO agglomerates of the dispersed nanopowder using ethanol as a solvent. The applied ultrasonic treatment procedure was optimized such that diluted dispersions yielded a stable minimal particle size after successive DLS measurements of the dispersion. Corresponding DLS analysis of the time-resolved particle size distribution for different CuO NP concentrations from diluted (i.e. 50 mg/L) to weakly (i.e. 500 mg/L) to concentrated (i.e. 5000 mg/L) are presented in the contour plots of Figs. 4.1a-c, respectively. The intensity size distribution in Fig. 4.1 refers to the size distribution of the CuO particles and their aggregates in the dispersion during a defined time interval (t) after the sonification step (t = 0). The DLS measurements of the size distribution were performed over specific size ranges ("size bins", as defined by the instrument/software), which results in a pixelation of the contour plots.

DLS analysis of the diluted dispersions (i.e. 50 mg/L) directly after the ultrasonic treatment should reflect the initial aggregate size(s) present in the original CuO nanopowder. The DLS analysis for the diluted dispersion revealed a bimodal size distribution with mean sizes of 182 ± 12 nm and 584 ± 51 nm (Fig. 4.1a), which is also detected in the weakly concentrated 500

mg/L dispersion (Fig. 4.1b; mean particle sizes around 180 ± 24 nm and 580 ± 110 nm), but absent in the concentrated 5000 mg/L dispersion (Fig. 4.1c).

Figure 4.1 Contour plots of the time-resolved CuO NP size distributions in ethanol (without surfactant), as measured by time-resolved DLS, for different CuO NP concentrations of: (a) 50 mg/L (diluted), (b) 500 mg/L (weakly concentrated) and (c) 5000 mg/L (concentrated). The color-coded scale bar indicates the corresponding particle size distribution scale. Photographs of the corresponding dispersions are also shown on the left.

When considering spherical aggregates the volume of the smallest observed aggregates with a diameter of ∼180 nm is about a factor of 27 larger than the primary CuO nanocrystallites in the nanopowder (diameter 60 ± 20 nm, as characterized by TEM). This indicates that the optimized ultrasonic treatment (for pure ethanol solvent) is effective in disrupting weakly-bound aggregates and agglomerates in the original nanopowder yielding the bimodal size distribution. The smallest aggregate size around ∼180 nm reflects the mean CuO aggregate size in the original nanopowder. We cannot rule out that even smaller aggregate sizes (i.e. single nanocrystallites) were also present in the dispersion; however their presence would be overshadowed by the large amount of bigger aggregates and agglomerates, since the scattering intensity scales with the particle size.206,279 As reflected by the relatively broad DLS signals of the bimodal size distributions in Figs. 4.1a and 4.1b, the initial aggregates in the

original nanopowder, as well as their agglomerates formed in the dispersion, have an irregular non-spherical shape, as verified through TEM analysis of particles dispersed in ethanol (Fig. 4.2).

Figure 4.2 TEM micrographs of CuO nanoparticle aggregates dispersed in ethanol.

The initial aggregates (~180 nm) have a very high mobility (through Brownian motion) in the pure ethanol dispersion (due to the relatively low viscosity of the solvent; see Table 4.4), which enables very fast agglomeration, especially towards higher concentrations. Consequently, the initial aggregate size of around ∼180 nm is no longer detected for the concentrated 5000 mg/L dispersion (see Fig. 4.1c). The low viscosity of ethanol solvent also enables fast sedimentation of large agglomerates by gravity, which keeps the mean agglomerate size distribution in the dispersion below 1000 nm for all CuO NP concentrations studied (Fig. 4.1). The upper size of roughly 1000 nm thus represents an upper threshold of the largest CuO NP agglomerate size in the ethanol dispersion prior to sedimentation. Notably, the mean agglomerate size in the concentrated dispersion increases with increasing measurement time from 504 ± 35 nm to 747 ± 64 nm (after 10 minutes). This effect can be attributed to the temperature instability of the dispersion directly after the ultrasonic treatment. Namely, the ultrasonic treatment increases the temperature of the solvent resulting in a lower viscosity and thus a higher Brownian motion, which both promote particle-particle interactions and agglomeration (and possibly sedimentation) during the first minutes of the DLS analysis (i.e. during temperature equilibration of the dispersion). Comparison of the photographs of the analyzed dispersions (see Fig. 4.1) illustrates the main limitation for the DLS analysis of concentrated dispersions;

i.e. these dispersions (or rather suspensions; see below) become very dark, which hinders an effective penetration depth of the laser light into the dispersion. Therefore, a concentration of 500 mg/L was used for further investigations of the mobility and agglomeration behavior of CuO NP aggregates, dispersed in organic solvents with different surfactants.

CuO NP dispersions in different organic solvents without surfactant

The effective mobility (i.e. the particle mobility under influence of an externally applied electric field) of CuO NP aggregates and/or agglomerates, as well as the conductivity of the different dispersions are reported in Table 4.4 (as obtained from Zeta-Potential measurements). The viscosity of the primary organic solvent increases with increasing hydrocarbon chain length from ethanol to hexanol. Accordingly, the (absolute) effective mobility of CuO NP aggregates and/or agglomerates, as well as the conductivity of the dispersions decrease with increasing viscosity (i.e. with increasing hydrocarbon chain length) from ethanol to hexanol.

Table 4.4 Mean size, effective mobility and conductivity obtained from Zeta-Potential measurements of CuO NP aggregates dispersed in different primary organic solvents (without surfactant). The viscosity and dielectric constant (ε) of the solvents are also given.280–282

Mean size Mobility Conductivity Viscosity Dielectric Solvent (nm) (μm·cm·V-1·s-1) (×10-4 mS·cm-1) (mPa·s) constant

180 ± 24 nm Ethanol -0.513 ± 0.031 17.30 ± 0.43 1.08 25.3 580 ± 110 nm

Propanol 1651 ± 422 -0.066 ± 0.008 7.368 ± 0.81 1.94 20.9

Butanol 832 ± 87 0.016 ± 0.005 5.501 ± 0.59 2.57 17.7

Pentanol 709 ± 75 < 10-3 3.302 ± 1.00 3.51 15.3

Hexanol 488 ± 43 < 10-3 3.572 ± 1.14 4.59 13.3

The mean size distributions of the CuO NP aggregates and/or agglomerates in different organic solvents (at a concentration of 500 mg/L without surfactant) were measured by time- resolved DLS for a duration of 15 minutes, starting directly after the ultrasonic treatment (Figs. 4.3a-e). The agglomerate sizes are plotted as function of the DLS measurement time in Fig. 4.3a; the corresponding averaged values are given in Fig. 4.3b. As previously discussed (cf. Fig. 4.1b) and reflected in Fig. 4.3a, the CuO NP dispersion (500 mg/L) with ethanol solvent

yields a bimodal size distribution through the ultrasonic treatment with mean size ranges of 180 ± 24 nm and 580 ± 110 nm. The initial aggregates (~180 nm) have a very high mobility in the pure ethanol dispersion due to its relatively low viscosity (see Table 4.4). Consequently, concentrated CuO NP dispersions in ethanol solvent exhibit very fast agglomeration of small aggregates. The low viscosity of ethanol allows the coagulation of large agglomerates into even larger ones, as indicated by the occasional occurrence of signal intensities at size > 1000 nm. In addition, the low viscosity of ethanol solvent enabled fast sedimentation of large

Figure 4.3 Contour plots of the size distributions of the CuO NP aggregates and agglomerates dispersed in the different organic solvents without addition of a surfactant. The data was obtained by time-resolved DLS directly after ultrasonic treatment. The color-coded scale bar indicates the corresponding particle size distribution scale. agglomerates under the influence of gravity. The concurrent fast coagulation and sedimentation of large agglomerates (size > 1000 nm) results in correlated fluctuations of the measured bimodal DLS signal intensity with time. We conclude that the concentrated CuO NP dispersions in ethanol solvent are unstable without the addition of a surfactant and thus rather resemble suspensions.

Figure 4.4 (a) Mean agglomerate size of the concentrated CuO NP dispersions in the different organic solvents versus DLS measurement time. (b) Mean agglomerate size plus standard deviation (over the DLS measurement time of 5 to 15 minutes) for the different organic solvents without surfactant. All data were extracted from the contour plots in Fig. 4.3.

The viscosity of propanol is roughly doubled compared to ethanol (see Table 4.4), which drastically reduces the Brownian motion of smaller aggregates and, particularly, of larger agglomerates in the dispersion. Consequently, a distinct bimodal size distribution as observed with ethanol is no longer evident for the CuO NPs dispersed in propanol (Fig 4.3b). Although we still find evidence for the presence of initial CuO NP aggregates in propanol by occasional signal intensities around ∼180 nm, their signal is much less pronounced. Instead a broadening of the signal intensity of the larger agglomerates is observed, indicating coagulation of smaller aggregates and agglomerates into larger agglomerates of irregular size and shape. Interestingly, the higher viscosity of propanol does not only suppress the mobility of larger agglomerates, but also reduces their sedimentation rate (compared to ethanol). Consequently, the mean agglomerate size of 1651 ± 422 nm is significantly larger in propanol than in ethanol solvent and hence the formation of very large agglomerates with sizes in the range of 4000- 5000 nm was occasionally detected (Fig. 4.3b).

With the stepwise increase of the carbon chain length to butanol, the solvent viscosity further increases (see Table 4.4). Therefore, the agglomeration kinetics were further reduced compared to propanol and, particularly, ethanol. While agglomeration of the smallest aggregates still occurred, the coagulation of large agglomerates further into larger ones is kinetically hindered, resulting in a relatively intense and narrow size distribution and a relatively small mean agglomerate size of ∼832 ± 87 nm.

The viscosity of the solvent further increases from pentanol to hexanol (Table 4.2); the corresponding DLS analyses are shown in Figs. 4.3d and 4.3e, respectively. DLS yielded mean agglomerate sizes of 709 ± 75 nm and 488 ± 43 nm for pentanol and hexanol respectively. With the increase in viscosity of the solvent, the size distributions show even less variance indicating a homogenous dispersion of stable agglomerates. Notably, the smaller size mode detected at ~180 nm (characteristic for the initial aggregate size in the powder) is only occasionally detected in the organic solvents with higher viscosities, which can be rationalized as follows. First, the disruption of weakly linked aggregates in the original nanopowder by the ultrasonic treatment is less effective for organic solvents with a higher viscosity. Secondly, with increasing viscosity of the solvent, larger agglomerates become more stable and thus more prominent, eventually dominating the DLS signal intensity.

SLS is a complementary technique to DLS, since it measures the average particle size by integrating the intensity of the scattered light at several angles over time. SLS analysis was applied to investigate the long-term stability of the CuO NP dispersions in the different organic solvents without surfactant. Prior to the ageing process, the concentrated dispersions were freshly prepared and ultrasonicated. Afterwards the dispersions were rested for 24 h under laboratory conditions and subsequently measured by SLS. Fig. 4.5 shows the thus-obtained volume size distributions of the CuO NP agglomerates in the different solvents. The volume percentage of agglomerates with sizes smaller than 1000 nm was most pronounced, especially in ethanol. Hence, the aged dispersions still maintain stable agglomerates with sizes of up to about 1 μm, despite progressive aggregation, agglomeration and sedimentation during 24 hours of aging.

In conclusion, the CuO NP powder dispersed in a primary organic solvent is predominantly stabilized by physical effects, e.g. by the viscosity of the used dispersant. Time-resolved DLS analyses showed that the agglomeration rate of smaller CuO NP aggregates and, especially of larger agglomerates, is successively reduced with increasing viscosity (i.e. with an increasing carbon chain length) of the organic solvent from ethanol to hexanol. The resulting mean agglomerate size decreased with increasing solvent viscosity from propanol to hexanol (see Fig. 4.4b). Ethanol is an exception to this rule, since larger agglomerates still have sufficient mobility to coagulate into even larger agglomerates, which quickly sediment from the dispersion.

Figure 4.5 The mean sizes and volume size distributions (by multi modal peak analysis) of the CuO NP agglomerates in the different dispersions (without surfactants) after aging for 24 hours. The color-coded scale bare denotes the volume percentage for the different size ranges. The average agglomerate size is indicated by the red line.

Previous research on surface charging mechanisms of oxides in pure primary alcohols with an intermediate dielectric constant (10 < ε < 30) indeed showed that the decrease in particle mobility with increasing hydrocarbon-chain length is mainly due to the difference in viscosity.283,284 The electrophoretic mobility and aggregation behaviors of oxide particles in colloidal dispersions is also governed by their surface charge. In the present study, all the alcohol solvents have the same functional OH-group and it can thus be assumed that the basic particle-solvent charging mechanism is identical for all organic solvents (without surfactant).283,285 It was shown that the aggregation behavior of CuO nanoparticles in aqueous solutions can be controlled by tailoring its surface charge by controlling the pH.286 In the pH range of 6-11 the electrostatic repulsive forces no longer prevent the particles from aggregating.287 In this regard, it is noted that none of the solvents were dried in the present study. Consequently, in particular the ethanol solvent will absorb humidity and thus have a higher water content than the other organic solvents. By absorption of humidity, a polar medium (water, ε = 80) is passively added, which leads to an increase of the effective surface charge of CuO particles that interact with dissolved water molecules (accordance to the Nernst equation288). This may also partially rationalize the much-enhanced mobility and aggregation/ agglomerates of the CuO particles in ethanol solvent (without surfactant).

CuO NP dispersion in ethanol solvent with different surfactants

The relatively high mobility of larger CuO NP agglomerates in ethanol solvent is a key criteria for the development of a suitable EPD process. Moreover, ethanol is the most volatile solvent, which facilitates removal of carbon contamination (solvent) residues from the deposited coating after the EPD step. As a next step, we investigated if the stability of the CuO NP dispersion with ethanol solvent could be improved by addition of a suitable surfactant, while assuring a high mobility and narrow size distribution of the dispersed CuO NP aggregates and/or agglomerates.

Table 4.5 Effective mobility and conductivity for the CuO NP dispersions in ethanol solvent with 0.5 wt.% addition of various surfactants, as obtained from Zeta-Potential measurements.

Dispersion Average size Mobility Conductivity composition (nm) (μm·cm·V-1·s-1) (×10-4 mS·cm-1)

225 ± 103 -0.513 ± 0.031 17.3 ± 0.43 pure ethanol 650 ± 198

+ acetylacetone 819 ± 155 0.221 ± 0.060 26.7 ± 1.2

+ SDS 1440 ± 286 0.477 ± 0.029 2945 ± 5.0

236 ± 45 + PEG 1450 -0.784 ± 0.033 41.9 ± 1.0 1048 ± 298

247 ± 90 + PVP K12 -0.596 ± 0.038 22.6 ± 0.6 1295 ± 259

211 ± 75 + PEG 4000 -0.530 ± 0.061 24.1 ± 0.3 1240 ± 287

232 ± 97 + PVP K15 -0.603 ±0.029 20.8 ± 1.0 1057 ± 181

To this end, CuO NP dispersions with ethanol solvent and 0.5 wt.% of AcAc, SDS, PEG-1450, PEG-4000, PVP-K12 or PVP-K15 surfactant were prepared. The different surfactants were selected based on their chemical nature: i.e. AcAc as a bidental aprotic ligand; SDS as an aprotic polar, ionic ligand; PEG-1450 & PEG-4000 as a short and longer polar, protic polymers; PEG-4000 as a longer chained protic polymer; PVP-K12 & PVP-K15 as short and long aprotic polymers. The effective mobility and conductivity of the dispersions, as obtained from Zeta-

Potential measurements, are given in Table 4.5 (the mean average agglomerate size by DLS is also listed).

Exemplary results of the agglomerate size distribution and mean agglomerate size with time (directly after ultrasonification) are depicted for AcAc, SDS and PEG-1450 in Fig. 4.6a (as measured by time-resolved DLS). The corresponding data for pure ethanol solvent (EtOH; without surfactant) is again given as a reference. The corresponding mean agglomerate size (plus standard deviation; as averaged over the DLS measurement time from 5 to 15 minutes) for each surfactant is given in Fig. 4.6b. The mean sizes and volume size distributions of the CuO NP agglomerates in the dispersions after aging for 24 hours are plotted in Fig. 4.6c (as determined by SLS).

As follows from Fig. 4.6a, addition of AcAc or SDS to the concentrated CuO NP dispersion resulted in a more intense and narrower agglomerate size distribution. Fluctuations of the size distribution were only observed during the first few minutes, which can be attributed to a temperature equilibration of the freshly ultrasonicated dispersion. The mean agglomerate size with AcAc (as averaged over a measurement time from 5 to 15 minutes) was 819 ± 155 nm. The agglomerates in the SDS dispersion were larger than with AcAc, having a mean size of 1440 ± 286 nm. Zeta-potential measurements (Table 4.3) indicate that the addition of AcAc or SDS changes the sign of the surface charge of the dispersed CuO NP agglomerates from negative to positive, which appears to be crucial for an effective stabilization of the ethanol dispersion. Addition of surfactants to the dispersions introduces additional ions, which can adhere to the initially negatively charged surface of the dispersed CuO nanoparticle aggregates. The addition of SDS is associated with the adsorption of sodium ions onto the oxide surface, which explains the observed surface charge reversal. AcAc coexist as keto and enol tautomers in solution. The enol form is a weak acid, which changes the pH of the dispersion. In addition, its interaction with the negative surface charge of the oxide particles apparently also results in a positive surface charge. Similar phenomena were previously 283 observed for SiO2, MgO and TiO2 particles in methanol when stabilized by aerosol OT. The agglomerate mobility is only slightly higher with SDS, whereas the conductivity of the dispersion is increased by a factor 103 for SDS (both as compared to AcAc; see Table 4.5). Notably, as discussed previously, a too high conductivity of the dispersion is problematic for the EPD process, which favors the use of AcAC over that of SDS.

Figure 4.6 (a) Exemplary results of the size distribution for the concentrated CuO NP dispersions in ethanol solvent with 0.5 wt.% of AcAc, SDS or PEG-1450 surfactant. The corresponding data for pure ethanol solvent (EtOH; without surfactant) is also given as a reference. (b) The mean agglomerate size (plus standard deviation; as averaged over a measurement time from 5 to 15 minutes) in ethanol solvent with the given surfactant. (c) Mean particle sizes and volume size distributions of the dispersions in pure ethanol solvent with different surfactants after aging for 24 hours (as determined by SLS).

The use of PEG-1450, PEG-4000, PVP-K12 or PVP-K15 does not change the sign of the surface charge of the dispersed CuO NP agglomerates (as compared to pure ethanol). Consequently, the agglomerate mobilities and dispersion conductivities in the presence of PEG-4000, PVP-K12 and PVP-K15 are very similar compared to ethanol; only PEG-1450 gives a slightly higher mobility and conductivity (see Table 4.5). Accordingly, time-resolved DLS also detected a fluctuating bimodal size distribution for the dispersions with PEG-1450, PEG-4000, PVP-K12 and PVP-K15 as surfactants: cf. Fig. 4.6a for PEG-1450. Notably, the fluctuating bimodal size distribution in the case of PEG-1450 was more distinct and indicated larger agglomerate sizes compared to the pure ethanol dispersion, which suggests that the agglomeration rates are slightly enhanced in the presence of PEG-1450. The usage of PEG 4000, PVP K12 or PVP K15 surfactant yielded fluctuating bimodal size distributions that were

similar to plain ethanol; i.e. the formation of very large agglomerates (as for PEG-1450) was not observed. While the smaller size distribution around ∼180 nm originated from the initial aggregates in the original nanopowder, the larger agglomerates are roughly two times larger compared to pure ethanol solvent (i.e. in the size range of 1050 -1300 nm). Hence it is concluded that the use of the long-chained polymer surfactants PEG-1450, PEG-4000, PVP- K12 or PVP-K15 does not improve the intrinsically poor stability of the CuO NP dispersions in ethanol solvent. An improved stability of the CuO NP dispersions in ethanol solvent is only achieved by the addition of AcAc or SDS due to the associated modification of the oxide surface charge.

Table 4.6 Effective mobilities and conductivities for the CuO NP dispersions in ethanol solvent with different surfactant types and concentrations, as obtained from Zeta- Potential measurements.

Dispersion Concentration Average Mobility Conductivity composition wt.% size (nm) (μm·cm·V-1·s-1) (×10-4 mS·cm-1) 225 ± 103 -0.513 ± 0.031 17.3 ± 0.43 pure ethanol 650 ± 198 + acetylacetone 0.05 1204 ± 372 0.130 ± 0.016 0.00248+1.38 + acetylacetone 0.25 1528 ± 368 0.424 ± 0.011 0.00259+1.49 + acetylacetone 0.50 819 ± 155 0.221 ± 0.060 26.7 ± 1.2 + SDS 0.05 1142 ± 233 0.177 ± 0.062 3837 ± 50.2 + SDS 0.25 1568 ± 322 0.409 ± 0.033 1690 ± 4.22 + SDS 0.50 1440 ± 286 0.477 ± 0.029 2945 ± 5.0

For our targeted application in the field of CuO-based nanothermites, it is essential to reduce the carbon contamination in the EPD coatings to a minimum. Therefore, we tested if CuO NP agglomerates in ethanol solvent can also be stabilized by lower SDS and AcAc concentrations (0.05 wt.% and 0.25 wt.%, see Table 4.6 and Fig. 4.7). Although the addition of AcAc and SDS in lower concentrations clearly stabilizes the CuO NP agglomerates (most evident for SDS) in the ethanol dispersions, it also lead to the appearance of not previously detected agglomerate sizes in the dispersion (i.e. initial aggregates and their agglomerates, as well as very large agglomerates), which is unwanted in the present work. Apparently, AcAc or SDS surfactant concentrations of 0.25 wt.% are too low to stabilize a single agglomerate size. A stable dispersion with a mono-modal size distribution can be obtained for AcAc and SDS surfactant

concentrations of 0.50 wt.% (see Figs. 4.6b and 4.6c), which we therefore applied for the EPD step.

Figure 4.7 Contour plots of the size distributions of the CuO NP aggregates and agglomerates dispersed in ethanol with (a) 0.05 wt.% Acetylacetone, (b) 0.05wt.% SDS, (c) 0.25wt.% Acetylacetone and (d) 0.25wt.% SDS. All data were measured by time- resolved DLS directly after the ultrasonic treatment. The color-coded scale bar indicates the corresponding size intensity scale.

The investigation of the effective mobility with different surfactant concentrations (Table 4.6 and Fig. 4.7) gives additional insights on the underlying mechanisms for the observed dispersion stabilization using SDS or AcAc. For SDS, the effective mobility and hence the surface charge increases with increasing SDS concentration, which supports the above statement that the particles are being electrostatically stabilized through the adsorption of positive sodium ions on the aggregate surface. For AcAc, the effective mobility and thus the surface charge increases with increasing surfactant concentration from 0.05 wt.% up to 0.25 wt.%, but is again lower for even higher concentrations of 0.5 wt.% (see Table 4.6 and Fig.

4.7). This observation suggests that the majority of AcAc-related ions are adsorbed on the particle surfaces up to 0.25 wt.%, which prevents a change in acidity of the dispersion by still dissolved AcAc ions. For higher AcAc surfactant concentrations >0.25 wt.%, the AcAc anion concentration in the dispersion rises, which results in a reduced acidity of the dispersion, as accompanied by a lowering of the effective surface charge.

Electrophoretic deposition from tuned CuO NP dispersion

Concentrated CuO NP dispersions are required to realize fast formation of micrometer thick coatings by EPD. Therefore, CuO NP concentrations of 5000 mg/L in ethanol solvent were used for the EPD step using a surfactant concentration to 0.5wt%. We increased the particle concentration to ensure a sufficiently high particle concentration for fast deposition of micrometer-thick coatings. Comparison of the DLS investigations for different particle and surfactant concentrations showed that the increased agglomeration behavior for these concentrated CuO NP dispersions has no significant effect on the maximum agglomerate size (see Fig. 4.1) prior to sedimentation and thus results in comparable aggregate/agglomerate size distributions.

Electrophoretic deposition was performed on Ti-covered glass substrates, according to the procedure described in experimental section. A planar SEM micrograph of the nanoporous CuO coating surface, as obtained after four EPD cycles from the dispersion with 0.5wt% AcAc, is shown in Fig. 4.8a. A corresponding cross-sectional SEM micrograph of the same sample is shown in Fig. 4.9. The original substrate could be fully covered with CuO NP agglomerates from the dispersion. Analysis using a profilometer yielded an average coating thickness in the range of 20 - 30 μm, after 480 s deposition time, as confirmed by cross-sectional SEM (Fig. 4.9). Image analysis of the cross-sectional SEM micrograph resulted in an estimated coating porosity of 43 % ± 2 %. Of course, the resulting coating porosity mainly depends on the mean size and shape of the initial aggregates in the selected CuO nanopowder. This implies that the nanoporosity of the coatings can easily be varied by choosing a finer or coarser CuO nanopowder.

Figure 4.8 Secondary electron micrograph of the sample surface after electrophoretic deposition from the concentrated CuO NP dispersions (5000 mg/L) in ethanol solvent on flat Ti-coated glass substrates. (a) with 0.5 wt.% AcAc surfactant (b) without any surfactant.

For comparison, we prepared a planar SEM micrograph of the sample surface after four EPD cycles from the dispersion without surfactant (Fig. 6b). It follows that the same EPD step (under identical conditions) from a dispersion without surfactant does not result in a micrometer-thick nanoporous CuO coating. Instead, the sample surface after the EPD step is only partially

Figure 4.9 Secondary electron micrograph of a cross-sectioned sample after electrophoretic deposition from the concentrated CuO NP dispersions (5000 mg/L) in ethanol solvent with 0.5 wt% AcAc surfactant on flat Ti-coated glass substrates. covered with CuO NP agglomerates; the loosely-packed patches of deposited CuO NP agglomerates have a thickness of up to 4 μm, which is well below the coating thickness achieved for the dispersion with AcAc surfactant. These results indicate that the addition of AcAc surfactant does not only promote the formation of stable agglomerates in the CuO NP dispersion, but is also needed to promote layer formation during subsequent electrophoretic deposition of the same agglomerates. This suggests that the addition of AcAc surfactant to the dispersion not only shield the effective repulsive forces between the CuO NP aggregates and agglomerates in the dispersion and hence promoting attraction between them, but also results in a net attractive interaction between neighboring agglomerates deposited on the substrate surface during the EPD step, thus promoting laterally homogeneous layer formation. In the absence of AcAc surfactant, the attractive interactions between neighboring agglomerates on the substrate surface are too weak (or likely even repelling), thus preventing layer formation.

Noteworthy, the EPD step was also performed for the same dispersions with 0.5 wt.% SDS surfactant. However, this EPD process failed to produce adequate layers due to the very high conductivity of the dispersions, which resulted in the solution heating up very fast and boiling when the default parameters were applied in the EPD step. While such fast heating of the dispersion could be counteracted by active cooling during the EPD step, it would be technically challenging to ensure accurate control and homogenous distribution of the temperature (and thus the viscosity).

The nanoporous CuO coatings as produced by EPD from the concentrated CuO NP dispersions with ethanol solvent and AcAc surfactant can obviously be envisioned for applications in the field of catalysis.289,290 In our present research, the obtained nanoporous CuO coatings will instead be used as a nanoporous scaffold for the production of Al/CuO nanocomposite thermite coatings by infiltration with Al metal, as will be presented in an upcoming paper. Such high energetic material systems with nano-sized components show promising application in the fields of combustion, propellants and joining.224,291–293

4.4 Conclusions

The particle mobility, size distribution and agglomeration behavior of diluted to concentrated (50 up to 5000 mg/L), non-aqueous CuO NP dispersions were investigated and tuned to achieve fast electrophoretic deposition (EPD) of micrometer-thick, nanoporous CuO films.

Ultrasonic treatment of the freshly-prepared CuO NP dispersions was essential to disrupt weakly-bounded aggregates and agglomerates in the original nanopowder, which was particularly effective in ethanol solvent due to its low viscosity. However, the concentrated CuO NP dispersions (50 to 5000 mg/L) in ethanol solvent were unstable without the addition of a surfactant and rather resembled a suspension with a bimodal size distribution (with mean particle sizes of 180 ± 24 nm and 580 ± 110 nm). The smallest CuO NP aggregates (∼180 nm) in ethanol solvent were composed of roughly 27 fused primary CuO nanocrystallites and reflected the average initial aggregate size in the nanopowder. The effective mobilities of CuO NP aggregates and/or agglomerates, as well as the conductivity of the dispersions, both decreased with increasing viscosity (i.e. with increasing hydrocarbon chain length) from ethanol to hexanol. Consequently, the rates of coagulation of initial aggregates and smaller agglomerates into larger agglomerates also decreased with increasing solvent viscosity.

The addition of AcAc or SDS as a surfactant changed the sign of the surface charge of the CuO NP agglomerates in ethanol solvent from negative to positive and effectively stabilized the dispersion. The addition of 0.5 wt.% PEG-1450, PEG-4000, PVP-K12 or PVP-K15 surfactant did not change the sign of the surface charge of the dispersed CuO NP agglomerates in ethanol solvent and, consequently, the corresponding agglomerate mobilities and dispersion conductivities were similar to pure ethanol.

Electrophoretic deposition from concentrated CuO NP dispersions (5000 mg/L) in ethanol solvent with 0.5 wt.% AcAc surfactant was successfully applied for synthesizing micrometer-

thick nanoporous CuO coatings, which can serve as scaffolds for the production of Al/CuO nanocomposite thermite coatings or as high-specific-surface-area catalysts. The addition of AcAc surfactant was a requisite to promote layer formation during the EPD step. In the absence of AcAc surfactant, the attractive interactions between neighboring agglomerates deposited on the substrate were too weak (or likely even repelling) to induce laterally homogeneous layer formation.

Reproduced with modifications from:

Dörner, L., Schmutz, P., Kägi, R., Kovalenko, M. V. & Jeurgens, L. P. H. Electrophoretic Deposition of Nanoporous Oxide Coatings from Concentrated CuO Nanoparticle Dispersions. Langmuir 36, 8075–8085 (2020).

Chapter 5. Electrophoretic Deposition of Cupric Oxide Coatings with Tailored Nanoporosity by Nanoparticle Aggregate Design

5.1 Introduction

Electrophoretic deposition (EPD) is known since the early 19th, but has currently gained increasing attention, because it enables easy and fast deposition of nanostructured materials.151–154,162 EPD is based on the directional migration of charged colloidal particles under an applied electric field between two electrodes, which allows to achieve fast coating deposition.162,272,294 The EPD process involves two principle steps: (i) the dispersed (charged) particles are directed towards the oppositely charged electrode by the applied electric field, and (ii) subsequently plated onto the surface of a (conducting) substrate.162,182,273

The resulting EDP coating typically has a porous structure, characterized by a high specific surface area (SSA), which offers unique properties as compared to their dense counterparts. For example, microporous oxide coatings are commonly used for water purification295 and catalysis.162 While different processes can be used to obtain micro- and nanoporous coatings,155 EPD is a promising method due to its simplicity, cost-effectiveness and low- temperature application, allowing coating deposition on a broad range of materials and on heat-sensitive compounds.156 The porosity and thereby the SSA can be tuned for such targeted applications by tailoring the dispersion properties and/or the EPD step, as demonstrated in the present study for EPD of nanoporous CuO coatings from CuO NP dispersions.

Copper oxide finds application in a wide range of different technologies, for instance catalysis 269 (electrochemical reduction of CO2), magnetic storage, printable electronics, energy conversion and storage, and recently also in thermites for joining.171,296,297 Notably, the copper- oxygen system features two stoichiometric oxides, cuprous (Cu2O) and cupric (CuO) oxide. For the envisioned application in the field of nanothermites for joining (see Ref. 296), the use of single-phase cupric CuO nanoparticles (NPs) is preferred,223,224 since it presents the most stable Cu oxide phase at ambient conditions according to bulk thermodynamics.225 Over the last few decades, a wide variety of methods (e.g. sol-gel synthesis,271 milling,226 electrodeposition,227 sonochemical synthesis,228 ultrasonic spray pyrolysis,229 hydrothermal synthesis230,231) have been used for synthesizing single-phase CuO NPs with controllable size and shape.148,149 Our group recently developed an economic green sol-gel synthesis route for easy production of CuO nanopowders consisting of submicron-sized, nanoporous CuO NP

aggregates with a very high SSA (>18 m²/g),271 which will be employed (among other commercial CuO nanopowders) in the current systematic EPD study.

One of the first reports on the fabrication of CuO thin films by EPD from nanoparticle dispersions, dates back to 2007 and described the effects of the oxide NP concentration and the EPD conditions on the resulting film morphology, as well as the influence of subsequent sintering on compactness and hardness.163 The characteristics of CuO/ZnO heterojunctions, as produced by EPD, were also studied.164 A more recent study on the production of photothermal absorbers by EPD employed Mg(NO3)2 as a binder to stabilize the NP dispersion in isopropanol solvent.276 The dispersion properties were analyzed with regard to the stabilizer concentration, the deposition time and the electric field to optimize the EPD process and resulting photothermal absorber properties.276 In another EPD study, porous graphene oxide was functionalized by ammonia to support the adhesion of CuO for non-enzymatic glucose sensing.298 EPD has also been used for producing a binder-free CuO nanosheet composite with multi-wall carbon nanotubes, which exhibits promising properties as an electrode material for lithium-ion batteries.165 EPD of Al/CuO thermites by co-deposition of micron-sized Al particles (with an oxide shell) and CuO nanoparticles, as dispersed at very dilute concentrations in a 3:1 ethanol/water solvent mixture, has also been demonstrated.139,292 As recently demonstrated by our group,299 electrophoretic deposition of micrometer-thick, nanoporous CuO layers can be performed from CuO NP aggregates dispersed in a primary organic solvent at concentrations as high as 5000 mg/L (i.e. much higher than the diluted NP concentrations in the range of 0.5 mg/L – 5 mg/L used in many other dispersion studies160,161). Such highly concentrated oxide NP dispersions are a prerequisite to produce micrometer-thick nanoporous oxide layers in a fast and easily scalable EPD process.162 Notably, aqueous-based dispersions cannot be used for EPD of nanoporous CuO coatings, since the applied external voltages by far exceed the water stability potential range and would induce the splitting of water 182 into its basic components H2 and O2.

Previous studies on the EPD process of porous oxide coatings from oxide NP dispersions have typically selected a given combination of solvent, surfactant and oxide nanopowder for investigating the influence of the deposition parameters on the resulting oxide coating 300 301 morphology (e.g. for multiphase oxide coatings of ZrO2-Y2O3-CeO2, Al2O3-ZrO2, SiO2- 302 303 TiO2 and hydroxyapatite-ZrO2 ). Up to date, only a very limited number of studies have systematically investigated the effects of the dry and the dispersed nanopowder characteristics on the resulting nanoporosity and respective SSA of the deposited coating, in particular, the effects of the size and shape of the primary NPs, of their fused aggregates, as well as of their dispersed agglomerates. This is the main focus of the present study. The systematic EPD

investigations for both commercially and in-house produced nanopowders, as performed in the present study, reveal the complex interdependencies of the dry nanopowder characteristics (NP and aggregate shape, size, morphology, and SSA), the CuO NP dispersion properties (NP concentration, time-dependent agglomerate size distribution, effective surface charge, electrophoretic mobility, conductivity), the EPD conditions (applied electrical field, electrode spacing), and the resulting coating microstructure (thickness, porosity and morphology). The thus-obtained fundamental knowledge allows control of the nanoporosity and SSA of electrophoretic deposited oxide coatings for targeted applications in the field of e.g. catalysis and reactive joining.

5.2 Experimental section

Materials and chemicals

In this study, six different CuO nanopowder types were employed to prepare CuO dispersions for subsequent EPD. One type of CuO nanopowder was in-house synthesized by an optimized sol-gel synthesis route.271 The other nanopowder types were purchased from different commercial vendors, as listed in order of increasing SSA in Table 5.1. The individual CuO nanopowders will be further designated as SSA1 to SSA6 throughout this work (i.e. SSA1 having the lowest SSA and SSA6 having the highest SSA). According to the vendors' specifications, the nanopowder types have primary NPs (i.e. discernible globular NPs representing the smallest building blocks) with sizes in the range of 25 - 55 nm with SSA values between 13 - 39 m2/g. Generally, no information on the size and shape of the NP aggregates, i.e. the clusters of physically fused NPs, is provided. Therefore, all nanopowders were also characterized in-house by X-ray diffraction (XRD), transmission electron microscopy (TEM) and BET (Brunauer-Emmet-Teller method). The thus-obtained values for the primary NP size, crystallite size and SSA of the different nanopowder types are gathered in Table 5.1. For the dispersion of the CuO nanopowders, ethanol (99.8%, C2H6O, from Merck / Fluka Analytical) and acetylacetone (AcAc; a bidental aprotic ligand with formula C5H8O2, from VWR) as surfactant were used.

Table 5.1 In-house synthesized and commercially available CuO nanopowders used in this study, as listed in order of increasing specific surface area (SSA). The SSA values, as specified by the vendor and as-measured by BET, are given. Furthermore, the average values for the primary CuO nanoparticle (NP) size, as specified by the vendor and as-measured by TEM, and of the primary crystallite size derived from XRD, are listed.

NP size Primary SSA SSA NP Size Vendor specified crystallite specified by By TEM by vendor size by XRD by vendor BET (nm) (nm) (nm) (m²/g) (m²/g)

SSA1 Alfa Aesar 30-50 61 ± 30 17 ± 4 13 7 GetNanoMateria SSA2 30 90 ± 69 32 ± 7 13 8.5 ls US Research SSA3 25-55 40 ± 10 15 ± 5 14 11 Nanomaterials SSA4 Empa271 n.a. 38 ± 8 25 ± 7 n.a. 19 SSA5 Sigma Aldrich < 50 36 ± 13 28 ± 5 29 20 SSA6 PlasmaChem 40 23 ± 5 19 ± 6 39 35

Nanopowder characterization

The average primary crystallite size of the CuO nanopowders was investigated by XRD using a PANanalytical X’Pert Pro Multi-Purpose X-ray diffractometer. The XRD data were collected in the 2Θ range of 10° – 100° with a step size of 0.026° using Cu-Kα1–2 radiation (λaverage= 0.15418 nm, 45 kV and 40 mA). The average size D of the CuO nanocrystallites can be estimated from the peak broadening change of the CuO reflections using the Debye-Scherrer equation,

= (5.2.1) cos( ) 𝐾𝐾 𝜆𝜆 𝐷𝐷 𝛽𝛽 𝛩𝛩 where β is the full width at half maximum of the respective reflection with Bragg angle Θ, K is a numerical factor (here: K = 0.9, which is a good approximation for spherical particles in the absence of detailed shape information 196–198), and λ is the wavelength of the incident beam (here Cu-Kα).199,200 A correction for the instrumental peak broadening was omitted in view of the very pronounced size broadening caused by the NPs. For the nanopowder analysis by TEM (JEOL JEM-2200FS operated at accelerating voltage of 200 kV), the nanopowders were first dispersed in ethanol without surfactant, ultrasonificated for 1 h and subsequently transferred onto a gold grid (300 mesh, TED PELLA, INC). For determining the average size of the primary NPS by TEM, the size of 20 to 50 individual particles was measured. Notably, the derivation of the average NP size from TEM images can be error-prone due to limited statistics, especially in case of highly aggregated NPs. The SSA of the CuO nanopowders was determined experimentally from a 5-point N2-adsorption BET-isotherm, measured with a

Beckman-Coulter SA3100 instrument. Before the BET analysis, the powder samples were dried for 2 h at 180 °C in synthetic air.

Preparation and analysis of the oxide NP dispersions

Unless stated otherwise, all CuO NP dispersions were prepared according to the previously established procedures.299 The CuO NP dispersions were prepared in ethanol solvent with a CuO NP concentration in the range of 50 mg/L - 10 g/L, and a constant AcAc surfactant concentration of 5 wt.%. This surfactant concentration is sufficiently high to achieve a similar surfactant coverage of the dispersed NP aggretaes and agglomerates for the different CuO NP concentrations used in the present work. No extra conditioning steps of the nanopowders (e.g. washing or drying) were performed prior to usage of the nanopowders. The ethanol solvent and the surfactant (AcAc) were first mixed by stirring. Next, the defined amount of nanopowder was added. Next, all dispersions were ultrasonicated in an ultrasonic bath for 1 hour.299 The extended ultrasonic treatment procedure aims at disrupting weakly-bonded agglomerates in the dispersed nanopowder in order to obtain a fresh dispersion that is representative of the NP aggregate size of the dry nanopowder.299 Dynamic Light Scattering (DLS) analysis of the "fresh" dispersions were conducted directly after ultrasonication to determine the evolution of the agglomerate size distribution with time (using a Zetasizer Nano ZS from Malvern Instruments Ltd., Malvern, UK; equipped with a max. 4 mW He-Ne laser emitting at 633 nm). Each DLS measurement was performed at the non-invasive backscatter angle (NIBS) of 173° at a temperature of 25 °C, and was preceded by a 30 s equilibration time. For the Zeta-Potential measurements (using the Smoluchowsky-Model), the same device with a ZEN1002 dip cell and automatic voltage selection was used. 10 successive measurements with 60 s intervals were performed to monitor the stability of the dispersions. Mean agglomerate sizes, effective mobilities, as well as conductivities of the different NP dispersions were determined for the initial state of the dispersions by averaging over the measurements for the first 2 min, and for the stabilized state by averaging over the measurements between 7 min and 10 min. Notably, the electrophoretic mobility was determined using a maximum voltage of 10 V at a constant electrode distance of 2 mm, corresponding to a relatively low electrical field of 50 V/cm. In addition, the conductivities of more concentrated NP dispersions (i.e. 5 g/L and 10 g/L) at much higher electrical fields (i.e. 750 and 200 V/cm respectively), as applied for the EPD step, were derived from the monitored current evolution upon EPD with time.

Electrophoretic deposition procedure

EPD of nanoporous CuO films from the NP dispersions was conducted using a Keithley Sourcemeter 2400. For the first set of depositions, a Ti PVD coated glass slide was used as a counter electrode, while the working electrode was PVD coated with Au. The electrodes were placed in parallel at a distance of 1 mm. For each electrode, an area of 7×7 mm2 was immersed in the NP dispersion with a default CuO NP concentration of 5 g/L. The deposition procedure was done using a potentiostat applying 4 potential pulses at 75 V (corresponding to an applied electrical field of 750 V/cm) for a duration of 120 s, each preceded by a 30 s ramp from 0 V to 75 V. Between the pulses, the system was allowed to rest for 60 s at a potential of 1 V, resulting in a total deposition time of 13 min. In a second set of measurements, the electrodes were placed in parallel at 5 mm distance, while increasing the pulse duration and voltage to 450 s at 100 V (corresponding to an electrical field of 200 V/cm), and increasing the NP concentration to 10 g/L. During the EPD process, the glass electrochemical cell containing the dispersion was placed in an ice bath to reduce evaporation of the solvent. After the EPD step, the electrodes were slowly lifted out of the dispersion, soaked in CHCl3 to remove the surfactant, and finally rinsed with ethanol. The conductivity σ of the dispersion during the EPD process can be calculated as follows: The electrical resistance R is given by

= , (5.2.2)

𝑅𝑅 𝑈𝑈⁄𝐼𝐼 with U being the applied voltage and I the measured current. The electrical resistivity ρ is given by

= , (5.2.3)

𝜌𝜌 𝑅𝑅 ∙ 𝐴𝐴⁄𝑙𝑙 with A being the area of the immersed electrode, and the distance between the electrodes.

The respective conductivity σ is then obtained from 𝑙𝑙

= 1 . (5.2.4)

𝜎𝜎 ⁄𝜌𝜌 Determining the actual voltage drop in the electrolyte is not completely straightforward, because the applied voltage also includes voltage drops at the two electrode/dispersion interfaces. However, for the relatively high voltages applied in this study, these voltage drops are very small compared to the voltage drop across the electrolyte, and can be neglected.

Characterization of the coating microstructure

The morphology of the EPD oxide deposits was investigated using a Hitachi S-3700N scanning electron microscope (SEM), equipped with an energy-dispersive X-ray detector (EDX) (Ametek EDAX, Octane Pro). The thickness of the deposited layers was determined using a profilometer (Bruker Dektak XT) with a stylus radius of 2 μm, a stylus force of 3 mg and trace resolution of 0.833 μm/pt. Cross-sections of the deposited oxide coatings were prepared by breaking the samples and milling the fractured edge with an IM4000 Ion Milling System (Hitachi) using a defocused Ar ion beam (6 kV accelerating voltage, 1.5 kV discharge and 0.09 3 cm /h Ar gas flow). The porosity P of the coating follows from the fraction of pore volume Vpore relative to the total volume Vtotal, which can be estimated from the 2-D cross-sectional SEM micrographs. To this end, the cross-sectional SEM micrographs were converted to binary black-and-white images using a standard imaging software package. An estimate for the porosity was then obtained by dividing the summed black intensity (associated with the pores) by the summed bright intensity (corresponding to CuO). The pore analysis by SEM primarily detects the larger-scale inter-agglomerate/aggregate micro-porosity in the deposited coating. The small-scale nano-porosity in-between the individual nanoparticles of the coating can only be assessed by TEM (or high-resolution SEM), but is generally closely related to the SSA determined for the dry nanopowders.

5.3 Results and discussion

Characterization of the «reference» nanopower (SSA1), its dispersion and resulting coating microstructure

In a previous study,299 the influence of different combinations and concentrations of solvents and surfactants on the dispersability and agglomeration behavior of the commercial SSA1 CuO nanopowder was investigated in detail using light scattering techniques. XRD analysis revealed an average crystallite size (representative of the smallest diffracting domains) of 17.0 ± 4.0 nm for the SSA1 nanopowder (Table 5.1), which can be compared with an average primary NP size of 60.9 ± 30.2 nm by TEM (Fig. 5.1a). The considerably larger size of the primary NPs obtained from TEM in comparison to the crystallite size obtained from XRD indicates that the primary CuO NPs of this nanopowder can consist of several grains (i.e. crystallographic domains; cf. e.g. dark structures within the individual NPs in Fig. 5.1a). TEM analysis of the nanopowder also clearly shows the presence of (firmly-bonded) NP aggregates and/or (weakly-bonded) agglomerates with an irregular shape and high compactness (see inset in Fig. 5.1a; note that a distinction between aggregates and agglomerates is generally

difficult by TEM). BET analysis of the SSA1 nanopowder gives a specific surface area of 7 m²/g, which is in agreement with our previous analysis.299 Following the previously established procedures,299 ethanol was selected as a solvent with acetylacetone (5 wt.%) as a surfactant for preparing the CuO NP dispersions for analysis of the dispersion properties (at concentrations of 50 and 500 mg/L) and for the subsequent EPD step (with higher concentrated dispersions).

Figure 5.1 Characterization of the commercial SSA1 CuO nanopowder. (a) Representative TEM micrographs of the nanopowder at two different magnifications. (b,c) Time-resolved DLS of the respective SSA1 dispersion for CuO NP concentrations of 50 and 500 mg/L (for interpretation of the color scale see Fig. 5.3). (d) Cross-sectional SEM micrographs of the EPD coating, as deposited from a concentrated 5 g/L SSA1 dispersion at 1 mm electrode spacing. (e) Results of the DLS and Zeta-potential measurements (also see Table 5.2).

The DLS analysis was performed over a duration of 10 minutes, starting practically directly after the ultrasonic treatment of the dispersions (to disrupt weakly-bonded agglomerates in the dispersed nanopowder). The results of the time-resolved DLS measurements are shown Fig. 5.3; the size distributions are presented as relative intensity plots with discrete size ranges ("size bins"). For a low SSA1 NP concentration of 50 mg/L, the time-resolved DLS measurements revealed a relatively narrow size distribution of the agglomerates and a mean size of 337 ± 26 nm (Fig. 5.1b, e), which is similar to the size of the aggregate, respectively agglomerate structures

observed in TEM (cf. Fig. 5.1a). Notably, DLS only provides a measure for the effective agglomerate size in dispersion; but trends for the actual agglomerate size and morphology (e.g. degree of compactness) may be inferred on the basis of the TEM analysis (cf. Fig. 5.1a). The size distribution measured by DLS remains stable during the total measurement time of 10 min. Hence, little agglomeration tendency exists at the given conditions, despite the comparatively low value of the Zeta-potential (dispersions with an absolute Zeta potential ≤ 4 mV are often classified as highly instable against further agglomeration), which may be attributed to the low NP concentration. Indeed, the rate of agglomeration generally increases with increasing NP concentration in the dispersion.299 At a higher SSA1 NP concentration of 500 mg/L, the size distribution strongly broadens within the first minutes and the respective mean size increases to 1417 ± 423 nm (Fig. 5.1c, e). This shows that for more concentrated dispersions, primary NPs and their fused NP aggregates cluster into larger weakly-bonded agglomerates, which can again break down into smaller fragments, or eventually precipitate from the solution beyond a certain critical size.299 The continuous formation, re-fragmentation, and precipitation of these agglomerates in the dispersion results in the observed size fluctuations over the DLS measurement time (see Fig 1c). Notably, after the initial strong broadening of the agglomerate size distribution and increase of the mean agglomerate size, the size distribution appears to stabilize, indicating that a dynamic equilibrium between agglomeration and re-fragmentation is reached.

The concentration of the CuO NPs also has an effect on the Zeta-potential and corresponding electrophoretic mobility: For dispersions of higher concentration, a larger total CuO surface area is accessible for the AcAc surfactant (which is in excess for all CuO concentrations used in this work). Acetylacetone coexists in a keto and an enol form when dissociated in ethanol, and can act as a weak acid. Primarily, the anion of the enol form acts as the surfactant which is adsorbed at the CuO surface, leaving its cation (i.e. H+) dissolved, thereby decreasing the pH of the dispersion. When a larger CuO surface area is available for adsorption, more anions are removed from the dispersion, resulting in an increased acidity of the dispersion. According to Nernst's equation, the pH has a great impact on the surface charge of the NP aggregates: an increased proton concentration results in a more positive surface charge (this mechanism principally also holds for non-aqueous solvents).283,285,288,304 The increase of the net surface charge of the CuO agglomerates helps to stabilize the dispersions with higher concentration against further agglomeration. In addition, also the electrophoretic mobility and the conductivity in the SSA1 dispersion increase with increasing concentration (Fig. 5.1e), which is beneficial for the EPD step.

For the EPD step, a fresh (ultrasonicated) SSA1 NP dispersion with a default NP concentration of 5 g/L was used. Dispersions with higher CuO NP concentrations are much more efficient for fast deposition of micrometer-thick oxide coatings by EPD, but do not allow a detailed characterization of the dispersion properties due to the limited light penetration depth of the DLS analysis.299 However, it may be assumed that the trends in the dispersion properties with increasing CuO NP concentration, as observed for low concentrations (i.e. 50 to 500 mg/L), can be extrapolated to higher concentrations. For the deposition, a 1 mm distance between the Ti and Au electrodes, and a maximum potential of 75 V, corresponding to a field strength of 750 V/cm, were chosen. The coating thickness resulting after a net deposition time of 13 min equals 40 ± 13 μm, as determined by profilometry. Cross-sectional SEM analysis showed that the thus-obtained coatings are composed of irregularly dispersed and densely clustered CuO NP agglomerates and/or aggregates with some porosity of similar size (see Fig. 5.1d). An estimate of the coating porosity as large as 43 % was obtained from the cross-sectional SEM analysis. The dispersed CuO NP agglomerates in concentrated SSA1 dispersions have a broad size distribution with a large average size of 1296 ± 393 nm, resulting from clustering of individual aggregates in the dispersion. Evidently, subsequent electrophoretic deposition of this NP agglomerate dispersion leads to a porous coating obtained by EPD with larger pores between irregularly packed and relatively large CuO clusters.

Effect of the nanopowder characteristics on the dispersion properties

Analysis of the SSA1 reference nanopowder (see Fig. 5.1) indicated a close relation between the characteristics of the nanopowder, its respective CuO NP dispersion and the resulting CuO coating microstructure. To elucidate these interdependencies, firstly the relation between dry nanopowder and dispersion characteristics was analyzed systematically. Following the procedure exemplified above for the SSA1 nanopowder, the purchased and in-house produced dry nanopowders were characterized by XRD and TEM (see Table 5.1). It follows that the primary crystallite sizes of the dry nanopowders (by XRD) vary within a relatively narrow range from about 15 - 30 nm and do not correlate with the SSA of the dry nanopowder. The primary NP size of the dry nanopowders (respectively primary NP surface area), as determined by TEM in this study does correlate with the SSA; for example, the SSA5 and SSA6 nanopowder batches having the smallest primary NP size also show by far the largest SSAs. Correspondingly, the primary NP size is inversely related to the SSAs, with the exception of SSA2. The SSA2 batch has a larger SSA than the SSA1 reference batch, although statistical TEM analysis yielded a larger primary NP size. This slight inconsistency

can be attributed to the relatively broad NP size distributions of the SSA1 and SSA2 batches (see Table 5.1). Notably, no correlation between the primary NP size and the SSA is found based on the specifications provided by the supplier. This implies that the values of the NP size and SSA, as specified by the different suppliers, need to be handled with caution, since it is not clear how these specifications were determined, and to what extend ageing of the nanopowders affects their characteristics. Generally, also the information provided on the NP aggregate size and shape is limited. Therefore, in the following, only the in-house determined nanopowder characteristics (primary crystallite size, primary NP size, aggregate morphology, and SSA), as gathered in Table 5.1, will be considered.

TEM micrographs of the dispersed and subsequently dried nanopowders are shown in Fig. 5.2. It follows that the nanopowders with larger primary NP sizes generally also exhibit a higher degree of clustering into larger and more compact aggregates and/or agglomerates: While the larger primary NPs of batches SSA1 and SSA3 form almost micrometer-sized compact clusters on the TEM grid (less pronounced for SSA 2), the smaller primary NPs of batches SSA4 to SSA6 cluster into more airy, less-densely packed aggregates and agglomerates. Hence, the TEM analysis indicates that the increase in SSA not only inversely correlates with the primary NP size (as discussed above), but also coincides with a general decrease of the compactness of the NP aggregates and agglomerates in the dry nanopowders. This coincidence of high SSA and small primary NP size on the one hand, and less dense NP aggregates on the other hand, are related to the respective NP synthesis conditions (which are unfortunately not disclosed by the suppliers).

Figure 5.2 TEM micrographs of the dry nanopowders as listed in Table 5.1. Scale bars: 20 nm and 0.1 μm (insets).

Next, the relation between the dry nanopowder characteristics and the dispersion properties will be addressed. To this end, the different CuO nanopowders were dispersed in ethanol with 5 wt.% AcAc surfactant, following the previously established procedures.299

Figure 5.3 Time-resolved DLS contour plots of the agglomerate size distributions for the different CuO nanopowders dispersed in ethanol at the indicated concentrations (50 and 500 mg/L) with 5 wt.% acetylacetone as surfactant (as measured directly after the ultrasonic treatment). The color-coded scale bar indicates the corresponding size intensity scale.

DLS analysis of the freshly prepared dispersions was performed for CuO NP concentrations of 50 mg/L and 500 mg/L. The thus determined size distributions of the agglomerates in dispersion are shown in Fig. 5.3. The corresponding mean agglomerate size in dispersion, and the effective surface charge and electrophoretic mobility, as well as the conductivity of the dispersion (by Zeta-potential measurements), are listed in Table 5.2. The chemical interaction

between the surface of the primary CuO NPs and the ethanol solvent in the presence of 5 wt.% AcAc should be similar for all CuO nanopowders. Observed changes in agglomeration behavior and the effective surface charge should therefore mainly depend on the characteristics of the dispersed NP aggregates and agglomerates (e.g. shape, size, SSA and morphology).

As reflected in Fig. 5.3, the measured size distributions of the dilute 50 mg/L dispersions are typically much narrower than the more concentrated 500 mg/L dispersions, as already observed for the reference nanopowder SSA1. Generally, the trends found for the average agglomerate size of the freshly prepared dilute dispersions (also see Table 5.2) and for the aggregate sizes observed by TEM are in good agreement, i.e. nanopowders with smaller aggregate sizes (as well as smaller primary particle sizes and larger SSAs, see discussion above) also have a smaller initial agglomerate size in dispersion. This indicates that the initial mean agglomerate size in dilute solution is dominated by the size and morphology of the NP aggregates of the nanopowder. The dilute dispersions also show a more or less stable or only slightly increasing mean size distribution over the course of the measurement time of 10 min. Exceptions are SSA2 and SSA4 dispersions, for which the size distributions broaden after a few minutes, indicative for stronger agglomeration tendencies. By comparison, the DLS analyses of the concentrated dispersions show relatively strong size fluctuations, i.e. a distinct broadening of the detected particle size distribution with time. As discussed above, for the reference nanopowder SSA1, this indicates that for the concentrated dispersions, relatively large agglomerates are formed by clustering of primary NPs and their aggregates in the first few minutes after preparation of the dispersion, accompanied by a broadening of the size distribution. Agglomeration continues until a dynamic equilibrium between agglomerate formation and re-fragmentation is reached, indicated by size fluctuations. Especially the SSA4 and SSA5 dispersions have relatively broad size distributions, which also tend towards the development of a bimodal size distribution, with one size population comparable to the 50 mg/L dispersion and a second population representative of much larger agglomerates. Notably, the dispersed SSA3 and SSA6 nanopowders maintain a relatively narrow size distribution also in the concentrated dispersions. TEM analysis of the SSA3 nanopowder revealed large NP aggregates with a relatively globular, compact shape (see Fig. 5.2). The SSA6 nanopowder showed much smaller, but also relatively compact aggregates (Fig. 5.2). Thus, a compact aggregate shape appears to hinder the formation of very large agglomerates in the dispersion even at high NP concentrations, possibly due to less favourable mechanical entanglement of the compact, more spherically-shaped aggregates.

The surface charges and effective mobilities of the dispersed nanopowders, as investigated by Zeta-potential measurements, are gathered in Table 5.2. Values for the dilute dispersions were evaluated for the freshly prepared dispersions to capture the characteristics of the initially formed agglomerates. Values for the higher concentrated dispersions were evaluated after ageing for 7 min to capture the characteristics of dispersions more similar to the ones used for EPD. A strong variation of the Zeta potential, respectively of the corresponding electrophoretic mobility, is found for the different nanopowders, both at dilute concentrations and at higher concentrations. Notably, no clear correlation between the Zeta potential and the SSA (or primary NP size) of the dry nanopowder is found (compare Table 5.1 and 3): for example, even though the SSA6 nanopowder has the smallest primary NP size and highest SSA (thus offering potentially more surface for the surfactant), it shows a lower Zeta potential and slightly larger agglomerate size in the dilute 50 mg/L dispersion as compared to the SSA5 dispersion. By contrast, a clear correlation exists between the initial Zeta potential and the observed initial mean agglomerate size determined by DLS for the dilute dispersions: a smaller mean agglomerate size coincides with a higher Zeta potential value. Since the initial size of the agglomerates is dominated by the size and morphology of the aggregates in the dry nanopowder (see discussion above), this indicates that these properties also determines the initial value for the Zeta potential in dispersion, i.e. agglomerates/aggregates with smaller initial size can establish a higher initial (innate) Zeta potential in the dispersion, e.g. by providing more surface area actually accessible to the surfactant and available for surface charging. Noteworthy, the nanopowders with a higher initial Zeta potential in the dilute dispersions generally also show a smaller increase in mean agglomerate size in the more concentrated dispersions, i.e. the higher innate Zeta potential stabilizes the dispersion against the formation of larger aggregates, also at higher concentrations (as to be expected). The nanopowder SSA3 is a clear exception to this trend (see Table 5.2). However, as discussed above, SSA3 contains very compact, large aggregates that may impede further agglomeration, despite its comparatively low Zeta value.

With increasing concentration, the Zeta potential strongly increases for the nanopowders with low initial Zeta potential (SSA1-SSA3), but decreases for the nanopowders with high initial potential (SSA4-SSA5), indicating that for the present dispersion system, a maximum in Zeta potential as function of particle loading exists. The electrophoretic mobility, which is directly related to the Zeta potential, follows the same trends as observed for the Zeta potential. For all nanopowders, the conductivity of the dispersions is comparatively low, indicating a low concentration of additional ions. With increasing NP concentration it slightly increases, which

can be directly ascribed to the higher number of charged particles present at higher concentrations, and the increasing acidity of the dispersions.

Thus, an increase in the dispersion concentration generally leads to an increase in mean agglomerate size, but is less pronounced for nanopowders with a small aggregate size and corresponding high initial Zeta potential. For nanopowders with a more compact, globular aggregate size (e.g. SSA3 and SSA6), the increase in mean agglomerate is less pronounced, resulting in a relatively narrow size distribution. The Zeta potential and the respective particle mobility increase with increasing NP concentration for relatively large initial aggregate sizes of the nanopowder (SSA1-SSA3). On the contrary, the Zeta potential and mobility values slightly decreases with increasing concentration for relatively small initial aggregate sizes (SSA4- SSA5). The conductivity of the dispersions increases with increasing nanopowder loading, but remains comparatively low. These general trends can probably be extrapolated for higher concentrations (as used for the EPD step), as long as the same chemical environment (especially a sufficient amount of available surfactant) is maintained.

Table 5.2 Mean agglomerate size, effective mobility and conductivity, as obtained from DLS and Zeta-Potential measurements of the different nanopowder dispersions at concentrations of 50 mg/L or 500 mg/L. The values for 50 mg/L were evaluated for the freshly prepared dispersions, the values for 500 mg/L for the dispersions after 7 min ageing (also see Fig. 5.2).

Particle Zeta- Mobility Conductivity Nano- Mean size Concentration Potential (μm·cm·V-1·s- (×10-4 mS·cm- powder (nm) (mg / L ) (mV) 1) 1)

50 337 ± 26 2.2 ± 0.1 0.10 ± 0.01 9.9 ± 0.3 SSA1 500 1417 ± 423 4.4 ± 0.7 0.20 ± 0.03 29.1 ± 0.2

50 209 ± 11 9.9 ± 0.3 0.46 ± 0.01 5.2 ± 0.3 SSA2 500 325 ± 60 17.3 ± 0.7 0.80 ± 0.03 6.4 ± 0.7

50 272 ± 24 3.7 ± 0.2 0.17 ± 0.01 7.3 ± 0.1 SSA3 500 422 ± 30 8.7 ± 0.3 0.40 ± 0.02 21.4 ± 0.3

50 217 ± 16 15.3 ± 0.3 0.71 ± 0.01 4.8 ± 0.3 SSA4 500 488 ± 90 12.0 ± 0.8 0.56 ± 0.04 40.6 ± 1.1

50 157 ± 8 19.4 ± 0.0 0.90 ± 0.00 15.0 ± 0.1 SSA5 500 360 ± 37 13.4 ± 0.7 0.62 ± 0.04 33.8 ± 0.3

50 166 ± 9 11.1 ± 2.4 0.52 ± 0.11 9.1 ± 1.1 SSA6 500 196 ± 3 13.3 ± 0.8 0.62 ± 0.04 23.1 ± 0.4

Effect of the dispersion properties on the EPD process and resulting coating microstructure

To investigate the different nanopowders for their layer-formation capabilities, electrophoretic deposition was first performed with concentrated 5 g/L dispersions, an electrode spacing of 1 mm and a high electric field strength of 750 V/cm. For all dispersions, micrometer-thick microporous CuO coatings could be successfully deposited. Depending on the specific dispersion, pronounced differences in the resulting coating microstructures, as reflected by the cross-sectional SEM analyses in Fig. 5.4a, can be found. In particular, large differences in porosity and coating thickness (cf. Table 5.3) occurred, depending on the type of nanopowder used. The microporosity of the EPD coatings (as determined by SEM image analysis) strongly correlates with the characteristics of the agglomerates in the concentrated dispersions (Fig. 5.4b and 3c, Table 5.2): The EPD process with the SSA3 dispersion, featuring large and compact agglomerates with a narrow size distribution, results in a high, irregular porosity with large pores. Notably, broad and/or bimodal size distributions can generally be beneficial for achieving higher particle packing densities, i.e. lower porosity.305 For the other nanopowders featuring broader size distributions, the microporosity closely follows the mean agglomerate size observed in dispersion. In case of SSA6, which has by far the smallest agglomerate size, apart from a few larger pores practically no micro-porosity was detectable by SEM.

Figure 5.4 (a) Representative cross-sectional secondary electron micrographs of the CuO coatings, obtained by electrophoretic deposition of the concentrated CuO NP dispersions using the different nanopowder types as listed in Table 5.1. The deposition was performed at an electrode distance of 1 mm and a CuO NP concentration of 5 g/L.

(b) Scatter plot of the SSA versus the average coating thickness. (c) Scatter plot of the SSA versus the coating porosity.

Generally, a high uniformity across the coating thickness was obtained, indicating that stable conditions for the EPD process, in particular also in the dispersions, were maintained during the EPD process. In contrast to the coating porosity, for the thickness (Table 5.3), no obvious correlation with the parameters determined for the dispersions (e.g. with the mean agglomerate size, or magnitude of the Zeta potential, respectively mobility) can be found under the present EPD conditions. Only in case of SSA6, a comparatively low thickness coincides with a small agglomerate size in the dispersion. As discussed above, the small agglomerate size in dispersion results in a very low microporosity, i.e. high compactness, of the deposited layer, which reduces the net thickness of the layer. In addition, it also leads to a slower effective growth rate of the deposited layer under the same deposition conditions.

It is thus concluded that the deposition rate and coating morphology can be tailored by optimizing the agglomerate size distribution in the dispersion, especially the mean agglomerate size, which strongly correlates with the aggregate size in the dry nanopowder.

Effect of the applied electric field on the EPD process

In a next step, the characteristics of the EPD process were analyzed in more detail, in particular with respect to its upscaling ability. To this end, the distance between the electrodes in the EPD cell was increased from 1 mm (see above) to 5 mm. Increase of the distance between the electrodes generally helps in maintaining a more homogeneous particle concentration upon EPD, but also implicitly leads in a decrease of the electric field strength at a constant applied potential. At 1 mm electrode spacing, a deposition potential of 75 V was applied, which corresponds to a relatively high electric field strength of 750 V/cm. To counterbalance the increased distance to some extent, the deposition potential was increased to 100 V for the depositions at 5 mm electrode spacing, which corresponds to an effective electric field strength of 200 V/cm. Under these conditions, the coating depositions of the SSA1, SSA3 and SSA4 nanopowder dispersions were not successful for NP concentrations of 5 g/L. As discussed, these dispersions feature a relatively low electrophoretic mobility, respectively Zeta potential. Consequently, a lower electric field strength exerts a weaker force on the agglomerates, leading to an insufficient deposition flux. Hence, to achieve coating deposition at 5 mm electrode distance for all nanopowder dispersions, the NP concentration of the dispersions was further increased to 10 g/L in order to increase the net flux, and to further increase the

effective surface charge, respectively mobility, by increasing the acidity of the dispersions (see discussion in 3.1). This way, again micrometer-thick CuO EPD layers could be obtained for all investigated nanopowders (see Table 5.3). Although the relatively low mobilities of the SSA1, SSA3 and SSA4 dispersions are still sufficient for efficient electrophoretic deposition at the applied low electric field strength, the achieved layer thicknesses are relatively small. The dispersions with a relatively high mobility benefit most strongly from the increase in NP loading, as reflected by a thicker layer deposit. Hence, for larger electrode distances and/or low electric field strengths, a high NP concentration in combination with a high effective mobility of the NP agglomerates in the dispersion becomes crucial to maintain a sufficiently high deposition flux.

Figure 5.5 Scatters plot of the thickness of the deposited EPD coating at two different electrode distances and field strengths (determined by profilometry) versus (a,c) the mean agglomerate size for a NP concentration of 50 mg/L (as measured by DLS) and (b,d) the mobility for a NP concentration of 50 mg/L (as represented by the measured Zeta-Potential). The EPD steps at electrode distances of 1 mm and 5 mm were performed at NP concentrations of 5000 mg/L (top panels, black data points) and 10 g/L (bottom panels, red data points), respectively.

Table 5.3 CuO coating thicknesses obtained by EPD from the different CuO nanopowder dispersions (by profilometry) for different electrode distances (delectrode), respectively electric field strengths, and respective NP concentrations (CNP).

Thickness Thickness (μm) Nanopowd (μm) delectrode = delectrode = 5 mm er 1 mm CNP = 10 g/L CNP = 5 g/L SSA1 33 ± 11 10 ± 4 SSA2 57 ± 14 36 ± 8 SSA3 43 ± 7 7 ± 3 SSA4 34 ± 15 8 ± 7 SSA5 61 ± 21 199 ± 39 SSA6 11 ± 3 75 ± 8

The conductivities of the nanopowder dispersions for NP concentrations of 50 mg/L and 500 mg/L were investigated at a relatively low electrical field of 50 V/cm by Zeta-Potential measurements (see Table 5.2). The conductivity of the concentrated NP dispersions at much higher applied electrical fields (>> 50 V/cm) can be directly monitored from the measured current evolution during the EPD process. Accordingly, the conductivity of the concentrated nanopowder dispersions (5 g/L for 1 mm and 10 g/L for 5 mm electrode spacing) during the EPD process were analyzed on the basis of the monitored current evolution for two different electrical field regimes: a high electrical field regime of 750 V/cm at 1 mm electrode distance and an intermediate electrical field regime of 200 V/cm at 5 mm electrode distance: see left and right panels of Fig. 5.6, respectively. The differently derived conductivities of the nanopowder dispersions at low, intermediate and high electrical fields (see Fig. 5.6c) are plotted as function of the NP concentration in Fig. 5.7. It follows that the conductivity increases with increasing NP concentration, in accord with the findings mentioned before.

Figure 5.6 Investigation of the conductivities of the studied nanopowder dispersions on the basis of the monitored current evolutions during the EPD process for two different electrical field regimes: 750 V/cm at 1 mm electrode distance (5000 mg/L, left panel) and 200 V/cm at 5 mm electrode distances (10 g/L, right panel). (a,b) Applied potential vs deposition time. (c,d) Measured current density as function of deposition time. (e,f) Calculated dispersion conductivities as function of deposition time.

With regard to Fig. 5.6, a minor contribution to the measured current by dissolved ions, which are also electrochemically deposited, cannot be excluded. It follows that the conductivity of the dispersions is co-determined by the agglomerate morphology (size and shape), the NP concentration, the effective surface charge, and the applied electrical field. As previously discussed, the agglomerate morphology correlates with the NP concentration and, to a lesser extent, with the effective surface charge; i.e. a higher concentration generally results in a larger agglomerate size with an associated increase of the effective surface charge, due to the change in acidity of the dispersion (see Table 5.2 and Fig. 5.7).

Figure 5.7 Conductivities as function of the CuO NP concentration. The conductivities for the more dilute dispersions were obtained from Zeta-Potential measurements (Table 5.2), whereas the respective values in the concentrated dispersions were obtained from the EPD process (Fig. 5.6).

The present study not only aims at the optimization of the nanopowder and dispersion characteristics for fast electrophoretic deposition, but also at the synthesis of CuO scaffolds with tunable microporosity for targeted applications in the field of catalysis and reactive joining. As discussed above, the coating porosity can only be effectively tuned by changing the agglomerate morphology and size distributions, which will generally also affect the efficiency of the EPD step. For example, the concentrated SSA6 dispersions are very efficiently deposited because of their high mobility and very small agglomerate sizes; however, the resulting porosity level of the EPD coatings is relatively low, and therefore insufficient for the targeted applications. By comparison, the SSA3 dispersion has a much larger mean agglomerate size, which results in a relatively high coating porosity (compare Figs. 3 and 4). However, its low mobility, associated with a large and compact aggregate size in the dry nanopowder, leads to highly insufficient layer formation properties under practical conditions, i.e. low effective field strengths. Hence, tuning of the coating porosity requires careful control of the agglomerate mean size and size distribution, stability, as well as mobility of the NP dispersion, which are strongly affected by the aggregate size and morphology in the dry nanopowder.

5.4 Conclusion

In this systematic study, a process to produce micrometer-thick, porous, nanostructured CuO coatings using electrophoretic deposition is described, which reveals the complex

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interdependencies between the dry nanopowder characteristics (e.g. NP and NP aggregate shape, size, morphology and SSA), the CuO NP dispersion properties (e.g. NP concentration, agglomerate size distributions, effective surface charge, electrophoretic mobility, conductivity), the EPD conditions (e.g. applied electrical field, electrode spacing) and the coating microstructure. To this end, six different CuO nanopowders with varying primary crystallite and NP sizes, NP aggregate morphologies and SSAs were compared with respect to their dispersion and coating characteristics. It is demonstrated that that thickness, porosity and deposition rate of the coatings strongly depends on the properties of the initial NP aggregates, as well as their dispersion characteristics. The evolution of the agglomerate size distributions in the dispersion are strongly affected by the shape, size and compactness of the primary NP aggregates in the dry nanopowder, as well as by the NP concentration in the dispersion.

Micrometer-thick coatings with variable porosity were successfully obtained from 5 g/L concentrated NP dispersions in ethanol solvent with 5 wt.% AcAc surfactant at 1 mm electrode distance under an electrical field of 750 V/cm. The coatings are composed of CuO NP aggregates (i.e. clusters of firmly bonded NPs) and larger agglomerates (i.e. clusters of weakly-bonded NP aggregates). Both the coating thickness and the microporosity of the EPD coatings increase with increasing agglomerate size in the dispersion.

The degree of NP agglomeration in the dispersion and thereby the mean agglomerate size increase with increasing NP concentration. For a relatively narrow electrode spacing of 1 mm and/or a very high electrical field of 750 V/cm, the deposition rate and coating morphology can be straightforwardly tailored by optimizing the NP concentration and the mean agglomerate size in the dispersion, which correlates with the NP aggregate size in the dry nanopowder. For larger electrode spacing and/or lower electrical fields, a high effective mobility of the NP agglomerates in the solution becomes crucial, since agglomerates with low mobility experience a too low force by the applied electrical field to contribute to the deposition flux. For larger electrode spacings (5 mm) and/or lower electric fields (200 V/cm), only the nanopowders with high mobility, which coincides with a small agglomerate sizes and high SSAs for the here investigated nanopowders, can still be deposited.

The coating porosity can only be effectively tuned by changing the agglomerate size distribution and the agglomerate compactness, which strongly depend on the size and shape of the aggregate in the dry nanopowder. Typically, nanopowder dispersions with a tunable mean aggregate size, but a defined mean primary NP size, are required to effectively tailor the coating porosity. To this end, the morphologies of the primary NP and their aggregates in the dry nanopowder needs to be carefully optimized.

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Reproduced with modifications from:

Dörner, L., Rheingans, B., Kägi, R., Kovalenko, M. V., Jeurgens, L. P.H., Schmutz, P. Electrophoretic Deposition of Cupric Oxide Coatings with Tailored Nanoporosity by Nanoparticle Aggregate Design. In preparation.

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Chapter 6. Advanced manufacturing of energetic metal- matrix Al/CuO thermites nanocomposites with pristine interfaces by CuO electrophoretic deposition and Al electrodeposition infiltration

6.1 Introduction

Since ancient times, different materials have been combined to obtain specific composite properties which differ from the individual constituent phases (e.g. hardness, strength, color, specific weight, thermal conductivity, thermal expansion).43,306 Up to date, such composite materials have been applied in numerous fields, including aeronautics, automotives, construction, cosmetics, sports, medical applications and robotics.73,74,307–310 The term nanocomposite is used if one, two or three dimensions of one of the constituent phases is in the nanoscale range (less than 100 nm). An important class of nanocomposites are so-called metal-matrix nanocomposites (MMNCs), composed of nano-sized particles, fibers or platelets of an intermetallic, ceramic and/or organic phase, embedded in a metal matrix. Many metals have been applied as matrix material in MMNCs (e.g. Al, Be, Mg, Ti, Fe, Ni, Co and Ag), with aluminum matrix composites having the broadest application range so far.311,312

MMNCs in e.g. machining, construction and transportation typically aim at a high specific strength and stiffness, which is sometimes combined with a tunable thermal expansion coefficient to reduce residual stresses (e.g. in brazed ceramic-metal joints).313 Such MMNCs are typically designed to be mechanically, chemically and/or thermally stable during long-term operation under harsh conditions (e.g. at elevated temperatures, in corrosive environments and/or under thermocyclic loading conditions). This requires that the MMNCs have a stable microstructure, i.e. thermodynamically stable constituent phases as well as stable interfaces. Hence, the constituent phases have no associated exothermic reactions, which greatly facilitates their synthesis and processing routes even at higher temperatures.

In recent years, the synthesis of so-called energetic or reactive MNNCs with a deliberately metastable microstructure for advanced applications in the fields of propulsion, sterilization, energy storage and nanojoining have attracted great interest.76,112,132,314 Energetic MMNCs can store substantial amounts of chemical energy, which can be released in the form of heat upon thermal activation of a "kinetically frozen" exothermic reaction between the constituent phases. The heat release of such energetic MNNCs can be tuned by tailoring the phase composition,

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whereas the reactivity (i.e. the kinetics of heat release) can be enhanced by maximizing the interface area between the reactant phases through nanostructure design. Evidently, the fabrication and processing of such energetic MMNCs is very challenging and much more elaborate than the production of stable MMNCs, because the reaction between the constituent phases can be very easily triggered (thermally activated) by mechanical and/or thermal processing steps.

Thermites constitute a specific class of highly energetic composite materials, which are generally composed of a metal oxide315, metal salt179,316 or non-metal oxide317 as the oxidizer phase and a pure metal with a high oxygen affinity (e.g. Al, Ti, Zr) as the fuel phase.166,167 A classical thermite system is the Al/Fe2O3 system, which has been used for many decades to 318–320 weld railroads. Heating of a homogenous Al/Fe2O3 powder mixture can trigger (ignite) a highly exothermic self-sustaining and self-propagating redox reaction between the Fe2O3 oxidizer and the Al fuel, according to: Fe2O3 (s) + 2Al (s)  Al2O3 (s) + 2Fe (l) with an associated reaction enthalpy of Δ = −121 kJ ∕mol−atom. Since this reaction is highly exothermic, part of the heat is consumed𝐻𝐻 for self-propagation of the redox reaction, whereas the remaining heat is consumed to produce molten iron for welding (with a low-density Al2O3 slag floating on the molten iron). The self-sustaining reaction triggered upon thermite ignition can be classified as self-propagating high-temperature synthesis (SHS).

At the macroscopic scale, substantial preheating is required to ignite a SHS reaction between 321 fuel and oxidizer (e.g. about 1600 K for the Al/Fe2O3 system ), which hinders its adaptation for the joining of smaller and/or more heat-sensitive materials and components. This obstacle has sparked interest in the development and fabrication of so-called nanothermites for nano- and micro-joining technologies.112,136,138 The reduction of the reactants to the nanoscale (e.g. by employing compacted nanopowder mixtures) drastically increases their contact area and also decreases their mutual diffusion distances, which results in much lower ignition temperatures, shorter ignition delays and higher reaction rates compared to conventional micron-sized thermites.112,124 Their ability to generate large amounts of heat locally on small scales makes them ideal candidates for various joining applications, e.g. to serve as an internal heat source for soldering. Yet, nanothermites have an even broader range of applications, for example as actuation parts222,322 or as gas generators.323,324 They are also used as propulsion units325–327 and are added in explosives328,329 and propellants.330–333 The design of such nanothermites in the form of a dense MMNC, composed of a nanodispersed oxidizer phase in a fuel metal matrix, is very beneficial as it allows the reaction to occur in an oxygen-free environment, even in vacuum, making it attractive for military and aerospace applications.334,335 Especially for joining applications, compact nanothermites are preferred due to reduced gas

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involvement during the reaction. Aluminum is used as a typical fuel in many nanothermites, forming highly caloric redox systems with several oxidizers such as WO3, CuO, Co3O4 and 167,177,178,336 3 Fe3O4 with a high combustion enthalpy of the order of 80 kJ/cm . This makes Al- based nanocomposites very interesting as energetic materials. In case of an Al/CuO-thermite, the exothermal reaction proceeds according to

116 3 CuO + 2 Al → 3 Cu + Al2O3 ΔH = -1'193 kJ/mol . (6.1.1)

For joining applications, the Cu content, which is produced in-situ by the reaction, can be directly utilized as a filler material for bond formation.

The simplest approach for producing nanothermites is by mechanically mixing and compacting nanopowders of the fuel and oxidizer phases. In addition, nanothermites can be produced by sol–gel synthesis,171,172 arrested reactive milling173,174,337, as well as sputtering136,137,175. Electrostatic self‐assembly based on charging nanoparticles in aerosols176 and functionalization with charged ligands141 have also been employed for nanothermite fabrication. Several studies have shown that ignition and combustion behavior of nanothermites can be altered by changing the size and the distance of their constituents.338– 340 Smaller particles, closer proximity (i.e. intimate contact areas), and a higher degree of compaction generally lead to a significantly enhanced reactivity125,138,168–170, i.e. to lower ignition temperatures and enhanced combustion including higher burn and propagation rates.168

Despite the recent progress made, the synthesis and processing of highly energetic nanothermites generally still entails some fundamental challenges: (i) The onset of the thermite reaction (or other parasitic reactions) must be suppressed during production. This usually requires minute control of the process parameters (e.g. during arrested reactive milling, or sputtering)123,337. (ii) The reaction of the metal fuel with residual oxygen must be kept to a minimum, in particular for production routes involving nanopowders. One of the major challenges in the production of Al-based nanothermites is to prevent the practically inevitable 167,180,341 formation of a thin surficial Al2O3 shell (2-4 nm) around the Al particles. This thin oxide acts as a diffusion barrier between the oxidizer and the fuel, thereby hindering the propagation and the completion of the thermite reaction.181 (iii) The microstructure (e.g. density and homogeneity) of the nanothermite must be controlled down to the nanoscale to ensure a high and homogeneous reactivity. Many of these challenges can be more easily tackled by shifting from physical nanopowder mixing routes to electrochemical deposition routes at ambient temperature. For example, Ni–Al–Al2O3 MMNC coatings with Ni as the matrix and Al and Al2O3

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as second‐phase particles were produced by electrochemical co-deposition from a dispersion 342 of Al/Al2O3 nanoparticles in an electrolyte containing a metal salt (e.g. Ni). During electrochemical deposition of the metal, the reinforcing nanoparticles are co-deposited, thus forming a MMNC coating. However, the simultaneous co-deposition of nanoparticles with the matrix component can be difficult to control, which makes the production of defined microstructures challenging. In addition, co-deposition requires highly dispersed nanoparticles, which also need to be chemically and sterically stable in the used electrolyte. More refined electrodeposition approaches for the production of (magnetic) MMNCs have instead employed a two-step process by first fabricating a nanostructured porous film, which is subsequently infiltrated with a metal using electrochemical deposition.343

To the best of our knowledge, the two-step synthesis of highly energetic MMNCs by electrophoretic deposition of a nanostructured oxidizer scaffold, followed by electrodeposition of the metal fuel from an ionic liquid, as demonstrated in the present study, has not yet been reported, but could provide significant benefits. Namely, by introducing the metal fuel using electrochemical deposition from an ionic liquid, the oxidizer/fuel interface can be kept free of a fuel-oxide layer, thus obtaining a pristine fuel/oxidizer interface. In addition, the electrochemical deposition of the metal fuel can be performed at ambient temperature with negligible interdiffusion between phases and energy impact for the thermite system. As such, pristine oxidizer/fuel interfaces can be obtained, ensuring maximum reactivity of the thermite system. In addition, pre-manufacturing of the nanostructured oxidizer scaffold provides additional control of the fuel-to-oxidizer ratio and thereby the thermite energetics. Finally, the production of thermite MMNC coatings by electrodeposition methods can provide access to additional technologies needing local electrodeposition (e.g. patterned deposition by use of photolithography). Major challenges that must be addressed for realizing the proposed electrochemical thermite production are the stability, with the risk of reduction, of the oxidizer scaffold upon electrochemical deposition of the fuel, and homogeneous filling of the porous oxide scaffold upon metallic fuel deposition. In this work, a new two-step approach for producing highly energetic MMNCs with pristine interfaces was developed, which consisted of the fabrication of an oxidizer scaffold by electrophoretic deposition, followed by electrodeposition infiltration with a metal fuel from an ionic liquid. The two-step synthesis route is demonstrated for the production of dense nanothermite MMNC coatings with a pristine (unreacted) Al/CuO interface and without a significant amount of contaminants. Parameters governing the density of the nanocomposite were investigated and optimized to generate a reactive Al/CuO MMNC foil, which could be further optimized for joining applications.

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6.2 Experimental section

Materials and chemicals

Two different CuO nanopowders were employed to build nanostructured scaffolds of the oxidizer phase by electrophoretic deposition. One nanopowder was purchased from GetNanoMaterials (with a specified nominal primary NP size of 30 nm), further denoted as GNM nanopowder. The second nanopowder was synthesized in-house by an adopted sol-gel synthesis route,271 further designated as SG nanopowder. As shown in our previous study,344 a single primary NP in the dry nanopowder (representative of the smallest building block) can be composed of several primary crystallites (i.e. "nanograins"). Accordingly, characterization of the dry GNM and SG nanopowders was performed by determining the mean primary crystallite size using XRD and the mean primary NP size by TEM, as well as the specific surface area (SSA) by BET.344 The dry nanopowders have mean primary crystallite sizes of 32 ± 7 nm (GNM) and 25 ± 7 (SG) with corresponding mean primary NP sizes of 90 ± 69 nm and 38 ± 8 nm.344 The dry nanopowders have SSA's of 9 m²/g (GNM) and 19 m²/g (SG), which indicates a much stronger aggregation of the GNM nanopowder. The nanopowder dispersions were prepared in ethanol (99.8%, C2H6O) solvent from Merck / Fluka Analytical with the addition of acetylacetone (AcAc, a bidental aprotic ligand with formula C5H8O2, from VWR) as a surfactant. The ionic liquid [BMIm]Cl*AlCl3 (ratio 1:2) was purchased from Iolitec.

Preparation of the CuO NP dispersions

Concentrated CuO NP dispersions for the electrophoretic deposition step were prepared by mixing ethanol solvent and AcAc surfactant by stirring and subsequently adding a weighted amount of nanopowder. All dispersions were prepared with a default surfactant concentration of 5 wt.% and a CuO NP concentration of 0.63 wt.% (5 g/l).299 The dispersions were subsequently ultrasonicated for 1 h to disrupt weakly linked agglomerates in the dispersed nanopowder using an ultrasonic bath operating at 40 kHz.271,299 The resulting mean agglomerate sizes in the freshly prepared dispersions, as determined by time-resolved dynamic light scattering (DLS), are 369 ± 77 nm (GetNanoMaterials) and 449 ± 85 nm (In- house).299

Electrophoretic deposition procedure

Electrophoretic deposition (EPD) of CuO scaffolds from the agglomerated CuO NP dispersions was conducted using a Keithley Sourcemeter 2400. Ti- and Au-coated glass substrates were used as a counter and working electrode, respectively. Both electrodes were immersed in the

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dispersion (immersed area of 7×7 mm2) and placed in parallel at a distance of 5 mm. EPD from the GNM dispersion was performed by applying a total of 24 deposition cycles, each consisting of a 30 s ramping step of the applied potential from 0 V to 75 V, followed by a 30 s deposition step at 75 V, ending with 60 s equilibration step at a potential of 1 V. EPD from the SG dispersions was performed accordingly at 1 mm electrode spacing by applying a total of 4 pulse cycles with an increased equilibration step to 120 s. After EPD deposition, the electrodes were slowly lifted out of the dispersion, soaked in CHCl3 to remove the surfactant, and finally rinsed with ethanol. The weight of the electrode was measured before and after the EPD deposition to estimate the amount of CuO deposited.

Electrochemical infiltration procedure

The electrochemical infiltration of the nanostructured CuO NP scaffolds with Al to form the Al/CuO nanocomposite thermite was performed using a potentiostat (Metrohm Autolab- PGSTAT204 with FRA32M EIS module, controlled by the Metrohm Nova 2.1.4 software). An

Al-containing ionic liquid (Iolitec, [BMIm]Cl*AlCl3, ratio 1:2) was used as electrolyte and as metallic ion source. The complete electrodeposition cell and setup was placed in a nitrogen- atmosphere glovebox to avoid degradation of the ionic liquid in presence of humidity. The Au- coated substrate with the deposited CuO film was employed as working electrode (cathode), while pure Al (99.9%) was used as a counter and pseudo-reference electrode (anode). The electrodes were placed in parallel at a distance of 5 mm. An area of 7×10 mm2 was immersed into the ionic liquid. During the infiltration, several processes occur simultaneously:345–347

- - - (1) Reaction at the cathode : 4 Al2Cl7 + 3 e → 7 AlCl4 + Al - - (2) Reaction at the anode : Al + 7 AlCl4 → 3 e + 4 Al2Cl7 - - (3) Degradation in the presence of humidity : 7 H2O + Al2Cl7 → 7 HCl + OH + 2 Al(OH)3

The infiltration process was performed galvanostatically to control the amount of reduced and deposited Al. The amount of electrochemically deposited metal can then be estimated by Faraday's Law:348

× = × (6.2.1) 𝑀𝑀 𝑄𝑄 𝑚𝑚 where m is the mass, M the molar mass and𝑧𝑧 z charge𝐹𝐹 number (= 3 for Al) of the deposited metal; Q is the measured electrical charge and F is Faraday's constant. Using the density ρ of the deposited metal and the deposition area A (= 7×7 mm2), a theoretical effective thickness

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d of the deposited film without the contribution of the nanoparticle scaffold can be calculated from:

× = (6.2.2) × × × 𝑀𝑀 𝑄𝑄 𝑑𝑑 𝑧𝑧 𝐹𝐹 𝐴𝐴 𝜌𝜌 Each electrochemical infiltration process was performed in pulsed mode consisting of multiple processing cycles. Each process cycle consisted of a repetition of deposition segments, followed by an extended resting time as equilibration period (the final optimized parameters for this process, as discussed in the Results and Discussion section, are reported in Table 6.1). During each deposition segment, a specific current was applied for a given duration to deposit Al from the electrolyte into the scaffold. Each of these deposition steps was followed by a short interruption step referred has off-time period where no deposition took place (i.e. - 0 mA, short equilibration period) allowing diffusion of Al2Cl7 in the scaffold pores: see Table 6.1. The choosen parameters (deposition and off times) are visualized and discussed in Fig. 6.3 of the Results and Discussion Part. Additionally, a 300 s break (equilibration period) was introduced after a given number of deposition cycles to allow the ionic liquid to equilibrate for an extended period (e.g. ion distribution, local Al-ion concentration and temperature). After completion of the infiltration process, the samples were immediately rinsed with toluene to remove residual ionic liquid and then with ethanol.

Table 6.1 Parameters for the electrochemical infiltration processes.

Type of Deposition Deposition Deposition Deposition experiment current time off-time cycles

Proof-of-concept -10 mA 3 s 37 s 2655

Nanothermite -7.5 mA 3 s 37 s 1827

Characterization of the nanocomposite

The composition of the Al/CuO nanocomposite was investigated by X-ray diffraction (XRD) using a PANanalytical X’Pert Pro Multi-Purpose X-ray diffractometer (MPD) and a Bruker D8 diffractometer operated in Bragg Brentano geometry. The XRD data were collected in the 2Θ- range of 10° - 100° with a step size of 0.026° using Cu-Kα1–2 radiation (λaverage= 0.15418 nm, 45 kV and 40 mA).

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The morphology and elemental composition of the nanocomposites were investigated using a Hitachi S-3700N scanning electron microscope (SEM), equipped with an energy-dispersive X- ray detector (EDX) (Ametek EDAX, Octane Pro). The thicknesses of the oxide scaffold deposits were determined using a profilometer (Bruker Dektak XT) with a stylus radius of 2 μm, a stylus force of 3 mg and a trace resolution of 0.833 μm/pt. Cross-sections of the deposited oxide scaffold layers and of the nanocomposite were prepared by breaking the samples and milling the fractured edge with an IM4000 Ion Milling System (Hitachi) using an Ar ion beam (6 kV accelerating voltage, 1.5 kV discharge and 0.09 cm3/h Ar gas flow).

A cross-section of the nanocomposite, as well as an electron-transparent cross-sectional lamella, were prepared by focused ion beam (FIB) milling using an FEI Helios Nanolab Dual Beam. Before ion milling, protective Pt layers were deposited on the coating surface by electron beam and ion beam, respectively. The lamella was analyzed with a scanning transmission electron microscope (STEM; JEOL JEM 2200 field emission transmission electron microscopy operated at 200 kV).

Differential scanning calorimetry (DSC) was conducted using a DSC 404 C Pegasus thermal analyzer and Al2O3 crucibles. The samples were heated from room temperature to 1150 °C at a rate of 10 K/min under Ar flow (40 ml/min). Data were corrected with a scan of an empty run measured under identical conditions. For data analysis and better representation, a numerical baseline fit was subtracted from the measured curves.

6.3 Results and discussion

In this study, a novel 2-step fabrication route was developed for producing highly energetic MMNC thermites, as depicted in the schematic in Fig. 6.1. In a first step, a nanoparticle scaffold is manufactured by electrophoretic deposition of individual nanoparticles aggregates onto a conductive substrate. Admittedly, various other techniques can be used to produce nanoporous scaffolds, including spin coating349, drop casting350 and doctor-blade casting351. However, as shown by a systematic EPD study from tuned CuO NP dispersions,344 EPD provides excellent control over the thickness, porosity and morphology of the nanoporous oxide scaffold, and hence also over the final MMNC microstructure. In particular, the thickness and porosity of the EPD oxide scaffold can be tuned through the size, shape and compactness of the NP aggregates and agglomerates in the NP dispersion, which in turn critically depend on the oxide nanopower characteristics: for details, it is referred to Ref.[344]. In a second step (see Fig. 6.1), the oxide scaffold produced by EPD is filled with a metal with a high oxygen

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affinity by electrochemical deposition from an ion-containing electrolyte. Notably, for the electrochemical deposition of less noble metals, e.g. Al, non-aqueous solvents such as ionic liquids must be chosen as electrolyte (see below). Other requirements for the selection of the electrolyte is excellent wettability of the scaffold surface and the chemical stability of the scaffold material in contact with the electrolyte during the electrochemical infiltration process. Excellent wetting with high adhesive forces is essential to enable full penetration by capillary effects of smallest channels in the nanoporous scaffold. Crucially, for production of a Al-based MMNC thermite, reduction of the oxidizer scaffold during cathodic electrochemical metal infiltration, as well as oxidation of the deposited Al metal fuel through a reaction with (i.e. a reduction of) the oxidizer scaffold (e.g CuO, WO3, Co3O4, Fe3O4) must be avoided at all cost, since it reduces the stored reaction enthalpy. In addition, the base electrode (substrate) of the oxidizer scaffold should be more conductive than the scaffold itself to promote a bottom-up filling of the scaffold with metal fuel and thus obtain a dense thermite MMNC coating.

Figure 6.1 Schematic representation of a new 2-step deposition route for producing highly energetic MMNC coatings. Step 1 involves deposition of nanoparticles onto a substrate, e.g. electrophoretic deposition of CuO nanoparticles as depicted here. In step 2, the nanostructured scaffold is electrochemically infiltrated with a metal to form the composite (here Al infiltration from an ionic liquid). The SEM micrographs show a

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deposited CuO nanoparticle scaffold (left), which is subsequently infiltrated with Al to obtain an Al/CuO thermite MMNC (right).

To demonstrate the proposed 2-step fabrication route for highly energetic MMNC Al/CuO thermites, nanostructured CuO scaffolds of different thicknesses were produced onto Ti- coated glass substrates by EPD from the GNM and SG CuO NP dispersions. To infiltrate the porous CuO scaffolds with Al, an organic halide with AlCl3 (BMImCl*AlCl3) was chosen as electrolyte. As verified by room-temperature wetting experiments in an inert atmosphere (see

Fig. 6.2), the wetting angle of the Al-containing ionic liquid ([BMIm]Cl*AlCl3) on CuO is smaller than 15°, which indicates nearly complete wetting. A pulsed deposition procedure (consisting of a deposition step and an "off-time") was applied to account for the sluggish ionic diffusion in - the viscous ionic liquid. Namely, cathodic deposition leads to a very fast depletion of Al2Cl7 ions in the infiltrated electrolyte (see Table 6.1 and Fig. 6.3). Consequently, an "off-time" is required after each deposition step to replenish the depleted diffusion layer at the scaffold surface before executing the next deposition step.

Figure 6.2 Wetting analysis of the Al-containing ionic liquid [BMIm]Cl*AlCl3 on a CuO surface conducted in a protective N2 atmosphere. The wetting angle is smaller than 15°, which indicates nearly complete wetting of the CuO surface by the Al-containing ionic liquid.

Optimization of the pulse sequences during the galvanostatic electrochemical infiltration step requires careful analysis of the measured potential evolution, as shown in Figs. 2a and 2b. For the electrolytic deposition of metals, the electrochemical overpotential must generally lie within

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the stability range of the solvent. The large negative standard potential of Al/Al3+ (E0 = - 1.66 V)352 does not allow efficient electrodeposition of Al from an aqueous solution due to strong cathodic hydrogen evolution. The here employed BMImCl*AlCl3 ionic liquid electrolyte avoids the problem of an additional cathodic reaction and shows excellent wetting behavior of the CuO scaffold (see Fig. 6.2). In addition, no significant chemical attack or reduction of the CuO scaffold by the ionic liquid itself was observed (as verified by detailed TEM investigations in the present study; see below), which implies that the thermodynamically preferred reduction of CuO by Al is kinetically obstructed during the room-temperature infiltration. Average overpotentials between -0.4 and -0.7 V were measured during the Al deposition steps, indicative for an efficient deposition rate (see Figs. 2a and 2b). As mentioned above, the Al anode is a pseudo-reference, because its potential is varying as function of the applied current. Consequently, the measured overpotentials during the successive deposition steps can only be quantitatively interpreted. Notably, for each successive deposition segment, the overpotential drops after approximately 3 s of cathodic polarization due to the very fast ion depletion of the infiltrated electrolyte during the activated cathode reaction. As concluded from a corresponding parameter study of the potential evolution as function of the deposition and off times (see below), an individual deposition step of no more than a few seconds (here: 3 s) is ideal to infiltrate the scaffold efficiently. Longer deposition steps induce very low overpotentials, which not only result in very slow deposition rates, but can also lead to other detrimental effects, like oxide scaffold reduction. During the extended off time (typically tenths - of seconds up to more than one minute; see below), the Al2Cl7 /Al redox equilibrium is slowly (re-)established (no current flowing through the pseudo-reference electrode). A theoretical equilibrium potential of 0 V should be attained once the entire inner surface of the porous CuO scaffold is covered with Al (i.e. for a completely and densely infiltrated scaffold). Instead, for partially filled oxide scaffolds, the measured potential steeply increases with time during the "off-time" period, reaching positive values (see Figs. 2a and 2b). This is expected because still uncovered CuO surfaces (and possibly small amounts of deposited Cu) in the infiltrated - scaffold have a higher electrochemical redox potential compared to the Al2Cl7 /Al surfaces. Indeed, with increasing number of deposition cycles, the established equilibrium potential at the end of the off time step slowly approaches to 0 V, indicative for a gradual filling of the oxide scaffold (see Fig. 6.3c). As reflected in Figs. 2a and 2b, the measured overpotential during successive deposition steps stabilizes at -0.7 V, which indicates that an "off-time" step of 37 s - (for a constant deposition time step of 3 s) is sufficient for Al2Cl7 ions to diffuse into the scaffold pores.

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Figure 6.3 Potential evolution during aluminum electrodeposition in the GNM porous CuO scaffold.

For a first proof of principle of the proposed 2-step synthesis method (Fig. 6.1), a nanostructured CuO scaffold with a thickness of 35 μm was produced by EPD from a dispersion of GNM CuO NPs onto Ti-coated glass. The CuO nanopowder has a larger mean primary NP size with a considerably broader size distribution than the SG nanopowder. Consequently, the GNM scaffold has a slightly higher porosity (see Figure 3 in Ref. [344]) and was therefore selected for our feasibility study. The pulsed Al infiltration process of the GNM CuO scaffold was repeated for a total 2655 cycles, yielding a nominally 40 μm thick Al-layer (as calculated according to Faraday's law), which resulted in a slight overinfiltration of the CuO scaffold coating (i.e. the oxide scaffold is covered with a thin Al overlayer).

A cross-section of the produced Al/CuO MMNC coating is shown in Figs. 3a and b. The light grey areas in the SEM images correspond to the CuO scaffold, whereas the dark areas constitute the Al-filling. The magnified SEM image in Fig. 6.4b illustrates that the porous CuO scaffold was homogeneously infiltrated by Al and even filled smallest nanoporous channels of the scaffold (for an image of the CuO scaffold before infiltration, see Refs. [299,344]). Only few tiny pores (in black) remain, which indicates that slight optimizations of the scaffold structure and/or the electrochemical infiltration step are still necessary to achieve a fully dense structure. The larger cracks in the MMNC coating are artefacts from the sample-preparation step, i.e. from breaking of the sample. EDX line-scan analysis was performed to reveal the elemental distributions in the MMNC coating (see Figs. 3a, 3c and 3d). The ratio of the CuL-peaks and the AlK-peaks in the (averaged) EDX scans of regions 1 to 3 are very similar (see Fig. 6.4a), which suggests that the CuO scaffold was homogenously infiltrated by Al. Only adjacent to the coating surface, a large increase of the Al fraction was observed (see area 4 in Fig. 6.4a), as attributed to the Al overfiltration (see above). Notably, the O elemental distribution from the

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EDX analysis can hardly be interpreted due to the inevitable formation of a native oxide on the air-exposed Al matrix phase (i.e. the entire cross-sectional surface contains oxygen). The recorded EDX maps of Cu and Al (Fig. 6.4d) show a homogenous central layer containing Cu, O and Al without substantial lateral variations of their signal intensities (Fig. 6.4d). Notably, only traces of C were detected by EDX, which suggests that the contamination of the MMNC with hydrocarbons from the electrophoretic and infiltration steps is negligible.

Figure 6.4 Microstructure and elemental composition of an Al/CuO thermite MMNC coating, as prepared with the proposed 2-step synthesis route. (a,b) Secondary electron micrograph of the cross-section of the MMNC coating. Areas analyzed by EDX scanning

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(c) and mapping (d) are marked in orange and blue, respectively. (c) Compositional analysis of different sections (area 1-4, marked in orange) of the MMNC cross-section, arranged from top to bottom (electrode) by EDX mapping. d) EDX mapping of area Nr. 5 (marked in blue) of the MMNC cross-section. (e) XRD analysis of the MMNC coating in the range of 30°-55°2ϴ.

XRD analysis of the MMNC coating revealed CuO243 and Al353 diffractions, as well as a significant metallic Cu354 contribution. As evidenced in Fig. 6.3a, the off-time potential during electrochemical infiltration of this composite was very positive suggesting the continuous presence of some Cu compounds on the scaffold surface. The ionic liquid used for the proof of principle was reused simulating an industrial processes and the presence of dissolved Cu from a previous deposition is expected. Additionally, small scaffold dissolution during the off- time cannot be excluded. Moreover, a weak but broad Cu2O signal was observed which indicates the formation of a nanocrystalline Cu2O phase either by a slight reduction of the CuO scaffold during infiltration and/or by air oxidation of the aforementioned Cu surface layer. Notably, no Al-oxide phases were detected by XRD (also no indication for the formation of an amorphous oxide, which typically appears as a broad intensity hump in the diffractogram), indicating that virtually only metallic Al was deposited upon infiltration.

Figure 6.5 HR-TEM analysis of a cross-sectional TEM lamella of the Al/CuO MMNC (identical to the sample as analyzed by SEM/EDX, XRD and HR-TEM in Figs. 3 and 5). (a) transmission electron micrograph with indicated STEM-BF linescan of (b) CuK (green), AlK (red) and OK (black); using a 20 points moving average filter for better

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visibility. (c,d) BF image and corresponding SAED with identified diffraction spots. The observed spots can be identified as CuO in (111)-orientation, with a second set of spots caused by double diffraction. The additional spots are caused by other overlapping phases in Fig. 6.5d.

A TEM lamella was prepared by FIB to analyze the microstructure and composition of the MMNC down to the nanoscale (Figs. 4 and 5). The investigation by TEM revealed a nanoscaled mixture of CuO-particles and Al (Fig. 6.5a). The transition between regions of varying contrast was investigated STEM-BF (line in Fig. 6.5a). In this regard, it is emphasized that the Al/CuO interfaces in the MMC are bended and the TEM lamellae will contain overlapping CuO- and Al-phases along the beam direction (since the thickness of the TEM lamella is larger than the primary CuO NP size). Nevertheless, while scanning along the selected Al/CuO interface, the Cu signal increases, while the Al intensity decreases (Fig. 6.5b). This indicates that the darker areas correspond to individual NPs of the CuO scaffold, while the brighter regions are rich in Al. The TEM analysis thus clearly evidences that even tiniest pores of the nanostructured CuO scaffold were infiltrated with Al, underlining that the ionic liquid could penetrate the entire CuO scaffold. Notably, as for the SEM cross-sectional analysis, the Al matrix phase exposed at opposite surfaces of the cross-sectional TEM lamellae will be air-oxidized, which hinders a quantitative interpretation of the O linescan profile in Fig. 6.5b. Nevertheless, a small increase of the oxygen signal can be observed when the

CuK-signal becomes stronger than the AlK-signal. This stems from the additional contribution of CuO phases (superimposed on the O signal from the oxidized Al surface). An individual CuO nanoparticle within the MMNC was analyzed using SAED: see Fig. 6.5c. The SAED diffraction pattern could be uniquely identified as CuO, confirming the chemical stability of the nanostructured CuO layer during the infiltration process (Fig. 6.5d). Fig. 6.6 shows a HR-TEM micrograph of the nanocomposite at high magnification. Lattice distances measured over several lattice fringes indicated the coexistence of CuO and Al metal in immediate contact (Fig. 6.6a). Correspondingly, the fast Fourier transformation (FFT) shown in Fig. 6.6b indicates the presence of CuO ((20-2), blue), as well as Al ((200), red; additional spots arise from other CuO particles and Al grains.

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Figure 6.6 HR-TEM analysis of a cross-sectional TEM lamella of the Al/CuO MMNC (same sample as analyzed in Figs. 3 and 4). (a) HR-TEM micrograph. The indicated lattice distances correspond well to CuO (20-2) (red) and Al (200) (blue) (b) FFT of (a) with the corresponding diffraction spots of the specified Al and CuO planes.

In conclusion, it could be demonstrated that the combination of electrophoretic deposition and electrochemical infiltration with "high deposition" current is an excellent tool to produce MMNCs with pristine matrix-particle interfaces, even when depositing metals with a high oxygen affinity, like Al. By proper selection of the electrolyte composition, deposition current and times and infiltration parameters, dense MNNCs suitable for thermite applications can be produced.

In the following section, the influence of different electrochemical parameters (e.g. current, durations of the deposition and off-time steps, as well as number of deposition cycles) on the produced Al/CuO MMNC microstructure was investigated for a GNM CuO scaffold microstructure. When infiltrating the CuO scaffold with a low current (-2.5 mA) and a deposition time step of 72 s (for a total 100 deposition cycles), planar SEM analysis showed a very rough, cauliflower-like surface structure with a homogeneous distribution of large voids, resembling porous channels. Such a structure is typical for ionic depletion in the valleys and preferential growth on the protruding structures. Corresponding cross-sectional SEM analysis revealed that, although the CuO scaffold is densely infiltrated at most locations, some very big channel- like voids remain, resulting in a dense pillar-like MMNC microstructure. An increase of the deposition current to -5 mA (while reducing the number of cycles to 50 to deposit a similar quantity of Al) resulted in a much smoother surface as shown in Fig. 6.7b. Corresponding cross-sectional SEM analysis indicated that, although the formation of a pillar-like

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microstructure could be minimized (probably because of the higher initial deposition rate in the pores), the densely infiltrated scaffold still contained many trapped voids. These findings indicates that an increased deposition current allows a more homogenous infiltration of the CuO scaffold during the initial stage of the infiltration process, but results in the accumulation of voids during the course of the infiltration. Apparently, the duration of the time-off step (72 s) between successive long deposition time steps of 72 s is too short to allow sufficient diffusion and equilibration of the Al ion concentration throughout the infiltrated scaffold, resulting in local Al ion depletion regions and associated formation of localized voids. The density of trapped voids becomes more and more pronounced with increasing number of deposition cycles, which indicates that the depletion gradients in the Al ion concentration become more and more pronounced during the course of the infiltration process. In addition, each successive deposition step will impose a mechanical strain on the nanoporous CuO scaffold, which may lead to local fracturing and an accompanied instantaneous depletion of electrolyte in the fractured region. For a given constant deposition current (i.e. -5 mA), the depletion of Al ions in the infiltrated scaffold can be effectively decreased by shortening the deposition time step, while decreasing the ratio between the deposition time step and the off-time step (as accompanied by a decrease of the net electric charge QP transferred during a single deposition step). To deposit the same quantity of Al during the entire electrochemical infiltration process, the number of deposition cycles has to be increased. Accordingly, to achieve a more gentle infiltration with a more homogenous Al-ion concentration profile across the CuO scaffold, the duration of the deposition pulse was reduced, while increasing the off time step between successive deposition steps (keeping the default duration of 144 s for a single pulse and applying a constant deposition current of -5 mA). Indeed, the density of trapped voids after 100 cycles could be drastically reduced, although pillar-like structures (similar to those formed at -2.5 mA) could still be observed in Fig. 6.7c.

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Figure 6.7 Influences of infiltration parameters on the microstructure of the resulting MMNC coating (IB = deposition current; tB = deposition step duration; IR = interruption current; tR = off time; QP = electric charge transferred during a single deposition pulse). (a-c) Influence of the deposition current and duration at high pulse charges. (d-f) Optimization of pulse parameters to produce dense nanocomposites using lower pulse charges. Note that the current values apply to nominal values, because it is impossible to define current densities when depositing in porous structures with undefined effective surfaces.

Based on the aforementioned parameter study, the infiltration process was further optimized by decreasing the charge transfer per pulse to QP = 30 C and the deposition time/off-time ratio. This was achieved in different ways by varying the following parameters: (i) reducing the deposition current (IB), (ii) decreasing the deposition time (tB), and/or (iii) increasing the duration of the off-time step (tR): see Fig. 6.7d. As such, a very gentle and homogeneous infiltration was realized with a minimized local depletion of Al ions in the infiltrated electrolyte during successive deposition segments and a suppression of pillar formation due to

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overgrowth on protruding areas of the scaffold. The compactness and homogeneity of the nanocomposite could thus be greatly improved. In particular, shorter deposition times with longer off-time durations allow a better equilibration of the Al ion concentration throughout the infiltrated scaffold. By shortening the deposition time to tB = 3s, increasing the off-time to tR =

37 s and increasing the deposition current to IB = -10 mA, an almost fully dense nanocomposite could be fabricated (Fig. 6.7e). Importantly, the overpotential during the deposition step must remain low enough to prevent the electrochemical reduction of CuO and the degradation of the electrolyte. Therefore, alternatively, a dynamic pulse sequence was applied during the deposition step, applying a high current of -10 mA at the start of the deposition step, which was linearly decreased to 0 mA over a 6 s period. This deposition sequence resulted in an even denser nanocomposite than the one obtained by infiltration with a constant deposition current of -10 mA (Fig. 6.7f).

To increase the energy density of the thermite MMNC, the infiltrated Al/CuO scaffold should not only be as compact as possible. In addition, the molar ratio of the oxidizer (CuO) and fuel (Al) should be close to the ideal stoichiometry ratio of 2/3 (see Equation 1). In practice, a certain excess of the fuel is often required to compensate for oxidation effects.124 The actual reaction enthalpy stored in the produced Al/CuO MMNCs was investigated by DSC. To this end, a ~35 μm thick CuO scaffold (produced from the SG nanopowder dispersion) was fabricated and subsequently infiltrated with Al by a pulsed sequence (Table 6.1). To determine a rough estimate of the Al/CuO molar ratio of the thus-produced MMC thermite coating, the initial porosity of the CuO scaffold was estimated from cross-sectional SEM analysis.344 The corresponding estimated scaffold porosity of 22.7% corresponds to an Al/CuO molar ratio of roughly 0.36 (i.e. a fuel-poor thermite), which is approximately 50% lower than the theoretical stoichiometric ratio of 2/3.

The reactivity of the produced Al/CuO thermite coating, as investigated by DSC, is shown in Fig. 6.8. Indeed, an exothermal thermite reaction (according to Equation 1) was observed when the temperature reached ca. 585 °C, which is somewhat lower than the melting point of Al metal at 660 °C (as associated with a strong endothermal signal). The corresponding reaction enthalpy of this fuel-poor thermite is as high as 1.081 kJ/g and thus of the same order as the theoretical reaction enthalpy of 4.077 kJ/g for the stoichiometric thermite composition.116 Notably, much smaller endothermic signals were observed at 540 °C and

585 °C, which can be attributed to the melting of Al/Al2Cu and ϴ-AlCu (in accordance with the Al-Cu phase diagram and indicative of the presence of minor amounts of Al-Cu intermetallics in addition to metallic Al). These endothermic reactions, as well as the possible presence of excess Al metal on the coating surface, will cause a decrease of the effective thermite reaction

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enthalpy. Further heating produces a strong endothermic signal at 1066 °C, corresponding to melting of the metallic (Cu)-phase produced by the thermite reaction.

Figure 6.8 DSC of Al/CuO nanocomposite with an Al/CuO molarity ratio of 1.6 (exothermal values are negative).

While the theoretical reaction enthalpy for an ideal Al/CuO thermite was not reached yet, the DSC analysis proves that highly energetic Al/CuO thermites can be obtained using the proposed 2-step synthesis route. Admittedly, there is still some room for improvement, which will be a main research task in the near future. As a first step, the porosity of the CuO scaffold will be further tuned to achieve an optimum Al/CuO stoichiometric ratio, probably slightly higher than 2/3, as well as an improved permeability (i.e. a better interconnectivity of the porosity). Subsequently, the infiltration process by electrochemical deposition will be even further optimized to enhance the homogeneity of the Al infiltration.

6.4 Conclusion

It could be demonstrated that the combination of electrophoretic CuO scaffold deposition and infiltration by electrochemical deposition is an excellent tool to produce energetic MMNCs with pristine matrix-particle interfaces, even when depositing metals with a high oxygen affinity, like Al. In a first step, a nanoporous oxide scaffold with tunable porosity is produced by electrophoretic deposition from a concentrated oxide nanoparticle dispersion. Next, this

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nanoporous oxide scaffold is densely infiltrated by a reactive metal, like Al, through electrochemical deposition from an ionic liquid. By proper selection of the electrolyte composition and electrochemical infiltration parameters, dense MNNCs suitable for e.g. nanothermite applications can be produced. The novel 2-step synthesis route enables control of the reactivity of energetic MMNC systems by tuning the porosity of the nanoporous scaffold during the electrophoretic step. To show the capabilities of the proposed synthesis route, a dense Al/CuO thermite nanocomposite with pristine metal/oxide interface was fabricated. No

AlOx oxide barrier was observed, proving the high quality of this new method. As such, a highly reactive Al/CuO nanocomposite with a reaction enthalpy of -1.081 kJ/g could be fabricated. The electrochemical deposition parameters used for infiltration are critical to obtain a dense MMNC. To the best of our knowledge, the two-step deposition of highly energetic MMNCs by electrophoretic deposition of a nanostructured oxidizer scaffold, followed by electrodeposition of the metal fuel from an ionic liquid, has not yet been reported, but provides significant benefits as compared to alternative fabrication methods, in particular:

(i) The production of pristine interfaces between the reactant phases (ii) Ambient temperature deposition with negligible diffusion and reaction between the constituent phases, ensuring maximum chemical energy storage (iii) A tunable energy density of the produced MMNC by varying the porosity of the oxide scaffold (iv) The possibility for patterned deposition of MMNC structures.

Reproduced with modifications from:

Dörner, L., Rheingans, B., Lin, L., Schmutz, P., Kovalenko, M. V., Jeurgens, L. P.H., Advanced manufacturing of energetic metal-matrix Al/CuO thermites nanocomposites with pristine interfaces by CuO electrophoretic deposition and Al electrodeposition infiltration. In preparation.

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Chapter 7. Conclusions and Outlook

7.1 Conclusions

This thesis describes the individual steps of a novel production procedure for Al based metal matrix nanocomposites in four Chapters. First, chapter 3 focuses on the tailoring of a sol-gel CuO synthesis yielding NPs with different sizes depending on the synthesis parameters. Chapter 4 & 5 highlight the parameters for tailoring CuO NP dispersions to obtain micrometer thick open-porous layers by EPD. Finally, a highly energetic Al/CuO thermite coating was fabricated (Chapter 6). A summary of the results is given below:

(1) CuO NP aggregates can be synthesized by a sol-gel process using aqueous Cu(OAc)2 and NH4(CO3)2 solutions as starting materials via an amorphous malachite-like precursor phase. The thermal decomposition of the precursor phase into CuO NP was initiated at 250°C. The resulting nanopowder was comprised of CuO nanoparticle-aggregates constituted of smaller crystallites. The shape and size of the primary crystallites can be tuned by pH and degree of supersaturation of the starting solutions yielding smallest coherent scattering domains of roughly 17 nm - 28nm. The density of the NP clusters, or nanoporosity, can also be tailored to enhance the specific surface area. To change the pH, the volume of added ammonia carbonate solution was adjusted and thereby the ratio of the educts. Even though a carbonate-rich system resulted in larger NP building blocks (TEM: 38 ± 8 nm) compared to a carbonate deficient system (TEM: 23 ± 6 nm) their specific surface area was increased by 20%.

(2) Tuning of CuO NP dispersions enables efficient EPD of micrometer-thick nanostructured CuO scaffolds. Diluted to concentrated (50 to 5000 mg/L) dispersions using different primary alcohols and additives were investigated for their suitability for EPD processes. CuO NPs in ethanol have the highest mobilities of -0.513 ± 0.031 μm·cm·V-1·s-1, which is beneficial for EDP. As dispersions in ethanol were unstable, the influence of various surfactants, such as AcAc, SDS and different polymers, on conductivity, particle mobility and aggregation behavior was tested. Addition of SDS or AcAc resulted in reversal of the surface charge of the particles to positive values, which is due to adhesion of Na+ ions on the oxide surface by SDS. For AcAc, an increase in acidity of the dispersion gives rise to the positive surface charge, which is counteracted by non-adsorbed surfactant ions at higher AcAc concentrations (>0.25 wt.%). While EDP without surfactant, with SDS or PEG 1450 only yielded a partial coverage of the electrode, a 20-30 μm thick homogeneous CuO NP film was fabricated using ethanol with 0.5 wt.% AcAc as a solvent.

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(3) Properties of CuO nanopowders such as crystallite/aggregate size and specific surface area as well as dispersion characteristics govern the growth, thickness and porosity of CuO nanolayers deposited by EPD. Six different CuO nanopowder with varying particle/aggregate morphology and size were compared regarding their potential as particle sources for EPD procedures.

At narrow electrode spacing of 1 mm larger initial particles yield thicker layers. Dense films can be produced with fine grained nanopowders, while coarser particle sources give rise to layers with large pores. When a larger distance of 5 mm between the electrodes is chosen, particle mobility also influences the layer formation. Particle size, accessible particle surface, surface charge and particle concentration are crucial parameters shaping the agglomeration behavior and hence the effective mobility in the electric field. Changing the mentioned parameters and deposition geometry allows tuning of the porosity of the deposited CuO layers.

(4) A novel procedure enables the localized and cost-effective production of highly energetic Al/CuO thermite coatings at room temperature. To this end, previous results were adopted to facilitate the fabrication of a nanostructured CuO film by EPD, however other procedures to generate a nanostructured layer can also be used as long as the substrate of is conductive. This nanoporous scaffold is then infiltrated with Al from an ionic liquid by electrochemical deposition. Tuning of infiltration parameters like deposition current, speed and pulse cycles revealed that short high-current pulses with long restoration duration are the most successful to achieve fully dense composites. Compact Al/CuO thermite nanocomposites can be produced with the presented method as excellent wetting of the ionic liquid on CuO allows infiltration of small nanopores. Illustrating the high quality of this method, the fabricated nanocomposites exhibit a pristine Al/CuO interface. No inhibiting AlOx layer is formed during the production. A reactive nanocomposite with an Al/CuO ratio of 1.6 was prepared with this method which upon reacting at 585 °C showed a heat release of ~1 kJ/g.

7.2 Outlook

With the continuous design and development of new nanomaterials for domestic and industrial applications the challenges for scientists to provide guidelines for adequate handling and processing of these nanomaterials increase. Especially the use of dry nanopowders presents a big safety concern for workers and the environment, due to their high reactivity and ability to pass through cell membranes355. In this thesis (chapter 3) a synthesis routine to fabricate porous CuO NP aggregates with high specific surface area is presented. If individual

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nanoparticles are linked by aggregation, they are less prone to become airborne as weight and size are increased, making them safer to handle. Yet they retain the characteristics of a high surface area due to the open aggregate structure. Manufacturers and distributors have already established their portfolio on nanosized CuO powders, but there is still a market for nanopowders with monodispersed particle sizes >50 nm. Such nanopowders with larger particles allow additional tuning of nanocomposite fabrication processes.

Current methods for the production of Al-based metal nanocomposites rely on reinforcing NPs dispersed in Al melt or on physical mixing of NPs with Al particles. Both processes are energy- intensive, costly and introduce impurities. The here developed novel procedure (chapter 6) to fabricate Al-MMNCs overcomes these challenges as it yields pristine Al/NP interfaces avoiding the formation of internal AlOx layers and allows synthesis at low temperatures. While the method is still in its infancy, the produced Al/CuO thermite already released ~25% of the theoretical maximum energy. Further tuning of the reactant ratios as well as the density of the composite should allow an increase in energy release. Moreover, additional processing steps such as pressing the composite into pellets or low temperature sintering could be envisioned to enhance the proximity of the Al/CuO grains which would be beneficial for the SHS reaction.

Another option to tailor the reactivity is exchanging the oxidizer from CuO to Cu2O, which is less exothermic, or using CuO@Cu core-shell particles to dilute the reactive components of the composite.

Low cost and high-quality production of Al/CuO nanocomposites are a big step towards solder- free nanojoining processes, as the reaction yields molten copper. In addition, this reaction system can release potentially up to three times more energy than currently available Ni/Al NMLs. To further develop Al/CuO nanofoils for joining application, the fabrication process needs to be upscaled. The production of homogenous composite layers will be more challenging when the electrode size is increased. This could be addressed either by performing multiple depositions in parallel or by ensuring a homogenous electrolyte flow when a larger electrode is employed.

For other applications, e.g. in the field of propellants and defense technologies, a variety of other oxidizers (i.e. MoO3, WO3) can be used to build the initial nanostructured scaffold. For Al-MMNCs that require a low loading of reinforcement materials an electrochemical co- deposition process can be constructive. Here, the NP would be dispersed in the Al containing electrolyte, similar to co-depositions demonstrated for Ni-MMNCs.342

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Appendix A: Abbreviation list

AcAc acetylacetone AFM atomic force microscope ARM arrested reactive milling ATR-FTIR attenuated total reflection Fourier transform infrared spectroscopy BET Brunauer, Emmett and Teller analysis CMNC ceramic matrix nanocomposite CNT carbon nanotube D-S Debye Scherrer equation DLS dynamic light scattering DLVO theory of Derjaguin, Landau, Verwey and Overbeek DSC differential scanning calometry EDX energy dispersive X-ray spectroscopy EPD electrophoretic deposition EtOH ethanol FIB focused ion beam HRTEM high-resolution transmission electron microscope MMC metal matrix composite MMNC metal matrix nanocomposite MOSFET metal-oxide-semiconductor field-effect transistor MPD multi-purpose X-ray diffractometer NML nanomultilayered system NP nanoparticle PEG polyethyleneglycol PMNC polymer matrix nanocomposite PVD physical vapor deposition PVP polyvinylpyrrolidone RT room temperature SDS sodium dodecyl sulfate SEM scanning electron microscope SHS self-propagating high-temperature synthesis SLS static light scattering SSA specific surface area STM scanning tunneling microscope TEM transmission electron microscopy TGA thermal gravimetric analysis W-H Williamson-Hall formula XRD X-ray powder diffraction

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Appendix B: Curriculum Vitae

Lars Dörner (né Bulthaupt)

Date of birth: December 11th, 1990 Place of birth: Kiel, Germany Nationality: German

Education 5/2016 - 8/2020 Doctoral studies (PhD) in Chemistry under the supervision of L. Jeurgens and Maksym Kovalenko

ETH Zurich, Institute of Inorganic Chemistry, Switzerland and EMPA Dübendorf, Federal Laboratories for Materials Science and Technology

“Highly energetic Al/CuO thermite coatings through nanoparticle composites”

9/2013 - 9/2015 Master of Science in Chemistry University of Munich (LMU), Munich, Germany Master thesis: “Synthesis, structural characterization and magnetic properties of CsMn2P2 – and BaMn2P2 – substitution variants"

9/2010 - 9/2013 Bachelor of Science in Chemistry and Biochemistry University of Munich (LMU), Munich, Germany Bachelor thesis: “Studies on the synthesis of Ca- and Sr-containing nitridogallates.”

6/2010 Abitur Augustinerschule, Gymnasium, Friedberg, Germany

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Appendix C: List of publications

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Appendix D: List of presentations

Oral presentation

EMRS Springmeeting 2018, Strasbourg (France), "Controlled synthesis and dispersion stability of submicron-sized CuO nanoparticle aggregates"

International Conference on Nanojoining and Microjoining 2018, Nara (Japan), "Highly- energetic Al/CuO thermites through nanoparticle composites for reactive joining applications"

Poster presentation

Swiss NanoConvention 2018, Zürich (Switzerland), "Highly-energetic Al/CuO thermites through nanoparticle composites for reactive joining applications"

EMRS Springmeeting 2019, Nice (France), "Porous CuO films as produced by electrophoretic deposition from tailored CuO nanoparticle dispersions"

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