A Dissertation
entitled
Application of Mass Spectrometry to the Characterization of Core and Ligand Shell
Modifications of Silver Molecular Nanoparticles
by
Aydar Atnagulov
Submitted to the Graduate Faculty as partial fulfillment of the requirements for the
Doctor of Philosophy Degree in
Chemistry
______Dr. Terry P. Bigioni, Committee Chair
______Dr. Cora Lind-Kovacs, Committee Member
______Dr. Dragan Isailovic, Committee Member
______Dr. Nikolas Podraza, Committee Member
______Dr. Amanda Bryant-Friedrich, Dean College of Graduate Studies
The University of Toledo
August 2017
An Abstract of
Application of Mass Spectrometry to the Characterization of Core and Ligand Shell Modifications of Silver Molecular Nanoparticles
by
Aydar Atnagulov
Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Chemistry
The University of Toledo
August 2017
Small silver nanoparticles, also called molecular nanoparticles (MNPs) or nanoclusters, are of great research interest due to potential applications in valuable fields such as biomedicine and catalysis. In the past decade, several groups reported successful formulae determination and crystal structures of the various species in this class of materials. Knowing such information is of crucial importance to start testing how slight modifications of both metal core and ligand shell affect the stability and properties of molecular nanoparticles.
Among the techniques employed for characterization of MNPs, mass spectrometry plays a vital role. Soft ionization techniques such as matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI), developed primarily for bioanalytical applications, became indispensable for the analysis of MNPs, most of which are labile during the ionization process. Mass spectrometry also provides the high precision required to measure the precise numbers of metal atoms, ligands and charges and thereby determine the formulae of these molecules. While modified samples often resemble a statistical distribution of a product mixture, individual products can be iii
successfully discriminated by their mass using tandem mass spectrometry and singled out
such that their behavior in the gas phase can be studied.
The all-silver M4Ag44(p-MBA)30 cluster was used as a model system, where M is
a monocationic counterion and p-MBA is para-mercaptobenzoic acid, which serves as a
protecting ligand. Metal core modifications were carried out by substituting gold for
silver to form M4AuxAg44-x(p-MBA)30 clusters. Gold was chosen as a second metal due to
some of its properties being similar to those of silver, including its electronic structure
and atomic size. Co-reduction and galvanic exchange were the two methods used for the
preparation of the bimetallic product. The range of product composition was determined,
and the most thermodynamically favorable sites of heteroatoms within the nanoparticle
structure were established. Moreover, chemical properties such as stability, reactivity,
and fragmentation were studied as a function of product composition. Thermodynamic
and kinetic barriers were evaluated for the aforementioned reactions.
The role of ligands in nanoparticle stability and structural outcome of the synthesis was investigated using the same model system, M4Ag44(p-MBA)30. Several
parameters including the length of an aliphatic chain between a sulfur atom and a phenyl
ring, introduction of bulky groups, and aromaticity, were varied aiming to find the
characteristics required for synthesis of M4Ag44(SR)30 (SR = thiolate). It has been found
that ligands can be divided into two categories that produce orthogonal sets of
nanoparticles. Such a division is based on the aliphatic or aromatic character of the
carbon atom directly bonded to the sulfur atom of the thiol group. The outcomes obtained by the method of direct synthesis have been confirmed by using a ligand exchange, which is a softer modification technique. The limits of miscibility of ligands belonging to two
iv
different classes were tested on M4Ag44(SR)30 nanoparticle using p-MBA and
glutathione.
Mass spectrometry provides means to control the purity of the synthetic product
and to identify potentially interesting by-products. When M4Ag44(SR)30 was synthesized
using para-tert-butylbenzenethiol (TBBT), another MNP, with the molecular formula of
M3Ag17(TBBT)12, was identified in the product. The synthesis was further optimized to yield primarily M3Ag17(TBBT)12. The small size of the nanoparticle, structural analysis of other silver and gold MNPs, and use of computational chemistry allowed for the rational prediction of the structure of this nanoparticle. The structure prediction was supported using heteroatom substitution as a structural probe. The inorganic part of the predicted structure was later found to be identical to that of the experimentally determined structure.
v
Acknowledgements
First and foremost, I would like to express gratitude to my advisor, Dr. Terry
Bigioni for his guidance during my graduate studies and helping to develop the essential
skills of a good scientist. Second, special thanks go to both Dr. Wendell Griffith and Dr.
Jingshu Guo for the countless hours of mass spectrometry training that made this work
possible. Third, I would like to acknowledge my labmates Dr. Brian Conn, Badri
Bhattarai, and Sameera Wickramasinghe for fruitful collaborations and their contributions to this work. Dr. Brian Conn and Badri Bhattarai contributed to co- reduction and galvanic exchange studies described in chapter 2, respectively. Syntheses described in chapters 3 and 4 were performed by Sameera Wickramasinghe.
Next, I would like to thank Dr. Uzi Landman and his group for supporting our work with molecular modeling and calculations. My sincere thanks go to both Dr. Dragan
Isailovic and Dr. Xiche Hu for classes on mass spectrometry and computational chemistry, respectively. I would also like to thank Dr. Cora Lind-Kovacs and Dr. Nikolas
Podraza for taking their time to be part of the dissertation committee. Last, but not the least, I would like to acknowledge the Department of Chemistry and Biochemistry of the
University of Toledo for giving me the opportunity to pursue my doctoral degree here and National Science Foundation for financial support of the research.
vi
Table of Contents
Abstract ...... iii
Acknowledgements ...... vi
Table of Contents ...... vii
List of Figures ...... xi
List of Abbreviations ...... xiv
List of Symbols ...... xvi
1 Introduction ...... 1
1.1 History of Nanoparticles ...... 1
1.2 Development of Precious Metal Molecular Nanoparticles Field ...... 3
1.3 Electronic and Geometric Shell Closing Rules...... 7
1.4 Mass Spectrometry in Molecular Nanoparticles Research...... 10
1.5 Dissertation Overview...... 12
2 Molecular Metallurgy of M4AuxAg44-x(SR)30 Bimetallic Nanoparticles ...... 14
2.1 Introduction ...... 14
2.2 Experimental ...... 16
2.2.1 Chemicals ...... 16
2.2.2 Synthesis of M4AuxAg44-x(p-MBA)30 by Co-reduction ...... 17
2.2.3 Synthesis of M4AuxAg44-x(p-MBA)30 by Galvanic Exchange ...... 17
2.2.4 Thermal processing ...... 19 vii
2.2.5 Optical measurements ...... 19
2.2.6 Electrospray Ionization Mass Spectrometry (ESI-MS) ...... 20
2.2.7 Crystallization ...... 21
2.2.8 Single-Crystal X-Ray Diffraction and Analysis of
M4Au12Ag32(p-MBA)30 ...... 21
2.3 Results and Discussion...... 23
2.3.1 Synthesis ...... 23
2.3.2 Thermal stability ...... 27
2.3.3 Location of Au heteroatoms ...... 30
2.3.4 Thermodynamics of galvanic exchange ...... 33
2.3.5 Kinetics of gas-phase fragmentation ...... 43
2.3.6 Optical properties ...... 46
2.4 Conclusion...... 48
3 M3Ag17(TBBT)12 Nanoparticles and Their Structure Prediction ...... 50
3.1 Introduction ...... 50
3.2 Experimental ...... 51
3.2.1 Chemicals ...... 51
3.2.2 Synthesis of M3Ag17(SR)12 and M3AuAg16(SR)12 ...... 51
3.2.3 Characterization ...... 52
3.2.4 Theoretical Methodology ...... 53
3.3 Results and Discussion...... 54
3.3.1 Synthesis and gas-phase stability of Ag:TBBT NPs...... 54
3.3.2 Synthesis optimization ...... 58
viii
3.3.3 Structure prediction ...... 60
3.3.4 DFT analysis of the predicted structure ...... 64
3.3.5 Heteroatom substitution ...... 66
3.3.6 Confirmation of the predicted structure ...... 68
3.4 Conclusion...... 70
4 Ligands as Structure Directing Synthons ...... 71
4.1 Introduction ...... 71
4.2 Experimental ...... 73
4.2.1 Chemicals ...... 73
4.2.2 Syntheses of Ag:p-MBA and Ag:p-MMBA nanoparticles ...... 73
4.2.3 Syntheses of Ag nanoparticles with BT, TBBT, CHT, BM,
TBBM, and PET ...... 74
4.2.4 Synthesis of Ag:SG nanoparticles ...... 75
4.2.5 Ligand exchange on M4Ag44(p-MBA)30 using GSH ...... 75
4.2.6 Ligand exchange on Ag:SG NPs using p-MBA ...... 75
4.2.7 Partial ligand exchange on M4Ag44(p-MBA)30 using GSH ...... 76
4.2.8 Characterization ...... 76
4.3 Results and Discussion...... 77
4.3.1 Transformation of M4Ag44(p-MBA)30 via ligand exchange ...... 77
4.3.2 Effect of ligand structure on the product of synthesis ...... 79
4.3.3 Conversion of Ag:SG NPs into M4Ag44(p-MBA)30 via ligand
exchange ...... 88
4.3.4 Partial ligand exchange on M4Ag44(p-MBA)30 using GSH ...... 90
ix
4.4 Conclusion...... 95
5 Conclusions ...... 96
References ...... 101
x
List of Figures
1-1 Plot of the chemical compositions of Au:SG nanoclusters against the number
of Au atoms and SG ligands ...... 4
1-2 Ag:SG and Au:SG bands from the same PAGE gel ...... 5
1-3 Schematic of “divide and protect” principle ...... 6
1-4 Mass spectrum and calculated electronic energies of bare sodium clusters,
N = 4 – 75 ...... 8
4- 2-1 ESI-MS spectra showing distribution of AuxAg44-x(p-MBA)30 species
synthesized by co-reduction using different Au:Ag input ratios...... 24
2-2 Distributions of M4AuxAg44-x(p-MBA)30 products obtained by co-reduction using
different Au:Ag input ratios with fits ...... 26
2-3 M4AuxAg44-x(p-MBA)30 species distribution before and after thermal processing
for Au:Ag input ratios of 12:32 and 14:30...... 28
2-4 Optical absorption spectra of M4AuxAg44-x(p-MBA)30 species synthesized with a
14:30 input ratio of Au:Ag as a function of thermal processing time ...... 29
2-5 Structure of M4Au12Ag32(p-MBA)30 ...... 32
2-6 Antigalvanic exchange on M4AuxAg44-x(p-MBA)30 nanoparticles ...... 35
4- 2-7 ESI-MS spectra showing distribution of AuxAg44-x(p-MBA)30 species
synthesized by galvanic exchange using different Au:Ag input ratios ...... 37
xi
2-8 Calculated free energy change for each galvanic exchange reaction to make
AuxAg44-x(p-MBA)30 clusters ...... 40
4− 2-9 Spontaneous fragmentation of Au12Ag32(p-MBA)30 (L = p-MBA) nanoparticles
produced by co-reduction and galvanic exchange methods ...... 42
2-10 ESI-MS spectrum of a pre-purified crystallization sample ...... 44
4- 2-11 MS/MS spectra of AuxAg44-x(p-MBA)30 ions as a function of x ...... 45
4- 2-12 Survival rate as a function of nanoparticle concentration for Ag44(p-MBA)30
4- and Au12Ag32(p-MBA)30 ions ...... 46
2-13 Activation barrier height of unimolecular fragmentation reaction for
M4AuxAg44-x(p-MBA)30 relative to M4Ag44(p-MBA)30 ...... 47
2-14 Optical absorption spectra evolution of M4AuxAg44-x(p-MBA)30 species
synthesized by galvanic exchange using gold thiolates...... 48
3-1 Absorbance spectra of Ag:TBBT molecular nanoparticles ...... 55
3-2 ESI mass spectrum of a mixture of Ag:TBBT molecular nanoparticles ...... 56
3- 3- 3-3 Spontaneous fragmentation of Ag44(TBBT)30 and Ag17(TBBT)12 ...... 57
3-4 ESI mass spectrum of Na3Ag17(TBBT)12 ...... 59
3-5 Absorption spectrum of Na3Ag17(TBBT)12 nanoparticles ...... 60
3-6 Proposed structure for Na3Ag17(TBBT)12 nanoparticles ...... 62
3-7 Electronic properties of Na3Ag17(TBBT)12 nanoparticles...... 65
3-8 ESI mass spectra of Na3AuAg16(TBBT)12 nanoparticles ...... 66
3-9 Optical absorption spectra of Na3AuAg16(TBBT)12 nanoparticles in DMF ...... 67
3-10 X-ray–determined structure of (TOA)3AuAg16(TBBT)12 nanoparticles and
comparisons with the theoretical prediction ...... 69
xii
4-1 Optical absorption spectra of M4Ag44(p-MBA)30 nanoparticles and the product of
the glutathione ligand exchange reaction. Inset: PAGE separation comparing the
exchange products to the members of the previously reported family of Ag:SG
nanoparticles ...... 79
4-2 Structures of ligands used in the study: p-MBA, TBBT, BT, CHT, p-MMBA,
TBBM, BM, PET ...... 80
4-3 Optical absorption spectra of M4Ag44(SR)30 nanoparticles in DMF, where SR is
TBBT, BT, and p-MBA. Inset: spectra of Ag nanoparticle product with other
ligands: TBBM, p-MMBA, PET, and CHT ...... 81
4-4 ESI mass spectra of M4Ag44(SR)30 nanoparticles in DMF, synthesized using
p-MBA, BT, and TBBT ...... 82
4-5 ESI mass spectra of nanoparticles synthesized using CHT, p-MMBA, TBBM and
PET ...... 83
4-6 Absorbance spectra of the products of ligand exchange reactions using
M4Ag44(p-MBA)30. Starting material, BT, TBBT, p-MBA (control), PET, CHT,
TBBM, BM ...... 84
4-7 NOESY NMR of Na4Ag44(p-MBA)30 nanoparticles in DMF ...... 87
4-8 Optical absorption spectra of a mixture of Ag:SG nanoparticles (dashed) and a
product of the ligand exchange (solid) with p-MBA ...... 90
4-9 ESI mass spectra of ligand exchange products using GSH:M4Ag44(p-MBA)30
ratios of 0:1, 5:1, 10:1, and 20:1. Gaussian fits to peak intensities from...... 92
xiii
List of Abbreviations
ACS ...... American Chemical Society
BM ...... Benzyl Mercaptan BO-DFT ...... Density Functional Theory using Born-Oppenheimer approximation BT ...... Benzenethiol
CCD ...... Charge-Coupled Device CE ...... Collision Energy CHT...... Cyclohexanethiol CID ...... Collision-Induced Dissociation
DFT ...... Density Functional Theory DMF ...... Dimethylformamide DMSO ...... Dimethyl Sulfoxide DOS...... Density of States
EF ...... Fermi Level ESI...... Electrospray Ionization ESI-MS ...... Electrospray Ionization Mass Spectrometry fcc ...... face-centered cubic structure
GE ...... General Electric GGA ...... Generalized Gradient Approximation GSH...... Glutathione
HDMS ...... High Definition Mass Spectrometry HOMO ...... Highest Occupied Molecular Orbital
IMS ...... Ion-Mobility Spectrometry
LDI ...... Laser Desorption Ionization LUMO ...... Lowest Unoccupied Molecular Orbital
MALDI ...... Matrix-Assisted Laser Desorption Ionization xiv
MNP ...... Molecular Nanoparticle MS ...... Mass Spectrometry MS/MS ...... Tandem Mass Spectrometry
NMR ...... Nuclear Magnetic Resonance NOESY ...... Nuclear Overhauser Enhancement Spectroscopy NP ...... Nanoparticle
PAGE ...... Polyacrylamide Gel Electrophoresis PBE ...... Perdew–Burke–Ernzerhof functional PET ...... 2-phenylethanethiol p-MBA ...... p-mercaptobenzoic acid p-MMBA...... p-(mercaptomethyl)benzoic acid PW91...... Perdew−Wang exchange and correlation functional qTOF ...... Quad Time of Flight
RCF ...... Relative Centrifugal Force RMS ...... Root Mean Square RS ...... Relative Stability
SID ...... Surface-Induced Dissociation SR ...... Thiolate
TBBM ...... 4-tert-butylbenzyl mercaptan TBBT ...... 4-tert-butylbenzylthiol TDDFT ...... Time Dependent Density Functional Theory TEM ...... Transmission Electron Microscopy TEMED ...... Tetramethylethylenediamine TOA ...... Tetraoctylammonium TOF ...... Time of Flight mass analyzer TPP ...... Triphenylphosphine
UV ...... Ultraviolet
VASP-DFT ...... Vienna Ab-initio Simulation Package - Density Functional Theory
XRD ...... X-ray Diffraction
xv
List of Symbols
ν ...... Number of valence electrons of the metal
Å ...... Angstrom e− ...... Electron eV ...... Electronvolt K ...... Degrees Kelvin L ...... Number of ligands M ...... Number of metal atoms n*...... Number of delocalized electrons in a nanocluster x...... Number of Au atoms in a M4AuxAg44-x(SR)30 nanoparticles Z ...... Overall nanocluster charge
xvi
Chapter 1
Introduction
1.1 History of Nanoparticles
From prehistoric times, metals have always been highly valued among humans.
Use of copper tools instead of stone ones increased the efficiency of ancient agricultural
techniques and played a role in the development of civilization after the Neolithic
revolution. Malleability of metals made them better materials for making tools for farming. One of the theories on scarcity of metal tool relics hypothesizes that they were constantly reused and recycled due to the high value of the metals.1 Every new metal
discovered by humans brought a new set of properties to the table, and was followed by a
plethora of inventions and technological improvements. Adding tin to copper to make
bronze made a societal transition from the Copper age to the Bronze age, since this
alloying gave tools greater hardness, which was a significant improvement. By the
beginning of the 21st century all metals had been discovered, and the emerging fields of
material science and nanotechnology became new fountains of novel properties.
It is surprising, that the first use of nanomaterials dates back to as early as the 4th
century.2 Ancient glassmakers were unintentionally forming colloidal gold nanoparticles
by adding tiny amounts of gold dust into molten glass, the most famous example of 1
which being the Lycurgus Cup.2 Using this technique, they could create glass with red
color, called cranberry glass, or gold ruby. Another well-known example of unintentional
nanoparticle use is in Damascus steel. Reibold et al. have shown using high resolution
TEM that Damascus steel contains multiwalled carbon nanotubes.3 This additive is what
is believed to be responsible for the famous properties of eastern Damascus swords, such as exceptionally sharp cutting edges and the characteristic wavy banding pattern on the
surface.
The first deliberate synthesis of gold nanoparticles and an attempt to describe
their optical properties in scientific terms belongs to Michael Faraday. In his classic 1857
paper, he shares the recipe for producing colloidal gold by reduction of gold chloride
solution using phosphorus.4 Remarkably, solutions of these colloidal gold particles are stable to this day, and displayed in Faraday’s original laboratory in the Faraday Museum in London. Faraday’s attempt to explain the ruby red color of colloidal gold was lacking a developed electromagnetic theory of light, that was proposed later, in 1864, by James
Maxwell5. However, full explanation of the origin of color in colloidal solutions of
metals was achieved only in 1908, when another classic paper was published by Gustav
Mie,6 in which he explained among other things, the phenomena of light absorption and
scattering by small spherical metal particles. Since then, great advancements have been
reached in the field of conventional noble metal nanoparticles including synthesis of
various shapes and compositions,7 functionalization,8 and commercial applications.9-10
2
1.2 Development of Precious Metal Molecular Nanoparticles Field
Nanoparticles occupy an intermediate position between bulk material and a single atom. Simple calculations using unit cell data for silver (fcc, 408.57 pm in length,11 and
0.068202 nm3 in volume) and considering 4 atoms per unit cell, shows that even a 5 nm
nanoparticle contains about 4 000 silver atoms and weighs around 400 kDa. It was
recognized in the 1980s that there is still a large gap between the properties of colloidal
nanoparticles and a single atom. A large portion of the materials science community
started directing their efforts towards the particles made of 10-1000 atoms, called
clusters, motivated by advancement of fundamental knowledge, as well as potential
beneficiary technological advances.12
Most of the cluster research, in its early years, was focused on gold clusters of low nuclearity, and mostly on gas-phase experiments.13 By the mid-1990s, methods for
obtaining high-nuclearity clusters in the solution phase started appearing in the
literature.14 Phosphines and thiols were used as protecting ligands. It became clear that
continuous distribution of sizes in the upper part of the nanoscale turns into discrete size
series in the lower region of the nanoscale.14 Formulae became more informative and
appropriate for describing a nanoparticle than its core diameter. Unfortunately, due to
underdeveloped synthetic and processing techniques and lack of resolving power of
analytical instrumentation, a majority of the formulae could not be determined at the
time. With the development of high resolution mass spectrometry and soft ionization
techniques,15-16 the research community became able to analyze these molecular
nanoparticles with atomic precision. In 2005, Negishi and Tsukuda published a seminal
work on glutathione-protected gold nanoclusters that were separated by PAGE and 3
analyzed by ESI mass spectrometry, consequently deducing their molecular formulae
from charge state distributions.17 The data analysis was challenging and had some flaws,
but a year later the same group published an updated catalog of the cluster formulae for
the glutathione family.18 Photographs of solutions of glutathione-protected nanoparticles and their metal and ligand counts are shown in Figure 1-1. It can be clearly seen that the family represents a discrete series of sizes.
Later in 2010, analogous work, aimed at obtaining a family of silver clusters protected by glutathione was reported by the Bigioni group, however without MS
analysis.19 It has been recognized early on that higher lability of silver molecular
Figure 1-1. Plot of the chemical compositions of Au:SG nanoclusters against the number of Au atoms and SG ligands. The closed and open dots represent the most dominant and minor species contained in the fractions, respectively. Reprinted with permission from reference 18 (copyright 2005, American Chemical Society)
4
Figure 1-2. Ag:SG and Au:SG bands from the same PAGE gel. The number of metal atoms in each Au:SG band is indicated. Reprinted with permission from reference 19 (copyright 2010, American Chemical Society) nanoparticles compared to their gold counterparts significantly imparts their formula
determination by mass spectrometry. A comparison of Au:SG and Ag:SG series is shown
on Figure 1-2. A non-monotonic change in properties, in this case a color, can be clearly
seen in the case of Ag:SG nanoparticles. Such behavior is in contrast to the monotonic
change in properties observed in large plasmonic nanoparticles.20
Another milestone in the research on precious metal nanoclusters was the
21-22 discovery of the crystal structure of Au102(p-MBA)44 by Roger Kornberg in 2007.
Knowing the arrangement of metal atoms in the core and in the core-shell interface was
crucial for understanding the origins of stability and properties of the nanoparticle.
Careful analysis of the structure showed that the “divide and protect principle” proposed earlier by Hakkinen and coworkers23 is useful for discussing structures of molecular
nanoparticles. According to this principle, the structure of molecular nanoparticles can be
viewed as a metallic core protected by capping motifs made of metal thiolates. In the
case of Au102(p-MBA)44, a 79-atom grand core had a truncated decahedral shape,
supporting earlier predictions of 5-fold symmetry in small gold nanoparticles,24 and
5
Figure 1-3. Schematic of “divide and protect” principle. Grand core of Au102(p- MBA)44 is capped by protecting gold thiolate motifs (left). Gold(I)-thiolate compounds have also been structurally characterized (bottom right). In both panels, gold atoms are depicted as yellow circles, sulfur as orange circles; the hexagons denote a phenyl (-C6H5) aromatic hydrocarbon. Adapted with permission from reference 22 (copyright 2007, American Association for the Advancement of Science capping motifs resembled fragments of linear gold thiolate polymer.25 The free electron count supported the superatomic model (vide infra).
In 2013, the first crystal structure of thiolate-protected silver nanoparticle,
26-27 M4Ag44(p-MBA)30, was discovered independently by two groups. Similar to the earlier reported case of gold, the core was found to have a high degree of symmetry. The structure of the capping motifs was found to be closely related to the structure of silver thiolate polymer,28 and the electron count was in accordance with the superatom model for spherical nanoparticles. Since then, plenty of new nanoparticles have been reported and their structures determined, which gave an opportunity to test existing theoretical models regarding structure and stability of nanoclusters.
6
1.3 Electronic and Geometric Shell Closing Rules
Early work on clusters in the gas phase supported the development of the so-
called superatomic theory based on the jellium model. The jellium model,29-30 also called
the unified electron gas model, treats the positive charges of the nuclei as being
uniformly distributed in space and focuses on a rigorous treatment of electron-electron
interactions between valence electrons. Its importance is that most of the computational
resources can be allocated to the modeling of outer shell electrons that govern the
chemistry of the compound. Core electrons and nuclei are represented by
pseudopotentials, which is advantageous for saving computational time for systems with
a large number of electrons, such as small noble metal nanoparticles.
Due to quantum confinement of electrons in a small metallic nanoparticle, the
quantization of energy level occurs. Superatomic theory treats the metal core as a large
spherical “superatom” and uses valence electrons to fill the superatomic orbitals, which
are analogous to regular atomic orbitals.31 One important difference is the set of angular
quantum numbers. The orbitals are filled according to the Aufbau principle in the
following order: 1S2|1P6|1D10|2S21F14|2P61G18|2D103S21H22|…, where a vertical line
denotes a significant HOMO-LUMO gap.32 So, for a gold or silver cluster with a
symmetry close to spherical, structures with 2, 8, 18, 34, 58, 92, 138 electrons will have
significant stability.32 Early work by Knight et al. clearly illustrated the idea of electronic shell closing by experimenting with sodium clusters.33 In the gas phase, clusters of some
special “magic numbers” have higher abundances compared to others, but for sodium,
magic numbers are slightly different from those of noble metals (Fig. 1-4 (a)). When
Schrödinger equations are solved for 3s valence electrons in a spherically symmetric 7
Figure 1-4. (a) Mass spectrum of sodium clusters, N = 4 – 75. The full scale intensity in the main figure is approximately 20 000 counts/sec. The inset corresponds to N = 75 – 100. (b) The calculated change in the electronic energy difference, Δ(N + 1) – Δ(N), vs N. The labels of the peaks correspond to the closed-shell orbitals. Reprinted with permission from reference 33 (copyright 1984, American Physical Society potential well and the difference of electronic energies of adjacent clusters is plotted as a function of the number of sodium atoms (Fig. 1-4 (b)), the graph shows peaks that almost perfectly coincide with experimentally observed “magic numbers”. These numbers correspond to numbers of free valence electrons required to close a series of superatomic orbitals. So, what is different in the condensed phase? First, in the solution phase clusters undergo much higher numbers of collisions with their surroundings compared to the low- pressure gas phase inside of a mass spectrometer, so clusters with a closed electronic
8
shell will be the only species surviving, since their open-shell counterparts will undergo a
transformation. Moreover, precious metal clusters in the condensed phase need to be
protected by organic ligands, commonly a thiolate, so the electron count should account
for the formation of metal-ligand bonds on the core-shell interface, which require one
electron per bond. Therefore, the formula for calculating the number of free delocalized
electrons is the following:
n* = νM – L – Z,
where ν is the number of valence electrons of the metal, M is the number of metal atoms,
L is the number of ligands and Z is the overall cluster charge.32 Indeed, most of the
MNPs with quasi-spherical symmetry reported in the literature obey the electronic shell
- 34 3- 35 closing rule. For example, Au25(SR)18 and Ag17(SR)12 both have 8 free electrons,
4- 26 36 21 Ag44(SR)30 , Au68(SR)34 and Au102(SR)44 have 18, 34 and 58 free electrons, respectively. Because of their molecular nature, nanoclusters are also often called molecular nanoparticles. These terms are used throughout the dissertation as synonyms.
The second stability rule, geometric shell closing should be considered. The idea
behind this rule is that each highly symmetric structure requires a number of atoms equal to the number of vertices of that solid. For example, to make a tetrahedron one will need
4 atoms, for an icosahedron one will need 12 atoms, 20 atoms are required to make a dodecahedron, etc. This rule can be easily understood using buckminsterfullerene, C60 as
an example.37 This molecule has a shape of a soccer ball, where every atom counts, and
therefore removing or adding one extra atom would destabilize the structure. Tighter packing of atoms commonly leads to stronger interatomic interactions and more stable structures. It appears that with the increase in size, geometric shell closings become more 9
38 39 important than electronic shell closing. For example, Au144(SR)60 is a particularly
stable nanoparticle with spherical symmetry despite its 84 free electron count, which does not correspond to any of the “magic numbers” for noble metal nanoclusters. Another important consideration is the location of capping motifs and configuration of ligands.
Higher density of motifs and a uniform ligand coverage make a nanoparticle more sterically protected.40
1.4 Mass Spectrometry in Molecular Nanoparticles Research
From the early days of the nanocluster field, mass spectrometry has played a
major role among characterization techniques. While bare clusters for experiments in the
gas phase were commonly produced in situ, ligand-protected molecular nanoparticles are
ionized by various techniques. Early ionization techniques, such as LDI, were too harsh
to analyze intact particles, and often only weights of the core were reported in kDa
units.14 Development of high-definition mass spectrometry gave a great impetus towards
precise determination of nanoclusters formulae, which is of crucial importance for
nanocluster research. Improvements in soft ionization techniques, namely ESI and
MALDI, led to minimization of fragmentation during an ionization event, so the formulae
of an intact cluster could be determined.
Generally, ESI is considered to be the more gentle technique, however, ESI- equipped mass spectrometers rarely have a high m/z range. MALDI, on the other hand, is more destructive, but provides a wide m/z range, which allows for analysis of molecular nanoparticles with high atom counts. Several groups showed that by carefully selecting a matrix and minimizing laser energy, gold nanoparticles can be analyzed by MALDI 10
without fragmentation.41-42 Reports showing that the same is possible for silver MNPs are
scarce since they commonly undergo severe fragmentation, mainly by cleavage of sulfur-
carbon bonds of a ligand.43
MALDI generates mostly singly charged species, which makes the m/z values fall
in the high mass range where resolution is commonly poor and does not allow for exact
formula determination. ESI, on the other hand, commonly produces multiply charged
species either by deprotonation of a ligand18, 44-45 or by adduct formation,46 which brings
m/z values to a low range where mass analyzers have a higher resolution, allowing for
less ambiguous determination of molecular mass, and therefore, a formula. Exact
molecular formulae allow for theoretical modeling and structure prediction.35 In addition
to the final product formula determination, MS can be used to monitor nanoparticle
synthesis,47 or transformation progress.48
In the last several years, substantial attention was given to the exploration of
thiolate-protected bimetallic MNPs. This allows the study of interactions of two metals
on an atomic scale, where the ligand shell serves as a container providing quantum
confinement. Ranges of nanoparticle composition and locations of heteroatoms are the
questions of the highest importance. Properties useful for separation and individual
characterization vary smoothly with the change in metallic composition of nanoparticles.
Changes in hydrodynamic radius and absorption interactions, if they exist, are not large
enough to enable separation of bimetallic nanoparticles by PAGE or chromatography, respectively. However, changes in mass can be accurately detected by HDMS, which makes it an indispensable tool for bimetallic nanoparticle characterization. Moreover,
11
HDMS can be applied to study ligand shell modifications of MNPs as long as the ligands do not have the same molecular mass.
Tandem mass spectrometry offers more in-depth analysis of MNPs. It allows studying stability in the gas phase using fragmentation via CID or SID.49 In the latter
case, in conjunction with theoretical modeling, metal-ligand bond energies can be accurately measured.50 Ion mobility spectrometry (IMS) was also used to characterize the
decomposition process of MNPs in the gas phase.51 Recently, soft-ion landing methods
were applied to nanoclusters.52-53 For soft-landing additional ion optics are attached with decelerating voltages, and the detector is replaced by a substrate on which the selected ions land. This allows the creation of nanocluster-functionalized surfaces and opens a door to evaluation of these nanoparticles as heterogeneous catalysts.54
1.5 Dissertation Overview
Current work covers formation and analysis of bimetallic nanoparticles,
development of structure prediction methodology, and a study of the ligand role in the
formation and stability of silver molecular nanoparticles. Substantial parts of the
26, 55 dissertation are related to M4Ag44(p-MBA)30 nanoparticles. Robust synthesis, single-
sized product, known crystal structure, and superior stability make it a useful platform for
investigating core and ligand shell modifications.
In chapter 2, investigation of bimetallic M4AuxAg44-x(p-MBA)30 is discussed.
Two synthetic strategies are described, and an analysis of the product in terms of
composition, stability, optical properties, and reactivity is presented. Thermochemical
12
data were calculated for galvanic exchange reactions, and kinetic energy barriers were calculated for gas-phase fragmentation using tandem MS.
In chapter 3, a new nanoparticle, initially identified as a byproduct of a synthesis
of M4Ag44(SR)30, was studied. Synthesis was optimized to produce only the new
nanoparticle, M3Ag17(SR)12. Structure prediction methodology was developed in
conjunction with computational modeling and tested by heteroatom substitution.
In chapter 4, the effects of ligand structure on the outcome of nanoparticle
syntheses were addressed. Ligands were divided into two classes that produce orthogonal
sets of species. Compatibility of ligands on M4Ag44(SR)30 nanoparticles was studied to
understand how many heteroligands are required to induce a structure transformation.
13
Chapter 2
Molecular Metallurgy of M4AuxAg44-x(SR)30 Bimetallic Nanoparticles
2.1 Introduction
It is impossible to overstate the importance of metals in the history of mankind.
Metallurgists have produced and used metals since prehistoric times, beginning with the noble metals gold, silver, and copper, which could be pulled from the Earth in their native metallic states. While copper was hard enough to use for making tools, it was not until it was alloyed with tin, to achieve technologically superior properties and performance, that the practice of metallurgy ushered in a new age of mankind: the Bronze Age. Since then, metallurgy has been key to the advancement of society through the development of technology, enabling tools of agriculture, warfare, commerce, transportation, and so on, most often through mixtures of metals, in the form of alloys and intermetallics, since it is by combining metals that new materials with useful properties emerge.
The study of metal nanoparticles has been similar in that initially the particles studied were monoelemental but over time mixtures of metals began to be studied.
Murray’s group first developed syntheses for monolayer-protected bimetallic nanoparticles in 1998.56 Molecular nanoparticles, however, are fundamentally different from larger nanoparticles in that they are molecules, which offers a new opportunity to 14
understand the mixture of metals with atomic precision and molecular definition. The
precise structures of molecular nanoparticles offer a unique opportunity to study the
mixing of metals within precisely-defined systems. While many examples exist of putting
a single heteroatom at the center of a molecular nanoparticle,57-59 few exist that involve
many heteroatoms.27, 60 In order to examine trends in properties as a function of
composition, mixtures must involve many heteroatoms. These are the systems that are
most interesting from a metallurgical point of view.
Bimetallic nanoparticles of Au and Ag have been the natural starting point since
these metals are easy to work with, they are isoelectronic, and they have the same radii,
however the different chemistry of Au and Ag leads to variations in properties with
composition.61-62 Previous efforts have focused on adding Ag into Au molecular
nanoparticles, which had the unfortunate effect of destabilizing the molecule. As a result,
it is difficult to find the natural stoichiometric limits of the mixtures, thereby
necessitating extrapolation. In the case of Au substituted into Ag nanoparticles, however,
the opposite is true, which led to the discovery of the first stoichiometric limit of
27 substitution, namely M4Au12Ag32(SR)30 (here, M is a cation and SR is a thiolate ligand).
The M4AuxAg44-x(SR)30 nanoparticle is a compelling model system for studying the chemistry of bimetallic nanoparticles since it is a well-defined system that can act as a molecular laboratory to probe a variety of questions regarding the consequences of metallurgical mixtures on the chemistry (reactivity/stability), composition, and structure of this class of molecules. While the existence of M4Ag44(SR)30 and M4Au12Ag32(SR)30
have already been established, the variation in properties with composition of
M4AuxAg44-x(SR)30 nanoparticles will herein be systematically studied to better 15
understand these molecular alloys. In fact, it is useful to view M4AuxAg44-x(SR)30
nanoparticles as molecular containers for 12 atom Au/Ag alloys, wherein the structure
and composition of the container does not change but the composition of the contents
does.
Previous studies of M4Au12Ag32(SR)30 nanoparticles reported that all 12 gold
atoms were found in the icosahedral core in the cases where SR = SPhF, SPhF2 or
SPhCF3. Such species are therefore best thought of as intermetallic nanoparticles, rather
than alloys, since the metal atoms are not randomly mixed. Other bimetallic species also
show site preferences for heteroatom substitutions, in particular those with centrally-
located heteroatoms in icosahedral metal cores.57, 63-66 In this case it is clear that these
substitutions are not random. For M4AuxAg44-x(p-MBA)30 nanoparticles with
substitutions from x = 1-12, however, it is possible that the Au atom substitutions are
truly random. This gives impetus to the metallurgical approach to studying the properties
of these bimetallic mixtures, which are contained within the heart of the M44 molecule.
2.2 Experimental
2.2.1 Chemicals. The following reagents were purchased from Fisher Chemical:
sodium borohydride, ethanol, methanol, toluene, N,N-dimethylformamide (DMF),
dimethyl sulfoxide (DMSO), citric acid, acetic acid, sodium hydroxide, cesium
hydroxide. Silver nitrate and 4-mercaptobenzoic acid (p-MBA) were purchased from
Sigma-Aldrich. Gold (III) chloride was purchased from Alfa Aesar. The p-MBA was
purified by selective dissolution in methanol. All other reagents were used without
further purification. De-ionized water (18.2 MΩ cm) was used. 16
2.2.2 Synthesis of M4AuxAg44-x(p-MBA)30 by co-reduction. The amounts of
AgNO3 and AuCl3 were varied to synthesize the M4AuxAg44-x(p-MBA)30 product with
different compositions (i.e. to vary x) using co-reduction. For example, for a Ag to Au input ratio of 30:14, 86.8 mg of AgNO3 (0.51 mmol) and 72.4 mg of AuCl3 (0.24 mmol)
were used for the metal sources. These materials were added to 33 ml of 7:4 water-
DMSO solvent along with 173.5 mg of p-MBA (1.125 mmol). This mixture was stirred
for 5 min and then sonicated for 2 min. These reagents reacted to form a precursor
mixture of metal thiolates, which was a cloudy light yellow precipitate that was dispersed
in the solvent. The pH was then adjusted to 12 using 50% w/v aqueous CsOH. The metal
thiolates dissolved as the pH was raised above 9, forming a clear, light yellow solution.
Next, 7.5 mmol of NaBH4 reducing agent was dissolved in 9 ml of water, was added
dropwise over a period of 30 min, and was left to stir for 1 h. This formed a dark
yellow/brown solution. Once the reaction was completed, the product solution was first
centrifuged for 5 min and decanted, and then precipitated using DMF. The precipitate
was collected by centrifugation and decanting. It is important not to dry this raw product.
The raw product was precipitated from a basic solution, therefore it was the
conjugate base (alkali metal salt) of the fully protonated species. To protonate, pure DMF
was added to the precipitated particles, which did not initially solubilize. Citric acid was
then added to the solution until the precipitate dissolved into the DMF, forming a golden
brown solution. Protonation was repeated 3 times, using toluene to precipitate from
DMF.
2.2.3 Synthesis of M4AuxAg44-x(p-MBA)30 by Galvanic Exchange. The galvanic
exchange reaction was carried out in semi-aqueous medium. A stock solution of 17
26, 55 M4Ag44(p-MBA)30 was prepared as described elsewhere. The concentration of the
stock solution was determined using the molar absorption coefficient of M4Ag44(p-
55 MBA)30. To prepare Au-(p-MBA) thiolate, 0.5 mmol of HAuCl4∙3H2O and 1.5 mmol of
p-mercaptobenzoic acid were allowed to react in a 7: 4 by volume of water: dimethyl
sulfoxide (DMSO) solvent mixture. The reaction mixture was sonicated for 5 min and
stirred for 10 min. An insoluble mass of gold thiolate was separated from the supernatant
by centrifugation and solubilized by using aqueous cesium hydroxide solution (50% w/v).
Cesium hydroxide raised the pH to ~10, which deprotonated the carboxylate group of the
ligand and made the gold thiolate soluble in polar solvents. 1.20 mL of acetic acid was
added in order to protonate the thiol ligands and precipitate the gold thiolate out of the
solvent. It is important to clean the starting material from chloride. Thiolates acts as
pseudohalides because their chemistry is similar to that of halides. Chloride can partially
substitute thiols in the process of ligation, which adds inconsistency to results. At this
point, the reaction mixture was centrifuged and the supernatant was tested for Au3+ and
Cl- ions and then discarded. The precipitate was redissolved in water: DMSO solvent (7:4
by volume, pH=12). The gold thiolate was precipitated out of the solvent again by adding
1 mL concentrated nitric acid. The reaction mixture was centrifuged and the supernatant
was discarded after testing for Au3+ and Cl-. The process of dissolution of gold thiolate
with cesium hydroxide solution and precipitation with nitric acid was repeated one more
time. The loss of Au3+ in the supernatant was tested with sodium borohydride and that of
Cl- was tested with silver nitrate. The final supernatant obtained was free of Au3+ and Cl-,
which means that gold was completely bound to the ligand. The obtained gold thiolate
precipitate was first dissolved in aqueous cesium hydroxide solution (50% by weight) and 18
DMSO was added later to maintain the ratio of the solvent system as 7:4, and hence 0.2
M gold thiolate solution was prepared.
A calibration curve of gold thiolate solution, based on phenyl ring absorbance at
~308 nm vs concentration, was plotted and was used for quantifying the amount of gold thiolate. Eight galvanic exchange reactions were set up. The molar ratios of Au thiolate:
Ag44 used were 1:1, 2:1, 6:1, 9:1, 12:1, 14:1, 22:1 and 26:1. For this, Ag44 was quantified in dimethyl formamide (DMF) by using its published molar absorptivity. Then it was precipitated by using toluene as antisolvent and redissolved in highly basic water:
DMSO solvent (7:4 by volume, pH=12). The gold thiolate and Ag44 solutions were mixed together in the above mentioned ratios and the galvanic exchange was monitored by using UV-visible absorption spectroscopy and mass spectroscopy.
2.2.4 Thermal processing. Fully-protonated M4AuxAg44-x(p-MBA)30 nanoparticles prepared with a 14:30 input ratio of Au:Ag were used for thermal processing experiments. Capped glass vials containing DMF solutions of the nanoparticles were placed in a water bath at 60 °C. After incubation, insoluble material produced by thermal processing was separated from the solution by centrifugation.
2.2.5 Optical measurements. Optical absorption spectra were recorded on a
Perkin Elmer Lambda 950 spectrophotometer. Spectra of M4AuxAg44-x(p-MBA)30 nanoparticles were measured in neat DMF or DMSO solvents. For the thermal processing experiments, 1.0 mL aliquots were taken, centrifuged, and placed in a 1 mm path length cuvette to record the absorption spectra. For samples made by galvanic exchange reaction solutions were centrifuged and diluted 40 times to 2 mL and measured in a 5 mm cuvette.
19
2.2.6 Electrospray Ionization Mass Spectrometry (ESI-MS). Mass
spectrometry data were collected on a Synapt HDMS G1 quadrupole-time-of-flight ion mobility mass spectrometer equipped with a nanoflow electrospray ionization source
(Waters Corp.), using homemade fused silica emitters. All mass spectra were collected in either negative V-mode or negative W-mode. The instrument was operated using the following parameters: capillary voltage, 2.0–4.0 kV; sampling cone, 15 V; extraction cone, 4.0 V; cone gas, 0 L/h; nanoflow, 0.1 bar; trap collision energy, 0.5 V; transfer collision energy, 1.0 V; source temperature, 40 °C; desolvation temperature, 120 °C. The instrument was calibrated in negative mode using cesium iodide in the range of 100 ≤ m/z ≤ 4000. Data were collected and processed using MassLynx 4.1 software (Waters
Corp.). Isotopic patterns were simulated using mMass 5.5 freeware (copyright, Martin
Strohalm). All samples were dissolved in DMF with a concentration of approximately 3 mg/mL.
For sample preparation of galvanic exchange experiments, 300 µL of each sample were precipitated by 350 µL of DMF. In the case of samples with 1 and 2 Au equivalents,
10 µL of 50% (w/v) CsOH solution were added to deprotonate nanoparticles and facilitate precipitation. Precipitates were collected be centrifugation at 5000 RCF for 30 s.
Isolated nanoparticles were protonated in 300 µL of DMF three times following precipitation with toluene and centrifugation. The first two protonations were carried out by adding approximately 20 crystals of citric acid, and the third protonation was carried out by adding 20 µL of formic acid. After the third protonation, NPs were cleaned by one more precipitation-dissolution cycle with no additives. Final samples were centrifuged at
20
16000 RCF for 2 min to remove any insoluble material prior to mass spectrometry
measurements.
2.2.7 Crystallization. The M4AuxAg44-x(p-MBA)30 nanoparticles were prepared
by co-reduction, then enriched in M4Au12Ag32(p-MBA)30 by thermally processing, washed and cleaned. The crystals were grown from a neat DMF solution of nanoparticles, dried under N2 gas. The resulting process obtained small rhombohedral crystals (~10
μm). These crystals were used as seeds in a second crystallization step. The second
solution was dried under N2 and the seeds grew into larger rhombohedral crystals (>50
μm). The crystals were first separated and isolated on a microscope slide using paratone
oil, and then were picked up and mounted with a MiTeGen MicroLoop.
2.2.8 Single-Crystal X-Ray Diffraction and Analysis of M4Au12Ag32(p-
MBA)30. The data reported herein were collected from a crystal of approximate
dimensions 200x200x100 μm3, which was cooled to 100 K for data collection. X-ray diffraction data were collected on a Bruker Apex Duo diffractometer (graphite- monochromated, CuKα = 1.54178 Å), which was equipped with an Apex II CCD detector and an Oxford Cryostream 700 low temperature device. The frames were integrated with the Bruker SAINT software package using a narrow-frame algorithm. The integration of the data using a trigonal unit cell yielded a total of 189319 reflections to a maximum θ angle of 62.42° (0.87 Å resolution), of which 12622 were independent
(average redundancy 14.999, completeness = 100.0%, Rint = 5.58%, Rsig = 1.92%) and
11138 (88.24%) were greater than 2σ(F2).
The structure was solved and refined using the Bruker SHELXTL software
package, using the R-3c space group, with Z = 6 for the formula unit 21
2 C210H150Ag32Au12O60S30. The final anisotropic full-matrix least-squares refinement on F with 373 variables converged at R1 = 3.98% for the observed data and wR2 = 13.87% for
all data. The goodness-of-fit was 1.090. The largest peak in the final difference electron
density map was 2.539 e-/Å3 and the largest hole was -1.536 e-/Å3 with an RMS
deviation of 0.253 e-/Å3. On the basis of the final model, the calculated density was 1.458
g/cm3 and F(000) was 28932 e-.
The M4Au12Ag32(p-MBA)30 nanoparticles crystallized in the R-3c space group.
All of the Ag, Au and S atoms were located by direct methods. During the following refinements and subsequent difference Fourier syntheses, the remaining C atoms and O atoms were located.
Refinements were restrained and constrained to idealize values (HFIX and
PART). The Au, Ag and S atoms were ordered, however 3 out of the 5 ligands in the asymmetric unit cell were disordered over two positions. The 3 disordered ligands were modeled over the two positions with the PART command, and then each position was relaxed and refined using a free variable to determine the site occupancy.
Au, Ag, and S atoms were refined with anisotropic displacement parameters, while all C and O atoms were refined with isotropic atomic displacement parameters. All
H atoms were geometrically determined (HFIX) and included as riding atoms in the final refinements. It is common for these nanoparticles to have a high amount of residual electron density observed in the metal core. It is noted that the alkali metal cations and the solvent molecules were not identified in the X-ray data (highest residue density was
2.539 e-/Å3).
22
2.3 Results and discussion
2.3.1 Synthesis. The synthesis of M4AuxAg44-x(p-MBA)30 bimetallic nanoparticles involves substituting a fraction of the silver for gold in the protocol for making M4Ag44(p-MBA)30 nanoparticles. When gold and silver salts were mixed together
in solution in the presence of p-MBA capping ligands, they reacted to form metal-
thiolates. The formation of the metal-thiolate precursor was not found to depend on the
order in which the metal salts were added if an excess of ligand was used. The metal-
67-68 thiolates were then reduced to form M4AuxAg44-x(p-MBA)30 bimetallic nanoparticles.
M here denotes Na+ or Cs+ ions. Since synthesis and processing involve inorganic
compounds containing these two metal ions, it is impossible to conclude which ion would
serve a role of a counterion. The synthetic reaction can be written approximately as
follows:
(Ag(p-MBA))m + (Au(p-MBA))n + NaBH4 → M4AuxAg44-x(p-MBA)30 + other species (1)
The reactivities of gold and silver are different therefore it is not obvious that the
composition of the final M4AuxAg44-x(p-MBA)30 nanoparticle product ought to be the
same as the Au:Ag ratio in the reactant mixture (hereafter referred to as the input ratio).
A series of synthetic reactions with Au:Ag input ratios varying from 0:44 to 26:18 were carried out and the compositions of the M4AuxAg44-x(p-MBA)30 nanoparticle products
were analyzed using ESI-MS. The populations of product species as measured by ESI-
MS are shown in Fig. 2-1.
23
4- Figure 2-1. ESI-MS spectra showing distribution of AuxAg44-x(p-MBA)30 species synthesized by co-reduction using different Au:Ag input ratios. Only species for 0 ≤ x ≤ 12 were observed. Species at m/z 2319.4 are 4- Au1Ag43(p-MBA)29 .
24
It is reasonable to expect that the random distribution of metal atoms in the
reaction mixture would lead to random nanoparticle compositions. In this case, gold
substitutions, x, ought to be characterized by a Gaussian distribution of product species
with compositions centered at the input number of gold atoms. This was approximately
the case for the input ratios 6:38 and 9:35, but it was not the case for the other input ratios
(see Fig. 2-1). At low input ratios, the distributions were bimodal, with both gold-rich and
gold-poor species observed. At high input ratios, the products tended to contain fewer
gold atoms than expected. It was also observed that the M4AuxAg44-x(p-MBA)30
nanoparticle products contained a maximum of 12 gold atoms consistent with the
previous report by Zheng.27
The bimodal distributions for low input ratios could be viewed as consisting of
one distribution with gold-rich species centered near x = 6 and one with gold-poor
species centered near x = 0, i.e. Ag44. The distributions could not be fit well with two
Gaussians (see Fig. 2-2), however, indicating that the products of the reaction likely changed over the course of the reaction and were therefore not truly random. For example, gold is more noble than silver and could be reduced preferentially at the beginning of the reaction, such that the initial solution composition would have contained more gold “monomers” at early times. This would have resulted in the production of gold rich compounds early in the reaction. Depletion of gold early in the reaction would have
then led to the formation of compounds with fewer gold atoms later in the reaction,
skewing the distribution toward lower x. Finally, Ag44 would have formed from the
remaining silver once the gold was consumed, leading to a complex (i.e. non-random)
distribution of species. It is also important to note that the population of species at low x 25
Figure 2-2. Distributions of M4AuxAg44-x(p-MBA)30 products obtained by co- reduction using different Au:Ag input ratios. Gaussians were fit into the distributions. In case of low gold loading bimodal distributions were fit with 2 Gaussians.
is expected to be underrepresented by the peak intensities due to lower stability, i.e.
higher fragmentation rates,27 which would distort the expected distributions somewhat.
At high input ratios, deviations from expectations are in the opposite sense.
Species were observed with lower gold loadings than expected based on the input ratio of metals. Increasing the amount of gold in the reaction mixtures resulted in increasing the amount of gold in the M4AuxAg44-x(p-MBA)30 product, however larger nanoparticle
species were also found when input ratios contained 12 or more parts gold. It was not
until equal parts silver and gold were used in the co-reduction reaction that
26
M4Au12Ag32(p-MBA)30 nanoparticles were found to be the most abundant of the
M4AuxAg44-x(p-MBA)30 nanoparticles produced. As the amount of gold in the reaction mixture was increased further, however, M4AuxAg44-x(p-MBA)30 nanoparticles ceased to be produced. Instead, large bimetallic nanoparticles were formed that primarily consisted of gold. These species were likely Au68 with silver atom substitutions. The distributions of M4AuxAg44-x(p-MBA)30 species were found to be Gaussian for intermediate to high input ratios, with the Gaussian distributions truncated at the x = 12 limit (see Fig. 2-2).
The range of gold substitutions was found to be limited to the range 0 ≤ x ≤ 12, which corresponds to filling the inner icosahedral core with up to 12 gold atoms.27 It is curious to note that there appears to be a bias toward x = 6 in several of the MS measurements in Fig. 2-1, wherein the distributions of species are Gaussian. These distributions correspond to the highest entropy configurations of heteroatoms in the nanoparticle cores, which may contribute to the bias in the product distribution. At higher gold inputs, the competition between gold incorporation into M4AuxAg44-x(p-MBA)30 and the formation of larger gold nanoparticles biases the product distribution toward lower x, which indicates that the thermodynamic driving force for making M4Au12Ag32(p-MBA)30 nanoparticles is not dominant. Further, these biases in the synthetic products indicate that the chemistry of the different M4AuxAg44-x(p-MBA)30 species may depend on composition (i.e. depend on x) in non-trivial ways.
2.3.2 Thermal stability. Silver nanoparticles naturally react with different species in solution (i.e. oxygen, other particles, etc.) such that solution compositions change over time. If the reactivity of bimetallic nanoparticles varies as a function of composition, then changes in the populations over time due to varying solution-phase stability will be 27
indicative of the different reactivities. Solutions of M4AuxAg44-x(p-MBA)30 nanoparticles, with varying x, were therefore heated in a water bath at 60 °C for 24 h and the populations of species were measured by ESI-MS before and after the thermal processing
(see Fig. 2-3). These solutions were prepared using Au:Ag input ratios of 12:32 and
14:30, which predominantly contained species where 7 ≤ x ≤ 12.
Figure 2-3. M4AuxAg44-x(p-MBA)30 species distribution before (solid lines) and after (dashed lines) thermal processing for Au:Ag input ratios of 12:32 (red) and 14:30 (blue). M4AuxAg44-x(p-MBA)30 species were more resistant to degradation as x increased. Here, the relative abundances were scaled such that the abundance of M4Au12Ag32(p-MBA)30 was kept constant.
ESI-MS measurements showed that the solution-phase thermal stability of
M4AuxAg44-x(p-MBA)30 nanoparticles depended strongly on the number of gold atoms
(see Fig. 2-3). Attrition was found to be most prevalent among species with fewer gold atoms, with thermal stability monotonically increasing with the number of gold atoms to a maximum in stability when x = 12. It is possible to use this dispersion in chemical 28
stability as a function of composition to discriminate between species that are otherwise quite similar and difficult to separate, enriching the product in the most stable species.
Thermal processing was used to prepare M4Au12Ag32(p-MBA)30 nanoparticles.
First, an input ratio of 14:30 was used to synthesize a product distribution with a
maximum that was slightly below M4Au11Ag33(p-MBA)30. Next, the distribution of
species was focused to x = 12 by thermal processing in a water bath at 60 °C for 30 h. A
series of spectra show the evolution of the distribution as a function of time, wherein the
spectrum of the final distribution was that of M4Au12Ag32(p-MBA)30 (see Fig. 2-4). It
Figure 2-4. Optical absorption spectra of M4AuxAg44-x(p-MBA)30 species synthesized with a 14:30 input ratio of Au:Ag as a function of thermal processing time. Absorbances were not adjusted but spectra were offset for clarity. Inset shows first and last time points with no offset.
29
should be noted that the optical density of the solution decreased over time as the more
reactive species were destroyed (see Fig. 2-4, inset).
2.3.3 Location of Au heteroatoms. Once high-purity samples of M4Au12Ag32(p-
MBA)30 nanoparticles were prepared, the locations of the gold atoms could be
determined. Prior reports determined that the gold atoms were located in the icosahedral
inner core of the molecule,27 however it is not clear whether different synthetic conditions
and different ligands would affect this. There are four sets of chemically equivalent
positions for metal atoms in the M4AuxAg44-x(p-MBA)30 structure. All 12 positions in the
icosahedral inner core are chemically equivalent, whereas the dodecahedral outer core
contains a set of 8 chemically equivalent positions (defining a cube) and a set of 12
chemically equivalent positions (a pair of atoms beneath each of the six mounts). The
remaining 12 metal atoms are found in pairs in the six mounts and are chemically
equivalent. In principle, then, there are three possible ways to locate 12 equivalent gold
heteroatoms.
Density-functional calculations were performed to evaluate the energy differences
upon substitution of gold atoms into each of these four distinct metal atom positions.
Each calculation was performed for a M4AuAg43(p-MBA)30 nanoparticle, the structures
of which were relaxed after substitution. In each case, the energy of M4AuAg43(p-
MBA)30 was found to be lower than M4Ag44(p-MBA)30. It was found that substitution of gold atoms into the icosahedral core has the biggest effect, lowering the energy by 0.701 eV. The next most favorable position was that of the 8 atoms in the dodecahedral shell, lowering the energy by 0.288 eV. These positions are of particular interest since they are the only parts of the metal core that are exposed and capable of directly interacting and 30
reacting with other species in solution. The least favorable positions for substitution were
found to be the pairs of metal atoms in the mounts, lowering the energy by 0.163 eV, and
the pairs of metal atoms beneath the mounts, lowering the energy by 0.119 eV. Based on
these calculations, the 12 substituted gold atoms were expected to be found in the
icosahedral core.
The positions of the 12 Au atoms were measured by single-crystal x-ray
crystallographic methods. Rhombohedral crystals of high-purity M4Au12Ag32(p-MBA)30
nanoparticles were measured at ~100 K, indexed, and integrated using a trigonal unit cell
and the space group R-3c. The cell parameters were found to be a = 25.7341(3) Å, c =
124.079(4) Å, and volume = 71162.(3) Å3, which were based upon the refinement of the
XYZ-centroids of the reflections. The crystal dataset had a maximum resolution of 0.87
Å, with completeness = 100.0%, R1 = 3.98%, and goodness-of-fit = 1.090. The full refinement of the M4Au12Ag32(p-MBA)30 structure revealed that the 12 gold atoms
resided in the icosahedral inner core of the nanoparticle. The structure consisted of a 12
gold-atom icosahedron surrounded by a 20 silver-atom dodecahedron, forming a 32-atom
excavated-dodecahedral bimetallic core. The metallic core was capped by six equivalent
Ag2(SR)5 mount motifs, which were octahedrally located about the core (see Fig. 2-5).
The measured location of the 12 gold atoms in the icosahedral inner core of the
bimetallic nanoparticle was consistent with the expected locations based on our DFT
calculations and based on previous reports.27 In addition, this result is in agreement with
the known properties of gold and silver. Although gold and silver are isoelectronic and
have almost identical atomic radii, their chemistries and bonding can be quite different.
For example, Au-S bonding is two-coordinate and Ag-S bonding is three-coordinate,25, 28 31
Figure 2-5. Structure of M4Au12Ag32(p-MBA)30. Complete x-ray determined structure shown with A) space-filling view, B) ball and stick view (Au12 core and out-of-plane ligands removed for clarity). The core structure is shown as C) Au12 icosahedral inner shell, which is nested inside of D) an Ag20 decahedral outer shell, together making E) a bimetallic 32-atom excavated dodecahedral core. Other colors: grey - C; red- O (H are not shown). Courtesy of Brian Conn
which makes the bonding of the gold heteroatoms incompatible with the structure of the
protecting mounts.26, 57 It is therefore unlikely that gold atoms would substitute into the
ligand shell without changing the metal atom count.69 Further, gold is known to be more electronegative and more noble than silver, so the gold atoms are expected to assume positions within the structure where they can possess the lowest oxidation states among the metal atoms. Bader analysis of the electron distribution in M4Ag44(p-MBA)30 has
shown that atoms in the inner icosahedral core have an oxidation state of zero,27, 55
27 whereas in M4Au12Ag32(p-MBA)30 those atoms are slightly reduced. The other metal 32
atoms were found to be oxidized, with their oxidation states increasing with distance from the center of the molecule. The x-ray determined location of the gold atoms in the inner core is therefore also consistent with the Bader analysis and the known properties of gold and silver.
The fact that there appears to be a bias toward 6 gold atoms (see Fig. 2-1) indicates that there might be ordering of metal atoms in the incompletely substituted core, possibly driven by symmetry breaking of the icosahedral shell. For example, it is possible that differences in the electronic structure of the metal atoms could lead to chemical inequivalencies in the otherwise identical positions within the inner shell. Alternatively, the random substitution of 6 gold atoms into the inner shell would achieve maximum configurational entropy, which could also explain the bias in ESI-MS measured populations. Further crystallographic or computational studies as a function of gold substitution could shed light on this interesting anomaly.
2.3.4 Thermodynamics of galvanic exchange. The ability to synthesize and analyze distributions of bimetallic nanoparticles affords an opportunity to study in detail their chemistry as a function of composition. In particular, in the case of adding gold heteroatoms to silver nanoparticles, it is possible to study the chemistry of bimetallic nanoparticles over a complete range of possible compositions of isostructural species.
Galvanic exchange reactions are reversible reactions that involve the chemical transformation of monometallic M4Ag44(p-MBA)30 nanoparticles into bimetallic
M4AuxAg44-x(p-MBA)30 nanoparticles by their reaction with species containing gold heteroatoms. The transformation of M4Ag44(p-MBA)30 into M4Au12Ag32(p-MBA)30
33
involves a series of reactions that will enable the detailed study of M4AuxAg44-x(p-
MBA)30 nanoparticle reactivity as a function of composition.
Murray’s group first demonstrated galvanic exchange reactions on molecular
nanoparticles and showed that metal thiolates are more efficient reactants than metal ions
70 for the exchange reactions. The transformation of M4Ag44(p-MBA)30 into
M4Au12Ag32(p-MBA)30 by galvanic exchange can therefore be accomplished as a series
of step-wise reactions between gold-thiolate polymers and M4AuxAg44-x(p-MBA)30
nanoparticles, wherein each sequential reaction involves the substitution of one gold atom
for one silver atom. This series of reactions can be written as follows:
M4AuxAg44-x(p-MBA)30 + (AuSR)n(AgSR)m
M4Aux+1Ag43-x(p-MBA)30 + (AuSR)n-1(AgSR)m+1 (2)
where 0 ≤ x ≤ 12 and where (AuSR)n(AgSR)m and (AuSR)n-1(AgSR)m+1 represent the
metal thiolates before and after the exchange reaction, respectively. Note also that the
galvanic exchange reaction is a reversible reaction (see Fig. 2-6). The fact that galvanic exchange involves a series of reversible reactions as a function of x enables the study of the thermodynamic consequences of changing the composition of a bimetallic nanoparticle.
Galvanic exchange reactions were carried out in a high pH water/DMSO mixture and were incubated for 24 h at room temperature. The composition of the reaction
mixture was again characterized by an input ratio. Here, the input ratio was defined as the
number of gold atoms to the number of silver atoms in the reaction vessel. For example,
for a reaction mixture that contained one gold atom for each silver nanoparticle, the input
34
Figure 2-6. Antigalvanic exchange on M4AuxAg44-x(p-MBA)30 nanoparticles. Gold enriched sample (A) was allowed to react with 6 molar equivalents of Ag(p-MBA) thiolate for 5 days at room temperature and yielded sample (B) with lower average gold loading.
ratio would be 1:44. The color changed during the incubation period from the deep red
color that is characteristic of M4Ag44(p-MBA)30 toward a more orange-hued red color of
M4Au12Ag32(p-MBA)30. The speed of the reaction and the extent of the color change
depended on the concentration of gold thiolates used, i.e. the input ratio. The color
change was barely perceptible for the cases of 1 and 2 Au atoms per nanoparticle,
whereas for 6 and 9 Au atoms the color changed after about an hour to contain some
orange. For the cases of 12-26 Au atoms, the solutions changed within a few minutes to a
color similar to that of M4Au12Ag32(p-MBA)30.
35
ESI-MS analysis of the reaction products showed that the average number of
substituted gold atoms increased with input ratio, as expected (see Fig. 2-7), however it did not match the input ratio. The results of galvanic exchange are different from those of
co-reduction. In the case of co-reduction, the product is mostly controlled by the kinetics
of reduction of silver and gold salts. In the case of a galvanic exchange, thermodynamic
of the reaction play a major role. Substitution was limited to 12 gold heteroatoms, as in the case for the co-reduction reaction.
Once the reaction mixtures reached equilibrium, the concentrations of
M4AuxAg44-x(p-MBA)30 nanoparticles were determined by the equilibrium constant for
each reaction. Assuming that the concentrations and activities are approximately equal,
the equilibrium constant for the reaction producing the M4AuxAg44-x(p-MBA)30 product
can be written as:
Kx/C = [M4AuxAg44-x(p-MBA)30] / [M4Aux-1Ag45-x(p-MBA)30] (3)
where 1 ≤ x ≤ 12 and C = [(AuSR)n-1(AgSR)m+1] / [(AuSR)n(AgSR)m]. All of the
reactions described by equation (2) occurred in the same solution, therefore the gold- and
silver-thiolate concentrations were identical for each reaction and C did not vary with x.
Also, since equation (3) contains a ratio of cluster concentrations, the relative gas-phase
ion abundances from ESI-MS measurements could be used rather than absolute solution-
phase concentrations. In such case, independence of desolvation and ionization
efficiencies on the composition of the nanoparticles was assumed. In addition, gas phase
fragmentations were measured to correct ion abundances of intact (4- charged) species.
36
4- Figure 2-7. ESI-MS spectra showing distribution of AuxAg44-x(p-MBA)30 species synthesized by galvanic exchange using different Au:Ag input ratios. Only species for 0 ≤ x ≤ 12 were observed. Small satellite peaks (see the 6:44 ratio) were identified as species with a chloride replacing a ligand.
37
4- In solution, solvation and counterions likely stabilize the AuxAg44-x(p-MBA)30
ions when they are in solution. Upon desolvation, fragmentation of AuxAg44-x(p-
4- MBA)30 ions likely occurs due to the high charge carried by the small ions, which may lead to a “Coulomb explosion”.26 Fragmentation can occur before, inside, and after the
CID cell. By measuring mass spectra of isolated parent ions (MS/MS), fragmentation in
and after the CID cell can be calculated. Fragmentation in the ion guides (i.e. before the
CID cell) cannot be directly measured and calculated. It can be estimated, however, as a
difference in fragmentation in the MS and MS/MS (with no additional collision energy)
modes of the mass spectrometer.
Samples containing bimetallic species do not allow an unambiguous measurement
of fragmentation in MS mode. These samples contain multiple bimetallic species
therefore it is impossible to attribute fragments to parent ions of any one particular
4- species. On the other hand, Ag44(p-MBA)30 can be synthesized as a single species
product, therefore all fragments can be attributed to parent ions of that one single species.
4- For this reason, measurements were carried out using Ag44(p-MBA)30 to evaluate the
extent of fragmentation.
4- Result obtained using Ag44(p-MBA)30 can shed light on the extent of pre-CID
fragmentation. Sets of samples with different dilutions were analyzed in both modes and
fragmentation was calculated by dividing the sum of the integrated intensities of the large
4- 3- 3- fragments (Ag44(p-MBA)29 , Ag43(p-MBA)28 , and Ag42(p-MBA)27 ) by the sum of the integrated intensities of those fragments and a parent peak. Fragmentation in MS and
MS/MS modes were calculated to be (63.5 ± 3.9) % and (70.2 ± 3.6) %, respectively.
Note that in this case the error bars on the measurements overlap, making their difference 38
statistically insignificant. From these values, it can be concluded that fragmentation in the
ion guides prior to entering the CID cell is below the sensitivity of our measurements.
Therefore, fragmentation coefficients can be calculated using MS/MS measurements for
all thirteen bimetallic species and then used to correct relative gas phase abundances for
measurements in MS mode.
The equilibrium constant is independent of the conditions of the reaction,
therefore Kx was evaluated for each of the galvanic exchange experiments that reached equilibrium using different input ratios. Q-test was used to remove outliers, and from the
remaining values averages and standard deviations were calculated. From these
measurements of Kx, the free energy change for the reaction for the synthesis of the
M4AuxAg44-x(p-MBA)30 product was found using the canonical equation:
ΔGx = – RT ln(Kx) (4)
The results of this analysis show that the reactivity of M4AuxAg44-x(p-MBA)30
nanoparticles is a complex function of the composition of the metal core (see Fig. 2-8).
The evolution of the chemical properties was neither a linear nor a monotonic function of
x, showing that the modification of these properties does not follow a scaling law. This
may indicate that the evolution of the electronic structure of these clusters is also non-
trivial, which implies that molecular design (particularly catalyst design) may be more
complex than expected.
The analysis of the free energies of reaction as a function of x shows that there is
a strong driving force for the incorporation of the first gold atom, however this decreases
markedly for the next three substitutions. It is worth noting that here Gibbs free energies
of the galvanic exchange reactions were measured and should not be confused with Gibbs 39
Figure 2-8. Calculated free energy change, ΔGx, (A) for each galvanic exchange reaction to make AuxAg44-x(p-MBA)30 clusters from Aux-1Ag45-x(p-MBA)30 clusters and (B) for total reaction to make AuxAg44-x(p-MBA)30 from Ag44(p- MBA)30 clusters.
free energies of formation of M4AuxAg44-x(p-MBA)30 species. Most of the substitutions were in fact energetically unfavorable, requiring large excesses of gold-thiolate reactants to make the equilibrium product favored. Addition of the twelfth gold atom was 40
energetically favorable, however, which improves the prospects of synthesizing large
amounts of M4Au12Ag32(p-MBA)30. Interestingly, the addition of a thirteenth gold atom
to form M4Au13Ag31(p-MBA)30 was not observed, therefore ΔG13 could not be evaluated.
The location of the gold atoms substituted by galvanic exchange is not obvious
and therefore must be considered. The energies of substituting gold atoms into the
various chemically equivalent positions within the molecule were evaluated by first
principles calculations (vide supra). It is not immediately clear that the gold atoms will be found in the core, however, since the other 12-fold degenerate substitution sites are also lower in energy compared to the all-silver structure (-0.163 eV for the mount sites and -
0.288 eV for the sites in the dodecahedral outer core). The metal sites within the mounts are more accessible for exchange with external species and could therefore be the preferred sites for substitution, in particular if kinetic barriers existed that prevent them from penetrating into the core. Further, mobilities of metal atoms in ligated molecular nanoparticles are not understood.
The location of the gold heteroatoms in the galvanic exchange product was evaluated by gas-phase fragmentation. The abundances of the small gold-containing
– fragments Au(p-MBA)2 would be expected to correlate with the proximity to the exterior
of the cluster, with the positions in the mounts producing the highest intensities and the
positions in the icosahedral core producing the lowest intensities. Fragmentation of
M4Au12Ag32(p-MBA)30 made by galvanic exchange, without heating or processing, was
compared to that of M4Au12Ag32(p-MBA)30 made by co-reduction and thermal
processing, which was shown to produce species with gold in the icosahedral core (see
Fig. 2-5). Measurements of fragmentation patterns revealed no significant differences in 41
4− Figure 2-9. Spontaneous fragmentation of Au12Ag32(p-MBA)30 (L = p-MBA) nanoparticles produced by (A) co-reduction and (B) galvanic exchange methods. Parent peak is marked by asterisk. gold-containing and silver-containing small fragments (see Fig. 2-9), therefore it can be concluded that in both cases all 12 gold atoms resided in the metal core, confirming our
DFT calculations. This also indicates that metal atom mobility in molecular nanoparticles is high, since gold atoms were able to diffuse both into and out of the cluster. This is also consistent with observations of metal atom rearrangement during cluster reactions.
The determination that galvanic exchange reactions resulted in gold atom substitution into the metal core is rather profound because it shows that a relatively small number of atoms within the inner core of the molecule were able to control the chemistry
42
occurring at the outermost positions of the molecule. The fact that the free energies of
reaction varied significantly as a function of the number of gold atoms in the icosahedral
core specifically illustrates this point, particularly with regard to the rejection of the
thirteenth gold atom from the core (see Fig. 2-7). With sufficient chemical pressure a
thirteenth gold atom may be attached to the cluster but in the form of a SR-Au-SR staple, with the insertion of a Au(p-MBA) into the mount,69 however this product cluster is not
isostructural with the reactant cluster. This again demonstrates the profound effect of a
single metal atom in the icosahedral core entirely changing the chemistry of the ligand
shell.
It has been shown that M4Au12Cu32(SR)30 nanoparticles are isostructural to
M4Au12Ag32(p-MBA)30 nanoparticles and that the incompatibility of the two-coordinate gold-thiolate bonding and the three-coordinate copper-thiolate bonding gives rise to new hybrid capping motifs wherein the bridging thiolate is replaced by a gold staple.69 It would be reasonable to expect, given the same three-coordinate thiolate bonding with silver and copper, that gold thiolates inserted into a silver mount would also form a
hybrid capping motif wherein the bridging thiolate is replaced by a gold staple.69 Figure
2-10 shows the mass spectrum of a sample used for crystallization experiments (vide
supra) before purification. Peaks corresponding to nanoparticles with up to three
transformations of mounts to mount-staple hybrids are observed.
2.3.5 Kinetics of gas-phase fragmentation. Unimolecular fragmentation reactions were also studied in detail as a function of cluster composition using tandem mass spectrometry (MS/MS). Mass spectra as a function of x are shown on Figure 2-11.
In this case the reactions were not reversible and the product distributions were not 43
Figure 2-10. ESI-MS spectrum of a pre-purified crystallization sample. determined by the equilibrium configuration of the system. Rather, it was the kinetic barriers that determined the product distributions. First, the reaction order was determined by measuring the dependence of the gas-phase fragmentation rates on the concentration of clusters. For this purpose, a relative stability (RS) variable was
4- introduced. RS was defined as the ratio of AuxAg44-x(p-MBA)30 integrated parent peak intensity to the sum of integrated peak intensities corresponding to daughter ions, namely,
4- 3- 3- AuxAg44-x(p-MBA)29 , AuxAg42-x(p-MBA)27 , AuxAg43-x(p-MBA)28 , Aux-1Ag44-x(p-
3- MBA)28 and a parent ion. This gives a convenient variable range, i.e. when an ion is completely unstable (no parent, only fragments) RS = 0, and an ion for which no fragmentation was observed would have RS = 1. By defining it this way, we attempt to calculate the fraction of parent ions that survived the path through the CID cell and reached the detector out of those that entered the mass spectrometer (I/I0), which should be equal to the ratio of gas phase concentrations ([A]/[A]0) at time t, when ions pass through the CID cell. We then transform integrated rate laws for 0th (Eq. 5), 1st (Eq. 6)
44
and 2nd (Eq. 7) order reactions and check for the dependence of survival rate as a function of initial concentration, where k is the fragmentation reaction constant.
= 1 (5) [ ] 𝐼𝐼 𝑘𝑘𝑘𝑘 𝐼𝐼0 − 𝐴𝐴 0 = (6) 𝐼𝐼 −𝑘𝑘𝑘𝑘 𝐼𝐼0 𝑒𝑒 = (7) [ ] 𝐼𝐼 1 𝐼𝐼0 1+𝑘𝑘𝑘𝑘 𝐴𝐴 0 The gas-phase fragmentation rate was found to be independent of the cluster concentration, which indicated a first order rate law (Fig. 2-12). The survival rate was measured for two terminal cases in the distribution (x=0 and x=12) as a function of
4- Figure 2-11. MS/MS spectra of AuxAg44-x(p-MBA)30 ions as a function of x.
45
Figure 2-12. Survival rate as a function of nanoparticle concentration for 4- 4- Ag44(p-MBA)30 (squares) and Au12Ag32(p-MBA)30 (circles) ions.
4- concentration. For Ag44(p-MBA)30 some deviation was observed due to the small ion current at low concentration and probabilistic nature of the fragmentation process. Next,
the relative rate of fragmentation was measured as a function of cluster composition, x,
such that the kinetic barriers could be calculated relative to that of M4Ag44(p-MBA)30
(Fig. 2-13). The kinetic method for measuring thermochemical functions developed by
Cooks and co-workers was used as a basis for calculations.71
The kinetics of M4AuxAg44-x(p-MBA)30 fragmentation reactions were also found
to be a complex function of the composition of the metal core (see Fig. 2-13). The
general trends of the reaction barriers and the free energies are different, however, which
is expected since the barriers ought to be dominated by the energetics of intermediate
structures and the costs of rearranging atoms. For example, the addition of the first gold
atom decreased the barrier to fragmentation, effectively destabilizing the molecule in the
gas phase. This surprising kinetic result is opposite to the thermodynamic result. 46
5
4
3
(kJ/mol) 2 0 U
1 - ∆ x
U 0 ∆ -1
-2 0 2 4 6 8 10 12 Au atoms
Figure 2-13. Activation barrier height of unimolecular fragmentation reaction for M4AuxAg44-x(p-MBA)30 relative to M4Ag44(p-MBA)30.
2.3.6 Optical properties. The change in optical properties of the products was also measured as a function of input ratio. The optical absorption spectra evolved smoothly as the gold content increased, from that of M4Ag44(p-MBA)30 to that of a
bimetallic M4AuxAg44-x(p-MBA)30 compound (see Fig. 2-14). Once again this showed
that the electronic structure of the nanoparticles evolved as a function of composition.
Absorption features were found to significantly blue shift and the optical density was
found to decrease as gold was added to the core. In particular, the oscillator strength was
found to decrease most markedly for the two lowest energy transitions (830 nm and 640
nm for M4Ag44(p-MBA)30), which were assigned as being between superatomic
orbitals.55 The atomic d orbitals of Au are known to dampen electronic excitations and
thereby diminish the oscillator strength of optical transitions involving those atoms,
47
therefore the addition of gold atoms to the icosahedral core ought to have the largest effect on transitions between superatomic orbitals in the metal core, as observed. The observed shift of absorption bands at 830 nm and 640 nm towards higher energies is
Figure 2-14. Optical absorption spectra of M4AuxAg44-x(p-MBA)30 species synthesized by galvanic exchange using gold thiolates. The Au:Ag input ratio for each spectrum is given. The bottom spectrum (grey) is M4Au12Ag32(pMBA)30 for reference. attributed to the widening of the HOMO-LUMO gap of M4AuxAg44-x(p-MBA)30 nanoparticles with increasing gold loading.
2.3 Conclusion
The properties of M4AuxAg44-x(p-MBA)30 were studied as a function of x. While thermal stability in the solution phase appears to have a monotonic trend, reactivity and 48
gas-phase stability are complex functions of the number of Au atoms in a nanoparticle.
Gibbs free energy calculations for galvanic exchange reactions show a strong preference for an intermediate number of heteroatoms (about four), likely due to a combination of enthalpic and entropic factors. Gas phase measurements of fragmentation using a kinetic
4- method revealed destabilization of AuxAg44-x(p-MBA)30 at low gold loadings, and
stabilization at higher loadings (five or more Au atoms) when compared to Ag44(p-
4- MBA)30 . This indicates that the behavior of bimetallic systems is more complex than
previously thought.
49
Chapter 3
M3Ag17(TBBT)12 Nanoparticles and Their Structure Prediction*
3.1 Introduction
Silver nanoparticles are of fundamental importance due to their significant
potential impact on fields such as coatings, optics and biomedicine. It is important to make and characterize new molecular nanoparticles to deepen fundamental knowledge.
Since the first reported crystal structure of a silver nanoparticle, M4Ag44(SR)30, two more
silver molecular nanoparticles were structurally characterized via sc-XRD.72-73 Taking
into account differences in structures of the ligands that were used for synthesizing the
new nanoparticles, it is clear that ligands are important variables in syntheses that are
aimed at making new MNPs. Jin and coworkers showed several examples of synthesizing
new gold MNPs using 4-tert-butylbenzenethiol (TBBT) as a ligand by ligand-induced
*This chapter contains adapted material primarily from Wickramasinghe, S.; Atnagulov, A.; Conn, B. E.; Yoon, B.; Barnett, R. N.; Griffith, W. P.; Landman, U.; Bigioni, T. P., M3Ag17(SPh)12 Nanoparticles and Their Structure Prediction. J. Am. Chem. Soc. 2015, 137 (36), 11550-11553 (copyright © American Chemical Society), and partially from Conn, B. E.; Atnagulov, A.; Yoon, B.; Barnett, R. N.; Landman, U.; Bigioni, T. P., Confirmation of a de novo Structure Prediction for an Atomically Precise Monolayer Coated Silver Nanoparticle. Sci. Adv. 2016, 2 (11), e1601609. S.W. performed synthetic work, A.A. performed MS measurements, B.Y., R.N.B and U.L. carried out theoretical studies. All authors contributed to the development of structure prediction methodology.
50
conversion.74-76 This ligand has not been applied for the synthesis of silver MNPs yet. In
this work, a new nanoparticle has been synthesized using TBBT, its formula was
established using ESI-MS, and its structure was predicted and supported by heteroatom
substitution using Au atoms.
3.2 Experimental
3.2.1 Chemicals. Sodium borohydride and N,N-dimethylformamide (DMF) were purchased from Fisher Chemical. Silver nitrate, gold (III) chloride trihydrate, and 4-tert- butylbenzenethiol (TBBT) were purchased from Sigma-Aldrich. All the reagents were used without further purification. Deionized water (18.2 MΩ cm) from a Millipore
Synergy system was used.
3.2.2 Synthesis of M3Ag17(SR)12 and M3AuAg16(SR)12. First, 121 mg of silver
nitrate (0.714 mmol) were dissolved in 7.20 mL DMF and stirred for 5 min. Next, 86 µL
of TBBT (0.500 mmol) were added to the solution, which was stirred for an additional 15
min. The silver-thiolate precursor formed during this time. A 28.60 mL DMF solution
containing 108 mg of NaBH4 (2.85 mmol) was added drop wise to the reaction mixture in
order to reduce the precursor. This reaction was allowed to stir at 1100 rpm for 3 h. After
this time, 4.20 mL of deionized water was added to the reaction in order to increase the
reduction potential of the NaBH4 and consequently the kinetics. This mixture was stirred
for another 2 min before storing in a freezer at -18 ºC for 16 h. After 16 h in the freezer,
the product was separated into a clear yellow supernatant containing the desired product
and a dark precipitate consisting of larger plasmonic nanoparticles. Triphenylphosphine
(TPP, 0.2 mmol, 52.5 mg) was added to the supernatant to prevent the aggregation and/or 51
further growth of M3Ag17(TBBT)12 nanoparticles. The synthesis of M3AuAg16(SR)12 was
carried out in two different ways: (i) with a stoichiometric Au:Ag ratio of 1:16, and (ii)
with a “nonstoichiometric” Au:Ag ratio of 5:16, i.e. a five-fold excess of gold. For these
syntheses, a gold salt was introduced to the starting material. The rest of the procedure is
identical to that of M3Ag17(SR)12 synthesis. For the stoichiometric (1:16) reaction, 114
mg of silver nitrate (0.672 mmol) and 16.5 mg of gold (III) chloride trihydrate (0.042
mmol) were used. For the 5:16 “nonstoichiometric” reaction, 93 mg of silver nitrate
(0.546 mmol) and 66 mg of gold (III) chloride trihydrate (0.168 mmol) were used.
3.2.3 Characterization. All optical absorption spectra were obtained using a
PerkinElmer Lambda 950 spectrophotometer with a standard 1.00 mm path length quartz cuvette. All mass spectra were collected on a Waters Synapt HDMS G1 quadrupole time- of-flight mass spectrometer in negative ion V-mode using a nanospray source with fused silica emitters made in house. Instrument parameters used for data collection were as follows: capillary voltage, 2.0-4.0 kV; sampling cone, 15 V; extraction cone, 4.0 V; nanoflow, 0.1 bar; cone gas, 0 L/h; trap collision energy, 0.5 V; transfer collision energy,
1.0 V; source temperature, 40 °C; desolvation temperature, 120 °C. Calibration was performed externally in the range of 100 ≤ m/z ≤ 4000 using cesium iodide. MassLynx
4.1 software (Waters Corp.) was used for processing spectra. Simulating isotopic patterns
was performed using mMass freeware (copyright Martin Strohalm).77 Samples were
taken directly from the reaction mixture and diluted using neat DMF. The formula of
M3Ag17(TBBT)12 is based upon the requirement that the molecule needs to be neutral in
the solid state, wherein 3 monocationic counterions are needed to balance the charge of
3- + the Ag17(TBBT)12 ion identified by ESI-MS. It is likely that the counterions are Na 52
given their abundance in the synthesis, therefore the formula is expected to be
Na3Ag17(TBBT)12.
3.2.4 Theoretical Methodology. The density functional theory (DFT)
calculations for Bader charge analysis78-79 were performed using the VASP-DFT package
with a plane-wave basis with a kinetic energy cutoff of 400 eV, PAW pseudopotentials,80
and the PW91 generalized gradient approximation (GGA) for the exchange-correlation
potential.78-79 For structure optimization, convergence was achieved for forces smaller
than 0.001 eV/Å. The rational design outlined in the text has been used as the starting
point for the structural relaxation. The calculations of the absorption spectra were carried
out following the time-dependent density-functional theory (TDDFT) method with the
formalism described in references 80-81 implemented in the real-space Octopus code.82-83
These calculations employed the norm-conserving non-local soft Troullier–Martins
pseudopotentials84 (including the valence electrons for the elements in the molecule: Ag
(4d105s1), S (3s2 3p4), C (2s2 2p2), H(1s1), Na (3s1)), using the generalized gradient-
85 corrected PBE exchange–correlation (xc) potential. The Na3Ag17(TBBT)12 structure
(and those of the Au-substituted clusters) were relaxed with the use of the Born-
Oppenheimer density functional theory (BODFT) code,86 employing the above soft pseudopotentials and PBE xc potential. In the subsequent absorption spectra calculations the system was placed in a sphere of radius 21 Å such that the electron vanishes outside of that sphere. The grid spacing was taken as 0.2 Å, which corresponded to a 70 Ry plane-wave kinetic energy cutoff. The calculation involved 898 valence electrons. In the
TDDFT calculations, we have used all states in the interval EF – 4.71 eV to EF +3.10 eV, where the lower limit was chosen to coincide with a minimum in the density of states. 53
This interval included 142 occupied states and 63 unoccupied states, and therefore 8946 electron-hole (occupied-unoccupied) pairs. Convergence was tested by varying the number of states included in the spectral calculations.
3.3 Results and discussion
3.3.1 Synthesis and gas-phase stability of Ag:TBBT NPs. The synthesis of silver molecular nanoparticles with non-aqueous ligands was reported elsewhere and forms a starting point for this work.87 However, single-sized product was not obtained. A
1:2 metal to ligand ratio produced a mixture of the nanoparticles, and the absorbance
spectrum of the product was almost identical to that of M4Ag44(SR)30, except that the
ratio of the peaks at 425 nm and 495 nm was different (see Fig. 3-1). The product of this
reaction was analyzed by electrospray-ionization mass spectrometry (ESI-MS). This
3– revealed the presence of a new silver nanoparticle, an Ag17(TBBT)12 species (see Fig.
3– 3– 3-2), along with Ag44(TBBT)30 and Ag43(TBBT)28 , both of which being derived from
4– 3– the Ag44(TBBT)30 parent ion (vide infra). Such an Ag17(TBBT)12 species was not observed in any other preparation of silver molecular nanoparticles with either aromatic or aliphatic thiolate ligands. Only a small amount of one fragment species was observed,
2– 3– namely Ag17(TBBT)11 , indicating that Ag17(TBBT)12 was quite stable under the
conditions of the measurement. No charge state distribution was observed since the
TBBT ligand is aprotic.
4– It is interesting to note that the Ag44(TBBT)30 ion was not stable in the gas
3– 4– 26, 55 phase, in contrast to both the Ag17(TBBT)12 and Ag44(p-MBA)30 ions. Further, the
4– primary mechanism of charge reduction for the Ag44(TBBT)30 ion was by the loss of 54
Figure 3-1. Absorbance spectrum of the product containing a mixture of Ag:TBBT molecular nanoparticles (solid). Dashed line shows a spectrum of pure M4Ag44(TBBT)30 nanoparticles for comparison. Baseline for offset spectrum is shown.
individual electrons, rather than the loss of anionic fragments, which again is in contrast
4– to the Ag44(p-MBA)30 ion.
Gas phase stability of M3Ag17(TBBT)12 and M4Ag44(TBBT)30 was evaluated by
measuring the spontaneous fragmentation using a quadrupole time-of-flight (qTOF) mass spectrometer (see Fig. 3-3). Ions of interest were isolated by quadrupole and fragmented
at the lowest value of the collision energy (CE), i.e. the ions were fragmenting
spontaneously, without additional energy input. The resulting fragments were then analyzed by the TOF mass analyzer. Despite the semi-quantitative nature of these 55
Figure 3-2. ESI mass spectrum of a mixture of Ag:TBBT molecular nanoparticles.
measurements, due to a difference in detection efficiency for ions of different masses, it
3- is clear that the Ag17(TBBT)12 species was significantly more stable than
4- Ag44(TBBT)30 , which is in agreement with their HOMO-LUMO gap difference (vide
4- infra). In fact, Ag44(TBBT)30 ions are so unstable that they were never observed in the
4- gas phase in contrast to Ag44(p-MBA)30 ions. This indicates different charge reduction
4- mechanisms for the two species. While Ag44(p-MBA)30 undergoes Coulomb explosion
- in order to reduce the negative (-4) charge of the metallic core by releasing a AgL2
3- 4- fragment and turning into Ag43(p-MBA)28 , the Ag44(TBBT)30 ion first ejects an e
- lectron, forming a species with an open electronic shell, and only then releases a AgL2 fragment. This indicates that the cohesive energy of the TBBT ligand shell is greater than
that of the p-MBA ligand shell in the gas phase. This is likely due to the attractive
interactions of the bulky tertiary butyl groups compared with the slightly negatively
charged carboxylic acid groups on the p-MBA ligands.
4- The charge reduction pathway of Ag44(TBBT)30 is presented below:
4- 3- - 2- - - Ag44(TBBT)30 → Ag44(TBBT)30 + e → Ag43(TBBT)28 + Ag(TBBT)2 + e ,
56
Figure 3-3. Spontaneous fragmentation (CE = 0.5) mass spectra of isolated 3- 3- Ag44L30 (A) and Ag17L12 (B) ions shows difference in gas phase stability in agreement with HOMO-LUMO gap difference. Note the Y-axis brake in panel B. (L = TBBT). where the second step is rate determining. This contradicts the electronic shell model, which predicts the opposite case, where an ion with a closed shell would first be destabilized by a loss of an electron, and then rapidly decompose to its fragments. 57
3- Moreover, Ag44(TBBT)30 species, which have a closed ligand shell and incomplete
3- electronic shell, are more abundant in the gas phase than Ag43(TBBT)28 which have a closed electronic shell with 18 electrons, but disrupted ligand shell. Such an inconsistency with the widely-accepted electron shell model might underline an important role of cohesive energy of the ligand shell in stabilizing molecular silver nanoparticles and their gas phase fragments.
On the other hand, gas phase fragmentation of Ag17 nanoparticles is consistent
3- with the notion of electronic shell closures. When isolated Ag17(TBBT)12 ions undergo
spontaneous fragmentation, only species with closed electronic shells are formed. Two
pathways of the fragmentation are associated with a loss of thiolate ions, or a
- 2- 2- Ag(TBBT)2 fragments, and lead to a formation of Ag17(TBBT)11 , or Ag16(TBBT)10
- and Ag15(TBBT)8 species, respectively, all having 8 delocalized electrons. This difference in fragmentation of Ag17 and Ag44 molecular nanoparticles suggests that for a smaller species the large HOMO-LUMO gap plays a determining role in fragmentation patterns, while for larger particles, cohesiveness of the ligand shell is more important, likely due to substantial non-covalent interactions between bulky tert-butyl functional groups.
3.3.2 Synthesis optimization. The product resembling a mixture of Ag:TBBT
molecular nanoparticles was in the supernatant obtained after reaction (Fig. 3-1), and attempts to isolate it by fractional precipitation or column separations failed. So, the synthesis was optimized to minimize the formation of species other than
Na3Ag17(TBBT)12. The metal to ligand ratio was changed from 1:2 to stoichiometric, i.e.
17:12. In addition to this, triphenylphosphine (TPP) was added to protect the particles 58
from growth and destabilization reactions.72 The mass spectrum of the product of the
optimized synthesis, containing almost pure Na3Ag17(TBBT)12, is shown in Figure 3-4.
- Other species observed included adducts of the parent compound along with Ag(TBBT)2
- 88 and Ag5(TBBT)6 , which may have been solution-phase decomposition products. No
4- Ag44(TBBT)30 was observed, consistent with optical measurements (Fig. 3-5). The dark-
yellow supernatant had a single strong absorption peak located at 424 nm that dominated
the optical absorption spectrum, unlike any previously observed, with two small features
on either side and a slowly decaying low-energy tail. The prominent peak at 424 nm is
much narrower (0.18 eV fwhm) and located to the red of a typical plasmon peak
characteristic of a spherical silver nanoparticle.89-90 None of the spectral features
Figure 3-4. Electrospray-ionization mass spectrum of Ag:TBBT nanoparticles, 3- showing Ag17(TBBT)12 along with other minor species. Inset: experimental 3- (black) and simulated (red) isotopic patterns for Ag17L12 , where L = TBBT, with a shift of 0.08 m/z to correct for a 63 ppm mass difference due to external calibration. Reprinted with permission from reference 35 (copyright 2015, American Chemical Society)
59
Figure 3-5. Optical absorption spectrum of Na3Ag17(TBBT)12 nanoparticles in DMF. Inset: spectrum in energy. Reprinted with permission from reference 35 (copyright 2015, American Chemical Society)
characteristic of Na4Ag44(TBBT)30 were observed in the spectrum, which is consistent with the ESI-MS results.
3.3.3 Structure prediction. X-ray data are not always available for structure
determination; therefore, structure prediction methods are needed. The prediction of
structures of gold and silver molecular nanoparticles presents one of the foremost
challenges in molecular nanoparticle science, however, and has yet to yield a definite
successful example. The small size of M3Ag17(TBBT)12 as well as past lessons learned
provide an opportunity to begin the formulation of guiding principles for structure
prediction and to attempt the prediction of a verifiable structure of this molecular
60
nanoparticle. First, it is well-known that very small metal particles tend to assume low- energy icosahedral structures.91-92 Gold and silver molecular nanoparticles share this tendency because the cores of many known structures contain icosahedra, with few exceptions; therefore, it is reasonable to begin a structural model with an icosahedral
core. Second, it is also well-known that the presence of a central atom in the icosahedral
core affects primarily the superatomic S orbitals because of their nonzero amplitude at
the origin, i.e., the center of the particle.93-95 For example, an 18-electron spherical core
will have 1S2, 1P6, and 1D10 occupied orbitals and a 2S orbital as the lowest unoccupied
molecular orbital (LUMO);33 therefore, an empty 12-atom icosahedron would be favored because it would raise the energy of the 2S LUMO and thereby increase the energy gap.
26-27 32 This is the case for M4Ag44(SPh)30. Formal counting for M3Ag17(TBBT)12
nanoparticles gives eight delocalized electrons, which are expected to fill the 1S2 and 1P6
orbitals33 so that the highest occupied molecular orbital (HOMO) is 1P and the LUMO is
1D. This is indeed found from our density functional theory (DFT) electronic structure
calculations (vide infra); therefore, there is no electronic advantage to an empty 12-atom
icosahedral core. This is generally the case for an eight-electron core, such as
96-97 MAu25(SR)18. In contrast, there is an energetic advantage to a 13-atom (atom-
centered) icosahedral core because of the coordination of the central atom. We therefore
predict Na3Ag17(TBBT)12 to have a 13-atom icosahedral core, as shown in Figure 3-6(a).
Next, we consider the ligand shell. In the case of gold molecular nanoparticles, the
capping motif has consistently been shown to be monomer and dimer staples.21, 96-98
These can be thought of as fragments of the linear gold thiolate polymer, p-(AuSR)n. For
silver, the capping motif for M4Ag44(SPh)30 nanoparticles was carefully analyzed and has 61
Figure 3-6. Proposed structure for M3Ag17(TBBT)12 nanoparticles, constructed and relaxed with DFT calculations. (a) The structure consists of an icosahedral Ag13 core (red) capped with four tetrahedrally located Ag atoms (green). (b) Twelve sulfur atoms (yellow) surround the silver core, with three S atoms forming an equilateral triangle around each tetrahedrally located Ag atom, to form a distorted icosahedron (yellow lines); E1, E2, and E3 are different edge lengths. (c) Isolated view of a Ag(TBBT)3 monomer mount structure; the S atoms form an equilateral triangle (yellow lines). Carbon atoms are gray, and hydrogen atoms are blue. (d) Isolated view of the Ag2(p-MBA)5 dimer mount structure found on the Na4Ag44(p-MBA)30 molecule. The S atoms form nearly equilateral triangles (yellow lines); oxygen atoms are in orange. (e) View of the M3Ag17(TBBT)12 structure down the threefold axis, showing slight rotation between the mount and the underlying icosahedral core. (f) View showing face- to-face interactions of the phenyl rings of ligands on neighboring mounts, leading to an overall octahedral arrangement of ligand bundles. Reprinted with permission from reference 35 (copyright 2015, American Chemical Society) 62
26 been shown to be the aforementioned Ag2(SPh)5 mount. This is a 3D structure and is
therefore distinct from the linear gold thiolate polymer. The fact that Ag2(SPh)5 mounts
were observed instead of staples can be understood on the basis of the topological
difference between the bonding of gold and silver in metal thiolates, which are two- and
three-coordinate, respectively.25 Using this example, the 4 Ag atoms and 12 ligands that
remain after accounting for the Ag13 core can be grouped into 4 trigonal quasi-planar
Ag(SPh)3 mounts, as shown in Figure 3-6(c). These can be thought of as fragments of the
28 2D silver-thiolate polymer. In fact, the Ag(SPh)3 mount could be considered to be the
primitive capping unit for silver thiolate ligands because Ag2(SPh)5 mounts can be
constructed by fusing two Ag(SPh)3 mounts. In Figure 3-6(d), two of the newly proposed
Ag(SPh)3 mounts are joined at the apex S atom with the elimination of a single thiolate.
21, 96-98 In analogy to monomer and dimer staples for gold thiolate ligands, the Ag(SPh)3
and Ag2(SPh)5 capping units can be thought of as monomer and dimer mounts. Because
icosahedra contain the tetrahedral symmetry group, it is possible to arrange the four
trigonal planar Ag(SPh)3 mounts symmetrically around the Ag13 core, as shown in Figure
3-6(e). Structural optimization of the molecule with the use of first principles relaxation
revealed that interactions between ligands on neighboring mounts lead to ligand pair
bundling,99 resulting in a ligand shell structure with an overall octahedral arrangement
(Fig. 3-6(f)). Here, the ligands tilt in order to maximize the interligand interaction,
thereby facilitating face-to-face interactions between the rings with minimal interference
from the tert-butyl groups. This ligand pair bundling and the symmetry that it confers on
the ligand shell are likely to assist in the crystallization of these molecular nanoparticles
and influence the properties of the resulting superlattice.100 63
3.3.4 DFT analysis of the predicted structure. The stability of the proposed
structure is strongly supported by the results of our DFT calculations, which reveal a
density of states (DOS) with a large HOMO-LUMO energy gap Egap = 1.77 eV (Figure 3-
7(a)). Such a large predicted gap is consistent with experimental ESI-MS measurements
of marked gas-phase stability (vide supra). Furthermore, the projection of the wave
functions onto their angular momenta components shows the expected superatom shell
structure with occupied 1S2 and HOMO 1P6 delocalized orbitals and superatom LUMO
1D orbitals (see wave function portraits in Figure 3-7(b)). The calculated time-dependent
DFT (TD-DFT) optical absorption spectrum is in good correspondence with the measured one, lending further support to the proposed structural model (Figure 3-7(c)).
The experimental spectrum was measured in DMF, and the theoretical spectrum was calculated in vacuum. Thus, red shift scaling was applied to the calculated spectrum to simulate a solvatochromic effect so that the main prominent absorption feature near 400 nm matched. The observed absorption features for M3Ag17(TBBT)12 are at (A) 424 nm
(2.92 eV) and (B) at 280 nm (4.43 eV). In the calculated spectrum for Na3Ag17(TBBT)12,
the main absorption features are at (A) 396 nm (3.13 eV) and (B) at 256 nm (4.85 eV).
Feature A at 396 nm (3.13 eV) originates from (i) occupied states at -2.33 eV lying mostly on the phenyl rings, excited to the LUMO (0.89 eV) and LUMO+1 1D superatom states on the metal core, (ii) occupied states on the sulfur and silver (d states) atoms at -
1.97 eV, excited to the 1D superatom states, and (iii) the HOMO superatom 1P state excited to unoccupied states at 2.30 eV on the phenyl ring. For feature B, the calculated peak occurs at 256 nm (4.85 eV), and it originates from (i) phenyl p-states at -2.31 eV, excited to p* states at 2.51 eV hybridized in part with sulfur states, (ii) d-band Ag and 64
Figure 3-7. Electronic properties. (a) Projected DOS calculated for the relaxed Na3Ag17(TBBT)12 structure. The color-coded angular momenta are given on the right. (b) Representative wave function portraits corresponding to the indicated energies are given at the bottom. (Blue and purple signify di erent signs.) The nodal structures for the delocalized orbitals with eigenenergies −6.19, −1.00, and 0.89 eV correspond to 1S, 1P (HOMO) and 1D (LUMO) superatomff states. The Fermi energy, at EF = 0.0 eV, is indicated by the dashed line. (c) Measured (dark and light-blue lines) and TD-DFT-calculated (red and dotted black lines) optical absorption spectra of Na3Ag17(TBBT)12 nanoparticles and calculated spectrum for Na3Ag17(SH)12 (pink) plotted vs wavelength and energy (inset). The dotted black line is the as-calculated spectrum, and the red line is obtained by scaling the as-calculated spectrum. Reprinted with permission from reference 35 (copyright 2015, American Chemical Society)
sulfur states at -1.97 eV, excited to phenyl and ligand states at 2.81 eV, and (iii) d-band
metal states at -3.7 to -3.9 eV, excited to the unoccupied 1D superatom states near 1.01
eV. The calculated spectrum for Na3Ag17(SH)12 (pink in Figure 3-7(c)) illustrates enhancement of the main observed spectral features (peaks A and B) by suppressing contributions from transitions involving ligand states (see the region between 300 to 400
nm). The latter are expected to be more susceptible to smearing of spectral features
because of solvent effects and fluctuations, as evidenced in the solution-phase spectra.
65
3.3.5 Heteroatom substitution. The structure of M3Ag17(TBBT)12 was probed by
the heteroatom substitution method using Au atoms (see Fig. 3-8). Previous reports
showed that nobility of the heteroatom metal dictates the sites of substitution. When less noble silver was introduced to gold nanoparticles with 13-atom icosahedral cores, both
58-59 MAgxAu25-x(SR)30 and AgxAu38-x(SR)24 crystal structures showed 100% site
occupancy of the central atom position by Au. DFT calculations using our model
structure predicted a strong preference for a single Au atom substitution (0.89 eV
stabilization for an optimal geometry with the central Ag atom substituted), accompanied
by a gap of Egap = 1.81 eV, compared to 1.83 eV for a two-atom Au substitution and 1.77
eV for the all-Ag structure, which was confirmed by experiment. Namely, when a
Figure 3-8. ESI mass spectra of the products obtained by co-reduction synthesis using 1:16 (A) and 5:16 (B) Au:Ag molar ratios. Reprinted with permission from reference 35 (copyright 2015, American Chemical Society)
66
stoichiometric 1:16 Au/Ag input ratio was used, Na3AuAg16(TBBT)12 was produced with
only a minor component of Na3Au2Ag15(TBBT)12; no Na3Ag17(TBBT)12 was detected.
Figure 3-8 shows mass spectra for the stoichiometric (1:16) and five-fold excess (5:16
Au/Ag input ratio) syntheses. In the latter case, excess gold formed larger plasmonic Au
nanoparticles. Absorbance spectra of both products are shown in Figure 3-9. The
spectrum of M3AuAg16(TBBT)12 was similar in nature to that of M3Ag17(SR)12, however
the main absorption peak was shifted to 408 nm. When the spectrum of the stoichiometric product is subtracted from the spectrum of the non-stoichiometric product using some scaling factor, the resulting spectrum shows only one broad absorption band with a peak at 515 nm characteristic for spherical plasmonic gold nanoparticles.
Figure 3-9. Optical absorption spectra of M3AuAg16(TBBT)12 nanoparticles in DMF, with 1:16 (blue line) and 5:16 (red line) input ratios. The difference (dotted line) is also shown. Reprinted with permission from reference 35 (copyright 2015, American Chemical Society)
67
3.3.6 Confirmation of the predicted structure. Shortly after developing the
prediction of the M3Ag17(TBBT)12 structure, isolation and crystallization of its
heteroatom substituted analog (TOA)3AuAg16(TBBT)12 was achieved. The higher
stability of the bimetallic particles was a key difference in their crystallization. Crystals
suitable for sc-XRD measurements were grown and analyzed, and the structure of
3- (TOA)3AuAg16(TBBT)12 was determined. The measured structure of AuAg16(TBBT)12
3- was found to be same as that predicted for Ag17(TBBT)12 , with the obvious exception of
3- the different central atom (Ag in the case of Ag17(TBBT)12 and Au in the case of
3- AuAg16(TBBT)12 ). The positions of all atoms in the inorganic part of the molecule (i.e.
metal and sulfur atoms) were found to be the same in both the predicted and measured
structures, validating the structure prediction as well as the structure prediction
methodology.
A hierarchical buildup (aufbau) of the molecule, from the inner core going
outward, illustrates the high degree of similarity between the predicted and x-ray–
determined structures, as shown in Figure 3-10 (B to G). The structure of
(TOA)3AuAg16(TBBT)12 has a 13-atom icosahedral core with a central Au atom surrounded by 12 Ag atoms. The 13-atom metallic core is capped by four silver atoms
forming a regular tetrahedron (Fig. 3-10, B and C). Each of these Ag atoms is the center
of a quasiplanar Ag(SR)3 capping mount, where SR is a thiol ligand (here, TBBT). The
predicted and measured metal cores and capping motifs are depicted in Figure 3-10 (D and E, respectively), showing only the first carbon atom (bonded directly to the S atom).
The striking similarity between the predicted and measured structures is evident. The sole
68
Figure 3-10. X-ray–determined structure and comparisons with the theoretical de novo prediction. (A) Relaxed X-ray–determined structure for (TOA)3AuAg16(TBBT)12. Color scheme: purple, gold; orange, silver in the M13 core; green, silver in the Ag(TBBT)3 mounts; yellow, sulfur; grey, carbon; light grey, hydrogen. The TOA+ counterions were faded for clarity, and the octyl carbon chains and the hydrogen atoms are represented by light pink and light gray spheres, respectively. (B and C) The predicted and x-ray–determined structures of the AuAg12 icosahedral core (B) and the four outer Ag atoms [green spheres in (C)] coincide. Below, the predicted structure is shown on the left, and the measured one is shown on the right. (D and E) The structures with the sulfur atoms (yellow) and the quasi-planar mounts. Each S atom is shown as bonded to the nearest carbon atom (dark and light blue spheres) of the thiol ligand (TBBT), with the S–C bond direction predicted by first-principles simulations of the structure (D), as well as the x-ray–determined one (E). In (D), the S–C bonds are all oriented in a clockwise sense, and in (E), they are oriented in a clockwise sense for one of the mounts (see white arrow) and in an anticlockwise sense for the other three mounts (light blue); see also insets. (F) View showing paired ligands on neighboring mounts; in (G), partial bundle ordering is found. Three pair-bundled TBBT ligands (in red, pink, and green), a single triple- bundled one (in blue), and three unpaired ligands (in gray) are identified. Adapted from reference 57.
69
variance between the predicted and measured structures is in the conformational sense
(angular orientation) of the ligands, which are anchored at the mounts.
3.4 Conclusion
We have presented experimental results showing the existence of
M3Ag17(TBBT)12. The structure of this new molecular silver nanoparticle is predicted to consist of a Ag13 icosahedral core that is surrounded by a tetrahedral arrangement of newly found Ag(SPh)3 planar mounts. A rational strategy for predicting the structure of this molecule and calculations that support the structural model were discussed. This work presents an important step toward the goal of developing accurate predictive structural models in order to relieve the crystallization bottleneck that currently limits the structural data available for silver and other metals. The predicted structure of
M3Ag17(TBBT)12 was later confirmed by sc-XRD measurements of its bimetallic analog,
(TOA)3AuAg16(TBBT)12.
70
Chapter 4
Ligands as Structure Directing Synthons
4.1 Introduction
The canonical thinking about the structure and stability of noble metal nanoparticles is that the core determines the overall structure and stability of the molecule, i.e. once the best core structure is formed the ligand shell simply passivates that core.101-104 This implies that the structure of the ligand shell is determined by the structure of the metal core. For example, Au25(SR)18 is a particularly stable nanoparticle that has been synthesized with a wide variety of ligands, including aromatic,96-97, 105-109 aliphatic,18, 34, 44, 107, 110-115 and biological.116-119 Further, it has been shown that the ligands
120-132 on Au25(SR)18 can be exchanged without changing the (core) structure.
Ligands are known to affect the product of a nanoparticle synthesis however, typically by biasing the mass distribution of the synthesis. For example, the mass distribution can be shifted to larger sizes by increasing the metal-to-ligand ratio,133-135 or decreased by choosing ligand properties in such a way as to limit growth based on the solubility of the ligand or based on steric repulsions between bulky ligands.136 For example, glutathione was successfully used to bias the mass distribution toward smaller particle sizes compared to the straight-chain thiols used in the Brust-Schiffrin method.137- 71
138 More subtle ligand effects have also been observed. For example, variations in the
structure of a ligand, such as the position of aromatic ring substituents, were found to
lead to different thermodynamic products. In this work, para-, meta-, and ortho- methylbenzenethiol were found to form Au130(p-MBT)50, Au104(m-MBT)41, and Au40(o-
139 MBT)24, respectively.
More recently, it has been shown that nanoparticle structures can be changed by
post-synthesis exchanging of the ligands, suggesting that ligands play a more significant role in determining the structure of a nanoparticle. Jin and coworkers have developed synthetic routes to obtain different nanoparticles by high-temperature ligand exchange.
74 For example, transformations included Au38(PET)24 to Au36(TBBT)24, Au25(PET)18 to
75 48 76 Au28(TBBT)20, Au144(PET)60 to Au99(SPh)42 and Au133(SPh-t-Bu)52. Bakr and
coworkers showed that ligand-induced transformation of silver nanoparticles can be performed on thiolate-protected silver nanoparticles too. In particular, they have been
140 able to switch between M4Ag44(SPhF)30 and Ag25(SPhMe2)18 nanoparticles. In their
other work, ligand-induced conversion of Ag35(SG)18 into 5 different products was
presented.141
Here, we show that the effects of ligands on nanoparticle structure and synthesis
are far more profound than previously shown. We show that ligand properties do not
simply influence but rather they determine the sizes and structures produced by
nanoparticle syntheses. We have found that there are two different classes of ligands that
select for two different families of nanoparticles. The classes of ligands can be
characterized based on the nature of the alpha carbon atom, which we define as the
carbon atom that is directly attached to the thiol group on the ligand. We found that 72
families of nanoparticles that were produced using ligands with aliphatic alpha carbons
were orthogonal to families produced using ligands with aromatic alpha carbons, whether
by direct synthesis or by post-synthetic ligand exchange reaction, in effect acting as
structure directing synthons.
4.2 Experimental
4.2.1 Chemicals. Silver nitrate (AgNO3, ), 4-mercaptobenzoic acid (p-MBA, technical grade, 90%), glutathione reduced (GSH, 99%), 4-tert-butylbenzenethiol (TBBT,
97%), benzenethiol (BT, food grade, ≥98%), cyclohexanethiol (CHT, 97%), 4-
(mercaptomethyl)benzoic acid (p-MMBA, ), 4-tert-butylbenzyl mercaptan (TBBM,
98%), benzyl mercaptan (BM, food grade, 99%), 2-phenylethanethiol (PET, 98%), N,N- dimethylformamide (DMF, 99%), dimethyl sulfoxide (DMSO, 99%), cesium hydroxide
(CsOH, 50% w/w solution), citric acid (ACS reagent, ≥99.5%), toluene (anhydrous,
99.8%) were purchased from Sigma Aldrich. Glycerol, t-pentyl alcohol, 2-propanol, tris base, glycine, acrylamide, bis-acrylamide were purchased from Fisher Scientific.
N,N,N',N'-tetramethylethylenediamine (TEMED, 99%), Ammonium persulfate (>98%) were bought from GE Healthcare. Ethanol (190 proof) from Decon Labs and sodium borohydride (>98%) from Acros Organics were used.
4.2.2 Syntheses of Ag:p-MBA and Ag:p-MMBA nanoparticles. A method used to synthesize silver nanoparticles with p-MBA and p-MMBA was reported elsewhere.26
Silver nitrate (0.0121 g, 0.0714 mmol) and the ligand (0.1285 mmol) were dissolved in a solution of water (21 mL) and DMSO (12 mL). The mixture was stirred to produce the insoluble silver-thiolate precursor. Then, the pH of the reaction mixture was increased up 73
to pH 12-13 (confirmed by pH paper) using a 60% (w/w) aqueous CsOH solution. At this point, the insoluble precursor was dissolved forming a clear, yellow solution. After that, the solubilized precursor was reduced with 9 mL of aqueous solution of NaBH4 (0.0162g,
0.4284 mmol). It is important to add the reducing reagent in three equal aliquots at 20 min intervals. After completing the addition of NaBH4 solution, the solution was stirred
for another hour to complete the reaction. After one hour, the solution was centrifuged
and the precipitate discarded. Finally, the product was precipitated with excess DMF and
collected after centrifugation. The product obtained at this point is required to be
protonated with citric acid as the carboxylic acid groups of the ligands were deprotonated
during the pH adjustment. Therefore, the obtained solid product was dispersed in 30 mL
of DMF and approximately 1 g of citric acid was added. This solution was agitated until
citric acid dissolved in the DMF solution. Then, the nanoparticles were precipitated with
30 mL of toluene. This protonation step was carried out three times to ensure complete
protonation of the carboxylic acid groups.
4.2.3 Syntheses of Ag nanoparticles with BT, TBBT, CHT, BM, TBBM, and
PET. Synthesis of silver nanoparticles with water insoluble ligands was reported
previously.87 First, silver nitrate (0.0121 g, 0.0714 mmol) was dissolved in 7.20 mL DMF
and stirred for 5 min. Then the ligand (0.1428 mmol) was added to the solution and
stirring was continued for another 15 min. At this point, the silver-thiolate precursor has
formed. A 28.60 mL DMF solution of NaBH4 (0.0108 g, 0.2856 mmol) was added
dropwise to reduce the precursor. The reaction was stirred at 1100 rpm for 3 h. After 3 h,
4.20 mL of deionized water were added to the reaction and it was stirred for another 2
min. Finally, the solution was incubated in the freezer at -18 °C for 2 days to complete 74
the reaction. The procedure was repeated for all ligands except for TBBM and BM,
which were unstable under ambient conditions, therefore corresponding syntheses were
carried out under an inert atmosphere (Ar gas was used).
4.2.4 Synthesis of Ag:SG nanoparticles. Ag:SG nanoparticles were synthesized
19 by a method reported by Kumar et al . Briefly, 85.0 mg (0.500 mmol) of AgNO3 were dissolved in 50 mL of water. To this solution 620.0 mg (2.02 mmol) of GSH were added and the mixture was immersed into ice bath for 30 min. Then, freshly prepared NaBH4
solution (10 mL, 0.5 M) was added dropwise. After mixing for 1 h, clusters were
precipitated by ice cold isopropanol, and then washed 3 times with ethanol. The product
was dried under vacuum to obtain a dry powder.
4.2.5 Ligand exchange on M4Ag44(p-MBA)30 using GSH. The solid sample of
unprotonated M4Ag44(p-MBA)30 was dissolved in a 10.0 mL solution of 10% (v/v) glycerol in water. The pH of the solution was adjusted to 12 with a solution of cesium hydroxide. The concentration of M4Ag44(p-MBA)30 in the resulting solution was determined using previously reported molar absorptivity55 in order to control molar ratios
of GSH to p-MBA, which were 0.5, 1, 2.5, and 5.0 The required amounts of solid GSH
were weighed and added to the solution of M4Ag44(p-MBA)30. Each solution was then
vortexed vigorously for 5 min, and the absorbance spectra for each sample were
measured.
4.2.6 Ligand exchange on Ag:SG NPs using p-MBA. Ligand exchange was
performed in a 7:4 (v/v) water:DMSO mixture at pH 12 with a 5:1 molar ratio of
incoming to leaving thiol. In previously reported silver MNPs protected by monodentate
thiols, M3Ag17(SR)12, MAg25(SR)18, Ag32(SR)19, and M4Ag44(SR)30, metal to ligand ratio 75
varies from 1.39 to 1.68. For simplicity, to calculate the amount of ligand in Ag:SG
particles, an assumption was made that the average metal to ligand ratio is 3:2. A sample
of p-MBA weighing 81.8 mg (0.53 mmol) was dissolved in 10 mL of the prepared
solvent, and CsOH solution was added dropwise until the ligand dissolved completely
and produced a clear colorless solution. To this solution, 49.7 mg of solid Ag:SG
nanoparticles were added and the mixture was vortexed and sonicated to dissolve the
nanoparticles. Then, the solution was left overnight under ambient conditions.
4.2.7 Partial ligand exchange on M4Ag44(p-MBA)30 using GSH. Partial substitution of p-MBA by GSH on M4Ag44(p-MBA)30 was carried out in a 9:1 (v/v)
DMF:water mixture. The concentration of the DMF solution of M4Ag44(p-MBA)30 was
determined spectrophotometrically and was 29.5 μM. A stock solution of GSH was
prepared with a concentration of 10.81 mg/mL using ultrasonically degassed water. To
conduct a series of experiments with different incoming to leaving thiol ratios, different
amounts of the GSH stock solution were diluted to a volume of 30 μL using deionized
water. To each of these solutions, 270 μL of the M4Ag44(p-MBA)30 stock solution were
added. The resulting mixtures were vortexed vigorously, incubated at room temperature for 30 min, centrifuged at 16873 RCF and then analyzed by ESI mass spectrometry.
4.2.8 Characterization. All optical absorption spectra were obtained using a
PerkinElmer Lambda 950 spectrophotometer using quartz cuvettes. Polyacrylamide gel
electrophoresis (PAGE) separations of Ag:SG clusters obtained via ligand exchange were
conducted on a Thermo Scientific vertical electrophoresis system Owl™ P10DS
following a previously reported method19. Gels with 30% acrylamide monomer and 4%
of bisacrylamide crosslinker were used, and dimensions were 20x20x1.5 mm. For NMR 76
measurements, protonated M4Ag44(p-MBA)30 nanoparticles were cleaned of residual
acetic acid. To clean the nanoparticles, they were redissolved in neat DMF, precipitated
with toluene, and then washed with toluene to remove the residual DMF. The clean
precipitate was dried under flowing nitrogen for approximately 6 h to remove the toluene.
A DMF-d7 solution was prepared from the dried nanoparticles with a concentration of 5
mg/mL. 1H-NMR spectra were collected on a Bruker Avance III 600 MHz spectrometer.
MS data were collected on a Synapt HDMS G1 quadrupole-time-of-flight ion mobility mass spectrometer equipped with nanoflow electrospray ionization source (Waters Corp.)
Emitters were made from fused silica capillary in house. Mass spectra were collected in negative V-mode using the following optimal parameters: capillary voltage, 2.0 – 4.0 kV; sampling cone, 15 V; extraction cone, 4.0 V; cone gas, 0 L/h; nanoflow, 0.1 bar; trap collision energy, 0.5 V; transfer collision energy, 1.0 V; source temperature, 40 °C; desolvation temperature, 120 °C. External calibration was performed in negative mode using cesium iodide in the range of 100 ≤ m/z ≤ 4500. Data sets were collected and processed using MassLynx 4.1 software (Waters Corp.). For analyses of products of direct syntheses sample preparation was carried out by taking an aliquot from the reaction mixture, centrifuging out any solid particles and diluting the supernatant with the solvent used for the synthesis to the optimal concentration. Ligand exchange samples were injected into the mass spectrometer directly without additional manipulations.
4.3 Results and Discussion
4.3.1 Transformation of M4Ag44(p-MBA)30 via ligand exchange. The synthesis
of M4Ag44(SR)30 with p-MBA has been shown to be exceptionally efficient and selective, 77
and many examples of M4Ag44(SR)30 have already been synthesized with a variety of thiolate ligands.26-27, 87, 142-143 It would be advantageous, however, if one could combine
the bio-compatibility of ligands such as glutathione, captopril, and cysteine with the high- yield, single-species synthesis of M4Ag44(SR)30. To date, however, a species resembling
M4Ag44(SR)30 has never been identified in the products of reactions involving the above-
mentioned bio-compatible ligands.19, 144-145 While it has not been possible to synthesize
M4Ag44(SG)30 directly, it might be possible that a ligand exchange reaction could be an
alternative route to obtaining M4Ag44(SG)30.
To test whether M4Ag44(SG)30 can be obtained by such a reaction, an aqueous solution of Na4Ag44(p-MBA)30 was prepared and a five-fold excess of glutathione was
added, i.e. there were 5 glutathione molecules added for each p-MBA ligand on a nanoparticle. This solution was incubated for 5 min at room temperature before the spectrum was recorded. The characteristic features of the M4Ag44(SR)30 spectrum were
no longer present after the exchange reaction (see Fig. 4-1), indicating that the exchange
reaction to obtain M4Ag44(SG)30 was not successful. Exchange of glutathione for p-MBA
ligands was found to destabilize the Na4Ag44(p-MBA)30 molecules, transforming them
into other materials. It should be noted that this ligand exchange reaction was quite rapid
(approx. 5 min). Similar reactions with gold nanoparticles typically require longer
incubation times and elevated temperatures.
The identity of the ligand-exchanged products was determined by polyacrylamide
gel electrophoresis (PAGE). The PAGE results showed that the end products resembled a
mixture of glutathione-protected silver nanoparticles from a previously known family
(see Fig. 4-1, inset).19 None of the spectra of these product species matched 78
Figure 4-1. Optical absorption spectra of M4Ag44(p-MBA)30 nanoparticles (dashed) and the product of the glutathione (GSH) ligand exchange reaction (solid) using a 5:1 GSH:p-MBA ratio in a 9:1 water:glycerol mixture. Inset: PAGE separation comparing the ligand exchange products to the members of the previously reported family of Ag:SG nanoparticles.
M4Ag44(SR)30, which indicated that the exchange reaction not only destabilized the
M4Ag44(SR)30 nanoparticles but also transformed their metal cores into other known molecular nanoparticle species. Despite the fact that M4Ag44(p-MBA)30 is a notably stable nanoparticle26, it was easily transformed by a brief ligand exchange reaction at room temperature. This indicates that ligand-ligand interactions make a significant contribution to the cohesive energy of M4Ag44(p-MBA)30 and therefore may play a large role in determining its structure and stability.
4.3.2 Effect of ligand structure on the product of synthesis. To better understand the relationship between metal core structure and ligand properties, ligand structural features were systematically varied, e.g. bulkiness, aliphatic nature, and 79
aromaticity (see Fig. 4-2). Three ligands, p-mercaptobenzoic acid (p-MBA), 4-tert- butylbenzenethiol (TBBT), and benzenethiol (BT), served as reference points for structural modification since derivatives of each were available with methylene groups between the thiol group and phenyl ring (see Fig. 4-2), in order to study the effects of alkyl character. In the case of BT, 2-phenylethanethiol (PET) is a common ligand with two methylene groups between the thiol group and the phenyl ring, such that the S-C and
Ph-C bonds are parallel. The effect of aromaticity could also be tested by comparing BT with cyclohexanethiol (CHT). The structural relationships between these ligands are shown in Fig. 4-2.
It was found that products of syntheses that used p-MBA, TBBT, and BT as
ligands contained clear evidence of M4Ag44(SR)30 nanoparticles in their spectra (see Fig.
Figure 4-2. Structures of ligands used in this study: p-MBA – p- mercaptobenzoic acid; TBBT – 4-tert-butylbenzylthiol; BT – benzenethiol; CHT – cyclohexanethiol; p-MMBA – p-(mercaptomethyl) benzoic acid; TBBM – 4-tert-butylbenzyl mercaptan; BM – benzyl mercaptan; PET – 2- phenylethanethiol. 80
4-3). In the case of TBBT, the steric bulk of the ligand was also found to produce a
35, 57 second, smaller species, M3Ag17(TBBT)12, which can presumably better
accommodate the bulky ligand. The other nanoparticle products (i.e. p-MBA and BT)
were found to contain only M4Ag44(SR)30, as verified by ESI-MS analysis (see Fig. 4-4).
These results are consistent with previous results wherein M4Ag44(SR)30 could be
synthesized with a variety of substituents on a benzenethiol ligand,26-27, 87, 142 with the
exception of the 2,4-dimethyl-benzenethiol (SPhMe2) ligand, which produced
73 MAg25(SPhMe2)18 nanoparticles.
Next, the p-MMBA, TBBM, and BM ligands were studied. These ligands were
identical to the p-MBA, TBBT, and BT ligands, respectively, except for the addition of a
Figure 4-3. Optical absorption spectra of M4Ag44(SR)30 nanoparticles in DMF, where SR is TBBT (blue), BT (red), and p-MBA (black). Inset: spectra of Ag nanoparticle product with other ligands: TBBM (blue), p-MMBA (red), PET (magenta), and CHT (black). 81
Figure 4-4. ESI mass spectra of M4Ag44(SR)30 nanoparticles in DMF, synthesized using p-MBA (A), BT (B), and TBBT (C).
methylene group between the thiol and aromatic ring, which imparted a mixed aromatic and aliphatic character. This small modification to the ligand structures was found to entirely change the product. Spectra of the products no longer contained any indication of the formation of Ag44(SR)30 molecules (see Fig. 4-3, inset); ESI-MS analyses were consistent with this observation (see Fig. 4-5). The products instead resembled mixtures of aliphatic silver nanoparticles, not unlike the family of silver glutathionate
19, 145 nanoparticles. These results indicated that the M4Ag44(SR)30 nanoparticle was not stable in solution with ligands that have mixed aromatic and aliphatic character.
82
Figure 4-5. ESI mass spectra of nanoparticles synthesized using CHT (A), p- 4- MMBA (B), TBBM (C) and PET (D). Ag44(SR)30 was not detected in any of 4- the four samples. Arrows show calculated positions of Ag44(SR)30 for every ligand.
To ensure that direct syntheses were not biased by any other factors other than
ligand structure, a softer synthetic method of synthesis was developed, where ligand
exchange was conducted with Ag44(p-MBA)30 as a starting material. All ligands from
Figure 4-2 were used, except p-MMBA, in 5-fold ratio to the initial ligand. Results of
this experiment are in good agreement with direct syntheses (see Fig. 4-6). Features
distinguishing M4Ag44(SR)30 nanoparticles were preserved in case of BT, TBBT, and p-
MBA, which was a control sample. It can be seen, however, that the optical density for
these samples decreased due to thiol etching.146-147 Absorbance spectra of exchange products of PET, CHT, TBBM, BM did not show any characteristic absorption bands of
Ag44(SR)30, in good agreement with the previous experiment. It is worth noting that the
83
Figure 4-6. Absorbance spectra of the products of ligand exchange reactions using Ag44(p-MBA)30. Starting material (A), BT (B), TBBT (C), p-MBA, control (D), PET (E), CHT (F), TBBM (G), BM (H).
times of ligand exchange required to make absorption spectra completely lose Ag44(SR)30
features were different for BM, TBBM, CHT, and PET. PET and TBBM took 30 min to
completely transform into the product, while only 15 min were needed in the cases of BM and CHT. By looking at the structures of these four ligands it can be concluded that
bulkiness and rigidity of the ligand effect the rate of the ligand exchange. A bulky t-Bu
group even in para-position to the thiol significantly slows down the ligand exchange
process in case of TBBM, and so does an ethylene group between phenyl ring and thiol in
case of PET.
84
Interactions between phenyl rings on Na4Ag44pMBA30 have been observed in
crystals,26, 55 so it is important to consider how the methylene groups could affect any solution-phase ligand interactions that might be otherwise present. The insertion of
methylene groups has three important geometrical effects that could affect such
interactions: (i) they impart an additional degree of freedom, allowing the phenyl rings to
rotate about the C-S bond axes, (ii) they change the angle of the phenyl rings with respect
to the C-S bond and the metal core due to the sp3 hybridization of the inserted C atom,
and (iii) they move the bulky phenyl ring away from the center of the nanoparticle. The
effects of points (ii) and (iii) could be tested using PET ligands and CHT ligands,
respectively.
PET ligands introduced two methylene groups between the phenyl ring and the
thiol group in BT (see Fig. 4-2). When silver nanoparticles were synthesized with PET,
again the product was found to contain no Ag44(SR)30 molecules, as shown
spectroscopically (see Fig. 4-3, inset) and by ESI-MS analysis (see Fig. 4-5). With two methylene groups, it was possible for the angle of the phenyl ring with respect to the C-S bond direction to be the same as for BT, although additional degrees of freedom would also make other orientations possible. The fact that no Ag44(SR)30 was observed in the
PET-ligated product shows that this structural modification was insufficient for
stabilization of the Ag44(SR)30 structure. This supports the notion that the relative angle
of the phenyl ring was likely not the key factor responsible for the instability of
Ag44(SR)30 with ligands that have mixed aromatic and aliphatic character.
The effect of proximity of the bulky phenyl ring to the nanoparticle was
investigated using CHT, which eliminated the aromaticity of the phenyl rings while 85
keeping the six carbon atoms in close proximity to the thiol group (see Fig. 4-2). In this
way, the bulkiness near the metal nanoparticles and much of the van der Waals
component of the ligand-ligand interactions could be maintained. When silver
nanoparticles were synthesized with CHT as the ligand, however, again the product was
found to contain no Ag44(SR)30 molecules, as shown spectroscopically (see Fig. 4-3,
inset) and by ESI-MS analysis (see Fig. 4-5). It can therefore be concluded that the
proximity of the carbon atoms in the ring to the metal core is not the key factor
responsible for the stability of Ag44(SR)30.
The above results for CHT and PET together indicate that it was the introduction
of additional degrees of freedom that was the most important factor that led to the
instability of the Ag44(SR)30 structure with ligands containing methylene groups between
the aromatic ring and thiol group. The comparison of BT and CHT also clearly shows the importance of aromaticity within the ligand. The above results point to the importance of the interactions between aromatic rings for stabilizing the Ag44(SR)30 structure and the
importance of restricting the degrees of freedom to promote such stabilizing interactions.
Indeed, all ligands in the Na4Ag44(p-MBA)30 crystal structure were found to interact strongly with their neighbors via their aromatic rings, which contributed significantly to the overall stability/cohesive energy of each molecule in the crystal.26, 55, 100
Strong ligand-ligand interactions have been predicted by computational
methods35, 99, 148 and recently observed in crystal structures.26, 57, 100 The observation of
strong ligand-ligand interactions in a crystal does not itself indicate the presence of such interactions in the solution phase of a synthetic reaction, however. In fact, it might be expected that ligand-ligand interactions observed in the crystal structure would be 86
disrupted upon solvation of the nanoparticles. Nuclear Overhauser effect spectroscopy
(NOESY) was therefore used to measure through-space coupling of protons on neighboring ligands in order to provide information about solution-phase ligand-ligand interactions.
Measurement of a solution of Na4Ag44(p-MBA)30 nanoparticles in DMF showed that ligands on the apex sites of the Ag2(SR)5 mounts interacted with pairs of ligands on either side of the mounts’ base (see Fig. 4-7). Peaks near 7.35 and 7.41 ppm correspond to the four ligands at the base of the mounts and peaks near 7.22 ppm correspond to the ligand on the apex site of the mounts.55 Off-diagonal peaks, which correspond to short- range through-space interactions, showed that strong interactions between the apex ligands and the pairs of ligands at the base of the mounts existed in solution despite their solvation.
Figure 4-7. NOESY NMR of Na4Ag44(p-MBA)30 nanoparticles in DMF.
87
This is the first observation of strong ligand-ligand interactions in a solvated nanoparticle, which contradicts the expectation of fully solvated ligands. While it is likely that the ligand-ligand interactions in the present case are stronger than those of an aliphatic ligand, it remains to be seen to what extent the current understanding of ligand solvation correctly captures solution phase behavior of ligated nanoparticles.
The above studies show that the stability of Ag44(SR)30 requires ligands that have
a phenyl ring directly attached to the metal nanoparticle through a primary thiol, i.e. the
alpha carbon must be part of an aromatic ring. On the basis of alpha carbon character,
ligands can be divided into two classes, namely, those whose alpha carbon is or is not
part of an aromatic ring (herein we classify these as α-aromatic and α-aliphatic ligands,
respectively). Further, it is important to note that no species made with one class of
ligands has been observed with the other class of ligands. For example, α-aromatic
ligands have been used to produce Ag17(SR)12, Ag25(SR)18, and Ag44(SR)30 nanoparticles,
which have not been observed in the products of silver nanoparticle syntheses using α-
aliphatic ligands; the spectra of these species are unique to the class of ligands. The
species produced using these two classes of ligands can therefore be considered
orthogonal. One can therefore state that, for silver, the ligands function as structure-
determining synthons, wherein the two classes of ligands produce two orthogonal classes
of nanoparticles.
4.3.3 Conversion of Ag:SG NPs into M4Ag44(p-MBA)30 via ligand exchange.
The failure to obtain M4Ag44(SG)30 from M4Ag44(p-MBA)30 by ligand exchange, as
described earlier, can now be interpreted as a transformation of one class of nanoparticles
into another, driven by ligands that were incompatible with the initial nanoparticle 88
structure. In other words, substitution of α-aliphatic glutathione ligands for α-aromatic p-
MBA ligands destabilized the Ag44(SR)30 structure, producing instead a series of
nanoparticles that were consistent with α-aliphatic ligand-silver chemistry (see Fig. 4-1 inset). One might then expect the opposite process to be possible, wherein a mixture of silver nanoparticles with α-aliphatic ligands could be converted to other structures consistent with α-aromatic ligand-silver chemistry as the result of a ligand exchange reaction involving α-aromatic ligands. For example, it might be expected that Ag:SG nanoparticles could be converted to Na4Ag44(p-MBA)30 by the addition of p-MBA
ligands.
To test this hypothesis, solid Ag:SG nanoparticles were added to a 5-fold excess
solution of p-MBA in order to exchange the glutathione ligands for p-MBA. After
incubating overnight under ambient conditions, the solution was transformed into a dark
wine red color. The optical absorption spectrum of the product contained absorption
bands that were characteristic of Ag44(SR)30 (see Fig. 4-8), which shows successful conversion of nanoparticles of one class to another. This finding is consistent with previous work addressing ligand exchange on molecular silver nanoparticles.141 It is
worth noting that the yield of the ligand exchange reaction was not quantitative based on
comparison of the optical density of the initial and final states of solution (see Fig. 4-8).
It is important to note that it is not clear to what extent this reaction could be
considered reversible. These reactions could be thought of as the disassembly of reactant
nanoparticles into a variety of materials followed by the reassembly of those materials
into the product nanoparticles, as dictated by the identity of the ligands. To what extent
the reactions produce the same distributions of product is unknown, however. For 89
Figure 4-8. Optical absorption spectra of a mixture of Ag:SG nanoparticles (dashed) and a product of the ligand exchange (solid) with p-MBA using 5:1 p- MBA:SG ratio in 7:4 water:DMSO mixture. The spectrum of the product indicates the formation of M4Ag44(p-MBA)30 nanoparticles as a result of the ligand exchange reaction.
example, it has been shown that the product of repeated oxidation and reduction cycles of
silver nanoparticles with α-aliphatic ligands can be narrowed with each successive cycle
to ultimately produce a single-sized product from what was initially a mixture of
nanoparticle sizes.149 While it is convenient to refer to these types of reactions as
reversible, it is important to recognize the limits of this description.
4.3.4 Partial ligand exchange on M4Ag44(p-MBA)30 using GSH. It is clear that the substitution of glutathione ligands for p-MBA destabilizes Na4Ag44(p-MBA)30
nanoparticles, but an important question remains: how many ligands can be substituted
before a nanoparticle structure is destabilized and transformed by the incoming ligands?
In other words, to what extent can the two classes of ligands coexist? 90
Substitution of glutathione for p-MBA on Ag44(p-MBA)30 was chosen to study
this question since this nanoparticle is known to be stable in the gas phase,26, 45 which
makes the mass spectrometric analysis of the products of substitution robust. Partial
ligand exchange experiments on M4Ag44(p-MBA)30 nanoparticles using GSH as an
incoming α-aliphatic ligand were conducted with ratios of GSH to Ag44(p-MBA)30 being
1:1, 5:1, 10:1, and 20:1. Briefly, the GSH was dissolved in 30 μL of deionized water, to
which 270 μL of 29.5 μM solution of Ag44(p-MBA)30 in DMF were added. The solutions
were then vortexed for 1 min and incubated at room temperature for approximately 1 h.
The optical densities of the four samples were lower after the incubation period, as
compared to the initial solutions, indicating a reaction between GSH and Ag44(p-MBA)30
had occurred such that the concentration of Ag44(SR)30 in the solutions had decreased.
The concentrations decreased as the amount of GSH in solution increased.
The products of the ligand exchange reactions were characterized by ESI-MS (see
Fig. 4-9). A series of peaks was observed at higher mass than the parent [Ag44(p-
4- MBA)30] peak, and their intensities increased with increasing GSH to Ag44(p-MBA)30
ratio. The masses of GSH and p-MBA are 306.32 Da and 153.18 Da, respectively, therefore substitution of glutathione for p-MBA would increase the mass of Ag44(p-
MBA)30 by 153.14 Da (38.285 m/z for the 4- ion). This mass difference corresponds to
the observed peak spacing. At a first look, it appears that there are multiple exchange
products with different amounts of glutathiones exchanged. The peak intensities,
however, do not follow the expected Gaussian distribution that would result from random
ligand substitutions. Careful analysis of the data can reveal the origin of the unexpected
distributions observed. 91
Figure 4-9. ESI mass spectra of ligand exchange products using GSH:Ag44 ratios of (a) 0:1, (b) 5:1, (c) 10:1, and (d) 20:1. (e) Gaussian fits to peak intensities from (d) indicate that there were two series of peaks that corresponded to species with adducts along with one (red line) and two (blue line) substitutions. The fits also show that the first three data points belong to a different series, without adducts.
92
It is important to consider the contribution of GSH adducts to the peak intensities.
4- 4- While the masses of [Ag44(p-MBA)30] and [Ag44(p-MBA)29(SG)1] are unique to those
species, the 2-fold mass symmetry of GSH and p-MBA creates an ambiguity between
4- substituted and adduct species. For example, the masses of [Ag44(p-MBA)28(SG)2] and
4- [Ag44(p-MBA)30 + GSH] ions differ only by 0.25 Da/z. The contribution of adducts to
the observed peak intensities must therefore be deconvoluted from that of substituted species.
Statistical analysis of the adduct distributions was carried out to reveal the extent of ligand exchange. There existed three possible contributions to the observed peak intensities: (i) ligand-exchanged species without adducts, (ii) species with adducts and an odd number of exchanged ligands, and (iii) species with adducts and an even number of exchanged ligands. Species (i) could contribute to all peaks, whereas species (ii) and (iii) could contribute to alternating peaks (see Fig. 4-9). When the data were fit using two
Gaussians to model cases (ii) and (iii) for only 1 and 2 substitutions, respectively, all but the first three peaks were well accounted for (see Fig. 4-9e). This indicated that the first three data points were part of a third distribution, which included only species without
adducts.
The fact that a distribution was not required to model adducts of M4Ag44(p-
MBA)30 with no substitutions indicated that such species did not exist at detectable
concentrations in our experiments. Only species that had undergone at least one exchange
reaction were observed to have adducts in the ESI-MS measurements. This indicates the existence of a specific interaction between glutathione molecules in solution and in the ligand shell. Further, the fact that the adduct distribution was Gaussian indicated that the 93
interaction was more complex than dimerization. It is worth noting that clustering in the
gas phase was observed for neat glutathione samples in the solvent used for ligand
exchange. Observing ligand exchange products that involved clusters of glutathione is
therefore not unexpected, however the fact that no adducts were found for species
without at least one glutathione ligand is surprising. Clearly the difference in the
interaction energies for GSH adsorption onto the different species is significant. While the p-MBA ligand can interact with GSH with its carboxylic acid group, a glutathione ligand can interact with both its carboxylic acid and amine groups, possibly as a zwitterion. This dipolar interaction could possibly be the origin of adduct formation and clustering.
The observed pattern of adduct formation also portends a possible multistep mechanism for this particular reaction. The first substitution reaction is expected to be
4- slow, in part due to the weak interactions between [Ag44(p-MBA)30] and GSH in solution. When GSH molecules adsorb to species with glutathione ligands, however, their opportunity to react with those species ought to be significantly enhanced and subsequent substitution reactions are expected to be faster. The glutathione ligands could be viewed as playing a role similar to a catalyst, although by increasing the pre-exponential factor rather than by lowering the activation energy. Such a mechanism may have implications for in vivo studies, where GSH is ubiquitous. Namely, unsubstituted species may be relatively inert in vivo, however once the first GSH substitution occurs, reactivity would increase.
The fact that a distribution was not required to model adducts of M4Ag44(SR)30
with 3 substitutions also indicated that such tri-exchanged species did not exist at 94
detectable concentrations in our experiments. The inclusion of such a distribution reduces
the quality of fit of the three-distribution model, therefore the existence of tri-exchanged
species in our measurements is unlikely. This leads to the rather profound conclusion that
it takes only three GSH molecules to destroy M4Ag44(SR)30.
4.4 Conclusion
This study shows that ligands can be divided into two classes based on the
character of the α-carbon of the thiol. The two classes of ligands were found to produce two orthogonal sets of products by both direct synthesis and ligand exchange.
Compatibility of the two different classes of ligands on M4Ag44(SR)30 nanoparticles was
studied using p-MBA and glutathione. It was found that M4Ag44(p-MBA)30 nanoparticles can tolerate up to two glutathione heteroligands and that the third substitution destabilizes the particle. This shows that ligands play an important role in determining a nanoparticle’s structure. Clustering of heteroligand was observed, which hints that ligands were substituted through a single site. However, the mechanism of substitution remains unclear.
95
Chapter 5
Conclusions
The field of thiolate-protected molecular nanoparticles has advanced greatly since the first attempts to characterize small gold nanoparticles in the 1990s.14 Back then, every
new species had a high impact in the literature. Nowadays, the number of thiolate-
protected gold MNPs synthesized and characterized is in the order of tens.150 Many of
them have crystal structures reported allowing analysis of the similarities and differences
of metal atom arrangements in cores and core-ligand interfaces. Silver nanoclusters are
still lagging in terms of published data. Only four all-thiol protected structures have been
discovered to date.26, 57, 72-73 Greater lability and reactivity of silver nanoparticles is the
main obstacle for their extensive study. Despite that, our understanding of these systems
has greatly improved in the past decade. Moreover, for commercial applications, silver
has a great advantage due to low cost. After gaining enough understanding of structure-
property relationships for monometallic nanoparticles, it is natural to expand studies to
bimetallic systems. In a search for synergistic properties, we thus study bimetallic
nanoparticles, which are alloys of the 21st century, quantumly confined in a metal- thiolate framework. As a scientific community, we are at the point where we can gather information about known structures and start rationally predicting structures of the 96
nanoparticles we have not characterized yet, and it makes us one step closer to rational
design. Finally, we start understanding a deeper role of ligands in the formation and
stability of the nanoparticles, which is far more complex than just steric protection.
Here, bimetallic M4AuxAg44-x(p-MBA)30 nanoparticles were synthesized by co-
reduction and galvanic exchange. Nanoparticles with up to 12 Au atoms were found in
the series. It was found that under single crystal measurement conditions (100 K) Au
atoms occupy the icosahedral core of the 44-atom structure. Incorporation of 13 and more
Au atoms led to formation of staple-mount hybrid protecting motifs, i.e. structural change. Such hybrid motifs have been shown to exist in structurally similar
69 Au18Cu32(SR)36 nanoparticles.
Both condensed phase and gas phase properties exhibited complex behavior with
changing numbers of Au heteroatoms. Syntheses by co-reduction at low Au:Ag input ratios (1:43, 2:42) produced bimodal distributions of nanoparticles in terms of x. At higher input ratios, products were normally distributed with the center of the distribution being equal to or lower than the input gold. Thermal stability was measured for products
of high ratio syntheses (12:32, 14:32) and stabilities were found to change monotonically
with x. Shifts of particle distributions towards higher x values after thermal processing
were measured by ESI-MS.
Galvanic exchange reactions on M4Ag44(p-MBA)30 using Au-(p-MBA) polymeric
thiolate as a source for gold atoms produced nanoparticles identical to those made by co-
reduction, as confirmed by tandem MS. This means that heteroatoms in the molecular
nanoparticles are mobile, i.e. can get from outside to the inner core, and their locations
are governed by outside conditions. 97
Mass spectrometry was used to find relative quantities of M4AuxAg44-x(p-MBA)30
nanoparticles. Fragmentation coefficients were used to convert molecular peak intensities
into concentrations. Thus, chemical equilibrium constants were found for every reaction
of M4AuxAg44-x(p-MBA)30 with gold thiolate to produce M4Aux+1Ag43-x(p-MBA)30
nanoparticles in experiments with different initial concentrations of thiol. Constants were
converted into standard Gibbs free energies and statistically analyzed to find outliers,
mean values, and standard deviations. It was found that incorporation of one to about
seven heteroatoms is favorable, while a higher number of gold atoms requires substantial
chemical pressure, i.e. high concentrations of gold thiolate.
Gas-phase stability of M4AuxAg44-x(p-MBA)30 nanoparticles was also found to be
a non-monotonic function of x. Surprisingly, low gold loadings destabilized the particles,
while insertion of five or more gold atoms improved stability. The kinetic method was
used to calculate activation barrier changes for fragmentation reactions of M4AuxAg44- x(p-MBA)30 with M4Ag44(p-MBA)30 as a reference.
Optical properties of M4AuxAg44-x(p-MBA)30 nanoparticles changed smoothly with x. Lowest energy peaks, corresponding to the HOMO-LUMO gap, were blue
shifted, indicating its widening. Molar absorptivities smoothly decreased with increasing number of heteroatoms. This was somewhat expected since it has been shown that gold nanoparticles, in general, absorb less light compared to their silver counterparts.
In chapter 3, silver nanoparticles were synthesized using t-butyl benzenethiol
(TBBT) for ligation. With the formation of already known M4Ag44(SR)30 nanoparticles,
new M3Ag17(TBBT)12 nanoparticles were formed. This allowed comparison of gas phase
3- behavior. Relatively small Ag17(TBBT)12 ions were found to undergo charge reduction, 98
also known in the literature as Coulomb explosion,49 by emitting anionic ligands and
- Ag(TBBT)2 fragments while keeping a constant 8 electron shell. In contrast,
4- Ag44(TBBT)30 ions were found to first emit an electron, thus breaking the stable electronic shell, while keeping their geometric integrity. Only in the next step,
3- Ag44(TBBT)30 ions reduced their charge by emission of anionic fragments. This showed
that for larger molecular nanoparticles stabilization greatly depends on interligand
interactions.
In contrast to the gas phase, the stability of M3Ag17(TBBT)12 in solution was poor
and attempts to separate the nanoparticle failed. However, its small size and structural
analysis of other noble metal nanoparticles allowed rational structure prediction. The
particle was predicted to have a 13-atom icosahedral core capped by newly proposed
Ag(SR)3 protecting units. Computational analysis using DFT predicted a high HOMO-
LUMO gap of 1.77 eV, which is consistent with good gas-phase stability. Since the
proposed structure has a central atom in the icosahedron, heteroatom substitution was
used to probe the structure. MS analysis of bimetallic synthesis using stoichiometric and
5-fold excess gold amounts showed the same results, except in the latter case excess gold
was producing larger plasmonic nanoparticles. M3AuAg16(TBBT)12 nanoparticles were
formed almost exclusively, consistent with DFT predictions of a strong preference for a
single atom substitution, thus supporting our predicted structure. The inorganic part of the
predicted structure was later found to be identical to that of the experimentally
determined structure.
In the final part of this work, Ag:SR nanoparticles were synthesized using a series
of ligands in which aromaticity, the length of aliphatic chain between sulfur and phenyl 99
ring, and different substituting groups on the phenyl ring were systematically varied. It
was found that only ligands with aromatic α-carbon yield M4Ag44(SR)30 nanoparticles.
Two other nanoparticles that have α-aromatic thiol ligands, M3Ag17(SR)12 and
35, 73 MAg25(SR)18 were reported in the literature. None of the products of synthesis with
α-aliphatic ligands including those used in this study and in the literature151 showed any
characteristic optical absorption features of these nanoparticles. Thus, ligands were
divided into two classes that produce orthogonal sets of species. We also showed that an
even softer approach, a ligand exchange reaction, triggers the transformation of the
nanoparticle if the ligand belonged to a different class.
We showed a complete transformation of Ag:SG nanoparticles into M4Ag44(p-
MBA)30 and back using ligand exchange. It was interesting to investigate how many GSH
ligands could be tolerated by M4Ag44(p-MBA)30 before it transformed into nanoparticles of the other class. Up to two heteroligands were detected on M4Ag44(SR)30 nanoparticles
at a 20:1 GSH to M4Ag44(p-MBA)30 ratio, which suggests that the third substitution led to
destabilization. At higher ratios, the transformation occurred too fast and the products of
the reaction were not detectable by ESI-MS. This shows that ligands can play a
determining role in the outcome of a synthesis, and their noncovalent interactions in the
ligand shell are more important than previously thought.
100
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