Nanostructure Quantification of Carbon Blacks

Journal of C Carbon Research

Article Nanostructure Quantiﬁcation of Carbon Blacks

Madhu Singh and Randy L. Vander Wal *

John and Willie Leone Family Department of Energy and Mineral Engineering and the Earth and Mineral Sciences (EMS) Energy Institute, Penn State University, University Park, State College, PA 16802, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-814-865-5813

Received: 20 November 2018; Accepted: 21 December 2018; Published: 31 December 2018

Abstract: Carbon blacks are an extensively used manufactured product. There exist different grades by which the carbon black is classiﬁed, based on its purpose and end use. Different properties inherent to the various carbon black types are a result of their production processes. Based on the combustion condition and fuel used, each process results in a carbon black separate from those obtained from other processes. These carbons differ in their aggregate morphology, particle size, and particle nanostructure. Nanostructure is key in determining the material’s behavior in bulk form. A variety of carbon blacks have been analyzed and quantiﬁed for their lattice parameters and structure at the nanometer scale, using transmission electron microscopy and custom-developed fringe analysis algorithms, to illustrate differences in nanostructure and their potential relation to observed material properties.

Keywords: carbon; nanostructure; HRTEM; fringe; quantiﬁcation

1. Introduction Carbon black is manufactured elemental carbon with customized particle size and aggregate morphology [1]. Produced from the partial combustion or thermal decomposition of hydrocarbons, carbon black is an engineered material, primarily composed of >98% elemental carbon. This number may vary based on its production process and final desired application, where carbon black may be doped with other elements like oxygen, nitrogen, or sulfur to impart solubility, better dispersion or binding properties to the material. The principal uses of carbon black are as a reinforcing agent in rubber compounds, especially tires, and as a black pigment in printing inks, surface coatings, paper, and plastics [1,2]. Worldwide production of the material was estimated at ~13 million metric tons (MMT) at USD ~14 billion in 2015, and is expected to reach ~19 MMT (USD ~20 billion) by 2022 [3]. Approximately >90% of carbon black is used in rubber applications, with the remainder used as an essential ingredient in hundreds of diverse applications, such as plastics, pigments, and coatings [3]. Carbon black is produced by the reaction of a hydrocarbon fuel, such as oil or gas, with a limited supply of combustion air at temperatures of 1300–1500 ◦C[4]. Carbon black was first manufactured in the 1930s using the Channel Black process, with natural gas, the feedstock, developed in the United States, and the Gas Black process, using coal tar as feed, developed by Degussa in Germany [1]. Both processes used flames impinging on cold surfaces to produce the material. However, owing to environmental and safety concerns, the Channel Black process phased out, but manufacturing with the Gas Black process continued given its environmentally friendly technology and handling [1]. These two processes paved the way for the heavy use of carbon black in the automotive industry in the two nations, respectively. Two major processes are presently used in the United States to manufacture carbon black: (a) the oil furnace process and (b) the thermal process [1,4]. The Furnace Black process is the most recently developed and widely used process for carbon black manufacture,

C 2019, 5, 2; doi:10.3390/c5010002 www.mdpi.com/journal/carbon C 2019, 5, 2 2 of 12 accounting for >95% of production [1]. This process is a continuous one which uses heavy aromatic oils as feedstock and natural gas as the heat source. The production furnace uses atomizing nozzles in a closed refractory-lined reactor to pyrolyze the feedstock oil. Primary quench water cools the gases to 500 ◦C to stop the cracking. The Thermal Black process accounts for <5% of carbon black production and uses natural gas, primarily methane, as a feedstock material. The process uses a pair of furnaces that alternate approximately every five minutes between preheating and carbon black production. The natural gas is injected into the hot refractory-lined furnace and, in the absence of air, the heat from the refractory material decomposes the natural gas into carbon black and hydrogen. The aerosol material stream is quenched with water sprays and filtered in a bag-house. Other processes, such as the lamp process for the production of lamp black and the cracking of acetylene to produce acetylene black, are specialty processes comprising <2% of carbon black production. The Lamp Black process is one of the oldest commercial carbon black processes. It uses an aromatic oil based on coal tar that is heated in a flat cast-iron pan to produce carbon black. The Acetylene Black process is categorized as a Thermal Black process, except that acetylene is the feedstock, and the carbon black is generally not processed into pellets. Acetylene black is a specialty carbon black owing to its purity of carbon and conductive properties, making it a key ingredient as a conductive additive in polymer compounds or in battery manufacture among other uses. Applying the terminology of the International Organization for Standardization’s (ISO) Technical Specification 80004-1 of 2015, carbon black is considered a nanostructured material (i.e., a material having internal or surface structure in the nanoscale). A generally accepted model is the crystallite model, wherein the primary particles are comprised of numerous crystallites oriented circumferentially. Each crystallite or basic structural unit consists of a turbostratic stack of short lamellae [5]. Though morphology and size have been well documented, yet remaining is the nanostructure, and in particular the differences between carbon blacks produced by the four processes in present practice. This work aims to bring to the reader’s attention the variations in nanostructure observed due to different manufacturing conditions for the carbon blacks. Nanostructure, in turn, dictates particle and material behavior and interaction at the macro scale. For instance, degree of reactivity of the material is based on available reactive edge sites. The use of carbon black as a filler depends on the matrix-filler interfacial interaction at the nanometer scale. Nanostructure modification can also impart conductive properties to the carbon black. Presented here is a comprehensive and comparative overview of the differences between these materials, to help make better choices when using these as they are or as model materials for fundamental studies on carbon.

2. Materials and Methods Furnace Black is from Cabot Corp. (Boston, MA, USA), thermal black is from Cancarb Ltd. (Medicine Hat, Alberta, Canada), and Lamp Black and Channel Black are from Degussa (now Orion Engineered Carbons, Frankfurt, Germany). Acetylene black is shown to illustrate the possible variation in morphology and nanostructure by changing reaction and processing parameters. Type-1 acetylene black is from AkzoNobel (Amsterdam, Netherlands) and Type-2 acetylene black is from Soltex Inc., (Houston, TX, USA). Bright field high resolution images for carbon nanostructure analysis were obtained using a Talos F200X (Field Electron and Ion Company (FEI), Hillsboro, OR, USA) equipped with a 200 keV Field Emission Gun (FEG) source and an information limit of 0.12 nm. Trade-off between image resolution and contrast was observed to be optimum with a 70 µm objective to collect the desired high-resolution images for quantification in this work. Particles were imaged close to Scherzer defocus. Samples were sonicated in methanol before being dropped onto 300 mesh lacey C/Cu TEM grids. Image quantification by fringe analysis has been done using custom-developed algorithms in-house, with details described in related works outlining code development [6,7]. More than 10 regions of a TEM grid were analyzed with a total of >60 images collected per sample. Of these, we analyzed ~10 representative images of the particle and its nanostructure for this work. C 2019, 5, 2 3 of 12 C 2018C 2,018 4, ,x 4 FOR, x FOR PEER PEER REVIEW REVIEW 3 of3 of13 13

3. Results 3. Results TransmissionTransmission electron electron microscopy microscopy (TEM) (TEM) hashas beenbeen used to visualize visualize and and subseq subseq subsequentlyuentlyuently quantify quantify parametersparameters of of each each of of the the different different types types of of carbon carbon blacks blacks mentioned above. above. TEM TEM micrographs micrographs representingrepresenting these these different different carboncarbon carbon blacksblacks blacks areare are shownshown shown in inin FiguresFigures1 1 and andand2 2.2. .

100 nm 100 nm

A) Furnace Black B) Thermal Black A) Furnace Black 100 nm B) Thermal100 Blacknm 100 nm 100 nm

C) Lamp Black D) Channel Black C) Lamp Black D) Channel Black Figure 1. TEM images showing aggregates of (A) furnace, (B) thermal, (C) lamp , and (D) channel Figureblacks 1.1.. TEM TEM imagesimages showing showing aggregates aggregates of (ofA )( furnace,A) furnace, (B) thermal,(B) thermal, (C) lamp, (C) lamp and (,D and) channel (D) channel blacks. blacks. A) Type-1 Morphology B) Type-1 Nanostructure 20 nm A) Type-1 Morphology B) Type-1 Nanostructure 20 nm

100 nm Acetylene Black 100C) nmType-2 Morphology D) Type-2 Nanostructure 20 nm Acetylene Black C) Type-2 Morphology D) Type-2 Nanostructure 20 nm

100 nm

Figure100 2. TEM nm micrographs showing two types of acetylene black. Images (A,B) illustrate morphology and nanostructure of type-1 and images (C,D) to type-2 acetylene black. C 2018, 4, x FOR PEER REVIEW 4 of 13 C 2019, 5, 2 4 of 12 Figure 2. TEM micrographs showing two types of acetylene black. Images (A,B) illustrate morphology and nanostructure of type-1 and images (C,D) to type-2 acetylene black. 3.1. Length Scales 3.1. Length Scales Carbon black exhibits a hierarchy of length scales: (a) nanostructure (i.e., internal to primary particles), Carbon black exhibits a hierarchy of length scales: (a) nanostructure (i.e., internal to primary (b) spheroidal primary particles, and (c) their collective bonding as aggregates. An illustration of these particles), (b) spheroidal primary particles, and (c) their collective bonding as aggregates. An lengthillustration scales is of shown these length in Figure scales3 .is Each shown of in theseFigure metrics3. Each ofare these distributional metrics are distributional properties and vary dependingproperties on and the vary carbon depending black grade.on the carbon black grade.

A) Aggregate 500 nm B) Particle 50 nm C) Nanostructure 20 nm

FigureFigure 3. Transmission 3. Transmission electron electron micrographs micrographs showing showing the the three three length scales scales:: (A (A) ) aggregate, aggregate, (B ()B ) primary particle,primary and particle (C) nanostructure, and (C) nanostructure for lamp for black. lamp black.

TheThe shape shape and and degreedegree of of branching branching of the of aggregates the aggregates are referred are to referred as its structure to as [8] its. The structure [8]. structure of carbon blacks is well-characterized by diverse grades, differing in primary particle size The structure of carbon blacks is well-characterized by diverse grades, differing in primary particle size and aggregate morphology depending upon the application for which it was engineered. The and aggregatestructure level morphology of carbon ultimately depending determines upon the its applicationeffects on several for which important it was in-rubber engineered. properties. The structure levelVarious of carbon carbon ultimately black grades determines can be divided its effects into tread on severalgrades, for important tire reinforcement in-rubber, and properties. non-tread Various carbongrades black, for grades non-tread can tire be use divided, to impart into antis treadtatic grades, and electrically for tire conductive reinforcement, properties. and Increasing non-tread grades, for non-treadcarbon black tire structure, use, to imparti.e., the degree antistatic of aggregation and electrically and the conductive dendritic nature properties. of the aggregates, Increasing carbon increases modulus, hardness, electrical conductivity, and improves the dispersibility of carbon black, black structure, i.e., the degree of aggregation and the dendritic nature of the aggregates, increases but also increases compound viscosity. The particle size, structure, and surface area of carbon black modulus,play a hardness,significant role electrical in the material conductivity, properties and of improvesrubber, plastics, the dispersibilityand other products of carbon as well black,[4,9]. but also increasesFor instance, compound the size viscosity. of the primary The particle largely size, determines structure, the and carbon surface black area surface of carbonarea and black play a signiﬁcanttint. Thus,role carbon in black the materialis manufactured properties in many of rubber,grades to plastics,meet the varying and other material products needs and as well [4,9]. For instance,application the specifications. size of the primary In general, particle carbon largely black grades determines with smaller the carbon particle black size surface have better area and tint. Thus,reinforcing carbon black and abrasion is manufactured resistance qualities in many than grades those to with meet larger the varyingparticle size. material Example needss of carbon and application blacks with high and low degrees of aggregation (i.e., number of primary particles per aggregate and speciﬁcations. In general, carbon black grades with smaller particle size have better reinforcing and dendritic vs. compact nature of the aggregate) are shown in Figure 4. abrasion resistance qualities than those with larger particle size. Examples of carbon blacks with high and low degrees of aggregation (i.e., number of primary particles per aggregate and dendritic vs. compactC 2 nature018, 4, x FOR of thePEERaggregate) REVIEW are shown in Figure4. 5 of 13

A) High degree of B) Low degree of aggregation aggregation

500 nm Lamp black 500 nm Thermal black

FigureFigure 4. TEM 4. TEM images images contrasting contrasting a a ( A(A)) highhigh and a a (B (B) )low low degree degree of aggregation of aggregation in the indifferent the different carboncarbon blacks. blacks.

3.2. Nanostructure Quantification Nanostructure is defined as the detailed physical metrics of carbon lamellae within primary particles, such as lamella length, curvature or undulation of the carbon lamella, and spacing between lamellae [10]. Individual graphene segments (dark lines) observed in a high-resolution TEM (HRTEM) image are referred to as lamellae. Nanostructure has been illustrated in Figure 5, with the image showing the internal structure of the particle of a thermal and a furnace black respectively.

A) Thermal Black 5 nm B) Furnace Black 5 nm

Figure 5. TEM image showing nanostructure of (A) thermal and (B) furnace black particles.

X-ray diffraction (XRD) has been one of the oldest techniques used to quantify material nanostructure though Bragg’s law for layer plane spacing and Scherrer’s equation for crystallite dimensions [11–13]. Raman spectroscopy, given its ease of measurement, has also been widely used to study the degree of order (or lack thereof) in carbonaceous materials [14–18]. An example of XRD and Raman for the furnace black is shown in Figure 6. XRD samples weighed ~1 g spread flat on a 25 mm × 25 mm flat sample holder with a ~1 cm diameter depression at its center to hold powdered samples. Raman spectra were obtained, with the powdered sample on a glass slide and spectra collected in DuoScan mode from a 20-micron diameter region. All XRD profiles were fitted for lattice parameter calculation with a residual (R value) of <3%. Following this, lattice parameters calculated C 2018, 4, x FOR PEER REVIEW 5 of 13

A) High degree of B) Low degree of aggregation aggregation

500 nm Lamp black 500 nm Thermal black

C 2019, 5, 2 5 of 12 Figure 4. TEM images contrasting a (A) high and a (B) low degree of aggregation in the different carbon blacks. 3.2. Nanostructure Quantiﬁcation 3.2. Nanostructure Quantification Nanostructure is deﬁned as the detailed physical metrics of carbon lamellae within primary particles,Nanostructure such as lamella is length, defined curvatureas the detailed or undulation physical metrics of the ofcarbon carbon lamella, lamellae and within spacing primary between lamellaeparticles [10]., such Individual as lamella graphene length, curvature segments or (dark undulation lines) observedof the carbon in alamella, high-resolution and spacing TEM between (HRTEM) lamellae [10]. Individual graphene segments (dark lines) observed in a high-resolution TEM image are referred to as lamellae. Nanostructure has been illustrated in Figure5, with the image (HRTEM) image are referred to as lamellae. Nanostructure has been illustrated in Figure 5, with the showingimage the showing internal the structure internal structure of the particle of the particle of a thermal of a thermal and a and furnace a furnace black black respectively. respectively.

A) Thermal Black 5 nm B) Furnace Black 5 nm

FigureFigure 5. TEM 5. TEM image image showing showing nanostructure nanostructure of ( AA)) thermal thermal and and (B ()B furnace) furnace black black particles particles..

X-rayX-ray diffraction diffraction (XRD) (XRD) has has been been one one of of the the oldest techniques techniques used used to toquantify quantify material material nanostructurenanostructure though though Bragg’s Bragg’s law law for for layer layer plane plane spacing and and Scherrer’s Scherrer’s equation equation for crystallitefor crystallite dimensions [11–13]. Raman spectroscopy, given its ease of measurement, has also been widely used dimensions [11–13]. Raman spectroscopy, given its ease of measurement, has also been widely used to study the degree of order (or lack thereof) in carbonaceous materials [14–18]. An example of XRD to studyand theRaman degree for the of fur ordernace (or black lack is thereof)shown in inFigure carbonaceous 6. XRD samples materials weighed [14 –~118 g]. spread An example flat on a of25 XRD and Ramanmm × 25 for mm the flat furnace sample black holder is with shown a ~1 in cm Figure diameter6. XRD depression samples at weighedits center to ~1 hold g spread powdered flat on a 25 mmsamples.× 25 mm Raman flat samplespectra w holderere obtained with a, ~1with cm the diameter powdered depression sample on at a its glass center slide to and hold spectra powdered samples.collected Raman in DuoScan spectra mode were from obtained, a 20-micron with diameter the powdered region. All sample XRD profiles on a were glass fitted slide for and lattice spectra collectedparameter in DuoScan calculation mode with from a residual a 20-micron (R value) diameter of <3%. region.Following All this, XRD lattice profiles parameters were fitted calculated for lattice parameterC 2018, 4 calculation, x FOR PEER REVIEW with a residual (R value) of <3%. Following this, lattice parameters6 of 13calculated for the different carbon black types from XRD are tabulated in Table1. d002 refers to the d-spacing for the different carbon black types from XRD are tabulated in Table 1. d002 refers to the d-spacing betweenbetween two two consecutive consecutive carboncarbon layer layer planes, planes, Lc Lisc the is thec-axis c-axis stacking, stacking, and La andrefers La to refersthe lateral to the lateral extentextent of these of these layer layer planes. planes.

0.06 0.002 XRD Raman (002) Furnace Black 0.04 Furnace Black D G 0.001

0.02 (100) 2D

Normalized Intensity(a.u.)

Normalized Intensity (a.u.)

0 0 10 30 50 70 500 1500 2500 3500 -1 2 Wavenumber (cm ) FigureFigure 6. 6Illustrative. Illustrative examples examples of ofXRD XRD and and Raman Raman spectra spectra of carbon of blacks carbon. blacks.

Table 1. Lattice parameters from X-ray diffraction.

Furnace Thermal Lamp Channel Acetylene Acetylene Lattice Parameter Black Black Black Black Black-1 Black-2

d002 (Å ) 3.60 3.58 3.56 3.70 3.54 3.45

Lc (using 002) (nm) 1.7 1.6 1.3 1.3 1.6 2.6

La (using 100) (nm) 5.6 4.5 4 3 6 5

Techniques such as Raman or XRD provide a composite average given their spatial averaging. A more detailed rubric by which to understand the nanoscale structure of carbon materials, and in particular carbon blacks, are afforded by quantification of HRTEM images. HRTEM offers a spatial resolution of the primary particle directly, and qualitatively visualizes the lamellae as “fringes” in bright field contrast. Fringes in high-resolution bright field phase contrast images represent the carbon lamellae within the primary particles, and may be analyzed for spatial metrics. Lattice fringe length is a measure of the physical extent of the atomic carbon layer planes as seen in the HRTEM image. Larger lengths correspond to larger crystallites and correspondingly fewer edge sites. Developed over 15+ years, our fringe analysis algorithms quantify nanostructure, particularly lamellae length, by analysis of HRTEM images [6,7].

Table 1. Lattice parameters from X-ray diffraction.

Furnace Thermal Lamp Channel Acetylene Acetylene Lattice Parameter Black Black Black Black Black-1 Black-2

d002 (Å) 3.60 3.58 3.56 3.70 3.54 3.45 Lc (using 002) (nm) 1.7 1.6 1.3 1.3 1.6 2.6 La (using 100) (nm) 5.6 4.5 4 3 6 5

Techniques such as Raman or XRD provide a composite average given their spatial averaging. A more detailed rubric by which to understand the nanoscale structure of carbon materials, and in particular carbon blacks, are afforded by quantification of HRTEM images. HRTEM offers a spatial resolution of the primary particle directly, and qualitatively visualizes the lamellae as “fringes” in bright field contrast. Fringes in high-resolution bright field phase contrast images represent the carbon lamellae within the primary particles, and may be analyzed for spatial metrics. Lattice fringe length is a measure of the physical extent of the atomic carbon layer planes as seen in the HRTEM image. Larger lengths correspond to larger crystallites and correspondingly fewer edge sites. Developed over 15+ years, our fringe analysis algorithms quantify nanostructure, particularly lamellae length, by analysis of HRTEM images [6,7].

3.3. Fringe Analysis The TEM has long been used to study carbonaceous materials [19–21]. Lattice fringes, formed by the constructive interference of the transmitted and diffracted beams in a TEM, provide a reconstruction of the lamellae structure, and can be used to quantify the nanostructure of the carbon black and differentiate between materials based on their lamellae arrangement. Fringe analysis algorithms [6] are applied here to quantify fringes for their length, tortuosity (or undulation), and their stacking, as metrics of nanostructure [10]. Fringe length is the end-to-end distance measuring the fringe along its length, while tortuosity is defined as a ratio of its length to the shortest distance between the fringe’s endpoints. Thus, a straight fringe would exhibit a tortuosity of one, as the shortest distance between its endpoints will coincide with its length. Fringes can be arbitrarily oriented, or they can be stacked with respect to one another. The stacking of fringes is analyzed using an available stack analysis algorithm [22]. This algorithm analyses the image and groups fringes into stacks if they fulfil a user-defined orientation criterion to qualify as a part of a stack. This criterion involves a threshold distance—a maximum angular and lateral displacement below which the fringes will be a part of the same stack. If a fringe is far-displaced laterally or angularly, it will not be a part of one stack, but can form a part of a different stack for which it lies within the defined threshold parameters relative to its neighboring fringes. These parameters have been represented by the schematic in Figure7. Our custom algorithms quantify nanostructure for lamellae length, tortuosity, and separation distance [6,7,23]. For consistency across samples, analysis for fringe length and tortuosity have been demonstrated, with fringe spacing calculation being a challenge for acetylene and thermal blacks, for instance. Figure8 outlines the capabilities of these algorithms. Regions of interest can be selected on an HRTEM image, after which the image is skeletonized and fringes are identified by adjusting the contrast of the image. Their application permits translating image data to quantitative distributions of physical scale (e.g., lamellae lengths) for statistical analyses. During such processing binary, so-called “skeletal” images are created, as illustrated in Figure8. C 2018, 4, x FOR PEER REVIEW 7 of 13

between the fringe’s endpoints. Thus, a straight fringe would exhibit a tortuosity of one, as the shortest distance between its endpoints will coincide with its length. Fringes can be arbitrarily oriented, or they can be stacked with respect to one another. The stacking of fringes is analyzed using an available stack analysis algorithm [22]. This algorithm analyses the image and groups fringes into stacks if they fulfil a user-defined orientation criterion to qualify as a part of a stack. This criterion involves a threshold distance—a maximum angular and lateral displacement below which the fringes will be a part of the same stack. If a fringe is far-displaced laterally or angularly, it will not be a part of one stack, but can form a part of a different stack for which it lies within the defined threshold Cparameters2019, 5, 2 relative to its neighboring fringes. These parameters have been represented by7 the of 12 schematic in Figure 7.

Length Stacked

L A

Tortuosity Stacked Fringes Un-stacked

Figure 7. Fringe parameters characterizing nanostructure. C 2018, 4, x FOR PEER REVIEW Figure 7. Fringe parameters characterizing nanostructure. 8 of 13

Our custom algorithms quantify nanostructure for lamellae length, tortuosity, and separation distance A[6,7,23]) Furnace. For consistency Black across samples, analysis for fringe length and tortuosity have been demonstrated, with fringe spacing calculation being a challenge for acetylene and thermal blacks, for instance. Figure 8 outlines the capabilities of these algorithms. Regions of interest can be selected on an HRTEM image, after which the image is skeletonized and fringes are identified by adjusting the contrast of the image. Their application permits translating image data to quantitative distributions of physical scale (e.g., lamellae lengths) for statistical analyses. During such processing binary, so- called “skeletal” images are created, as illustrated in Figure 8.

B) Skeletonized Furnace Black C) Lamp Black

D) Skeletonized Lamp Black

Figure 8. Image panel showing high-resolution TEM (HRTEM) and respective skeletonized images for Figure 8. Image panel showing high-resolution TEM (HRTEM) and respective skeletonized images (A,B) furnace and (C,D) lamp black. for (A,B) furnace and (C,D) lamp black. Fringe statistics of length and tortuosity can then be extracted from the binarized and skeletonized Fringeimages. statistics These are of plotted length for and furnace, tortuosity lamp, and can channel then black be in extracted Figure9, and from for the the two binarized grades and skeletonizedof acetylene images. black These in Figure are plotted 10. Owing for to furnace, the high densitylamp, ofand fringes channel for thermal black blackin Figure (as shown 9, and in for the Figure5A), fringes could not be distinctly and reliably measured by the algorithm and therefore have two gradesnot of been acetylene presented black here. in Figure 10. Owing to the high density of fringes for thermal black (as shown in Figure 5A), fringes could not be distinctly and reliably measured by the algorithm and therefore have not been presented here.

60 60 60 Furnace Black Lamp Black Channel Black

40 40 40

% Fringes%

% Fringes% 20 Fringes% 20 20

0 0 0 < 1 1 2 3 4 < 1 1 2 3 4 < 1 1 2 3 4 Length (nm) Length (nm) Length (nm)

60 Furnace Black 60 Lamp Black 60 Channel Black

40 40 40

% Fringes% Fringes%

% Fringes% 20 20 20

0 0 0 1 1.1 1.2 1.3 1.4 1.5 1 1.1 1.2 1.3 1.4 1.5 1 1.1 1.2 1.3 1.4 1.5 Tortuosity Tortuosity Tortuosity Figure 9. Fringe statistics of (top) length and (bottom) tortuosity for furnace, lamp, and channel black. C 2018, 4, x FOR PEER REVIEW 8 of 13

A) Furnace Black

B) Skeletonized Furnace Black C) Lamp Black

D) Skeletonized Lamp Black

Figure 8. Image panel showing high-resolution TEM (HRTEM) and respective skeletonized images for (A,B) furnace and (C,D) lamp black.

Fringe statistics of length and tortuosity can then be extracted from the binarized and skeletonized images. These are plotted for furnace, lamp, and channel black in Figure 9, and for the two grades of acetylene black in Figure 10. Owing to the high density of fringes for thermal black (as

Cshown2019, 5 ,in 2 Figure 5A), fringes could not be distinctly and reliably measured by the algorithm8 and of 12 therefore have not been presented here.

60 60 60 Furnace Black Lamp Black Channel Black

40 40 40

% Fringes%

% Fringes% 20 Fringes% 20 20

0 0 0 < 1 1 2 3 4 < 1 1 2 3 4 < 1 1 2 3 4 Length (nm) Length (nm) Length (nm)

60 Furnace Black 60 Lamp Black 60 Channel Black

40 40 40

% Fringes% Fringes%

% Fringes% 20 20 20

0 0 0 1 1.1 1.2 1.3 1.4 1.5 1 1.1 1.2 1.3 1.4 1.5 1 1.1 1.2 1.3 1.4 1.5 Tortuosity Tortuosity Tortuosity CFigureF igure2018, 4 ,9 9. x. FringeFORFringe PEER statistics REVIEW of ( toptop)) length length and and ( (bottom)) tortuosity tortuosity for for furnace, furnace, lamp, and channel black black.9 of 13.

60 60 Acetylene Black (Type-1) Acetylene Black (Type-2)

40 40

% Fringes% % Fringes % 20 20

0 0 < 1 1 2 3 4 < 1 1 2 3 4 Length (nm) Length (nm) 80 80 Acetylene Black (Type-1) Acetylene Black (Type-2)

60 60

40 40

% Fringes%

20 20

0 0 1 1.1 1.2 1.3 1.4 1.5 1 1.1 1.2 1.3 1.4 1.5 Tortuosity Tortuosity FigureFigure 10. 10Fringe. Fringe statistics statistics of of ( top(top)) length length and ( (bottombottom) )tortuosity tortuosity for for two two acetylene acetylene blacks blacks..

FringeFringe statistics statistics give give an an overview overview onon nanostructurenanostructure quantification quantification and and provide provide the user the userwith witha a betterbetter metric metric to describe to describe the the carbon carbon black black particleparticle with with reference reference to toits itsnanostructure. nanostructure. With With HRTEM HRTEM and itsand quantification, its quantification, nanostructure nanostructure isis seenseen to be different different based based on on the the carbon carbon black black production production process, with each process resulting in carbon black suited to a desired purpose. process, with each process resulting in carbon black suited to a desired purpose. While these are 3D objects, they are all well less than 100 nm, and as such, electron transparent. AdditionallyWhile these, are while 3D there objects, is a they radial are variation all well lessin mass than-thickness 100 nm, contras and ast, such, the added electron diffraction transparent. Additionally,contrast at while high magnification there is a radial does variation permit visualization in mass-thickness of crystalline contrast, nanostructure the added and diffraction subsequent contrast at highfringe magnification analyses. It is does true, permit however, visualization that despiteof location crystalline of the nanostructure image plane (focusing/defocusing and subsequent fringe analyses.conditions), It is true, some however, distortion that of despitethe interfering location wave of the fronts image does plane occur (focusing/defocusing due to internal “scatter conditions),”. This somemanifests distortion as ofloss the of interfering sharpness, butwave no frontst fringe does reduction. occur All due images to internal have “scatter”. some contrast This variation manifests as loss ofalong sharpness, fringes that but can not lead fringe to artificial reduction. breaks, All but images the ‘join have’ parameter some contrast in the algorithms variation offsets along this fringes that caneffect. lead However, to artificial the thermal breaks, black but the defin ‘join’es the parameter limit of sufficient in the algorithms image contrast. offsets As thisothe effect.r studies However, of carbon blacks and flame-formed carbons show, often there is a lack of quantifiable (nano)structure at particle cores. Relative to metal or metal oxides, carbon d002 fringes have a particularly large spacing, beneficially mitigating such blurring, as it would severely limit similar analyses on these other materials. Lattice parameters calculated after peak deconvolution of Raman and XRD data result in one value of La for the material. Fringe analysis as described here gives the distribution around this one reported, seemingly averaged value typically reported by XRD and TEM. These techniques have their advantages in not requiring sample preparation and image processing, but image quantification using TEM helps the user understand the type and spread of the distribution of fringe lengths to better characterize the carbon black.

4. Discussion Direct surface characterization of carbons is difficult. Beyond textural measurements, assessing reactive sites entails adsorption/desorption using varied gases as probes. While yet allowing quantification of adsorbed gas, prior surface history, heterogeneity, and measurement parameters often make definitive interpretation problematic. Nanostructure, with metrics derived by C 2019, 5, 2 9 of 12 the thermal black defines the limit of sufficient image contrast. As other studies of carbon blacks and flame-formed carbons show, often there is a lack of quantifiable (nano)structure at particle cores. Relative to metal or metal oxides, carbon d002 fringes have a particularly large spacing, beneficially mitigating such blurring, as it would severely limit similar analyses on these other materials. Lattice parameters calculated after peak deconvolution of Raman and XRD data result in one value of La for the material. Fringe analysis as described here gives the distribution around this one reported, seemingly averaged value typically reported by XRD and TEM. These techniques have their advantages in not requiring sample preparation and image processing, but image quantification using TEM helps the user understand the type and spread of the distribution of fringe lengths to better characterize the carbon black.

4. Discussion Direct surface characterization of carbons is difficult. Beyond textural measurements, assessing reactive sites entails adsorption/desorption using varied gases as probes. While yet allowing quantification of adsorbed gas, prior surface history, heterogeneity, and measurement parameters often make definitive interpretation problematic. Nanostructure, with metrics derived by quantification of HRTEM images validated against XRD for lamellae spacing and Raman for lamellae length [6], is a useful metric for surface and internal structure characterization of carbon blacks. C 2018, 4, x FOR PEER REVIEW 10 of 13 Nanostructure has been shown to govern bulk reactivity in oxidation [24,25]. Many HRTEM studiesquantification have shown of a HRTEM radial images variation validated in carbon against lamellae XRD for lamellae length spacing and organization; and Raman for each lamellae increasing outward.length Basal [6], plane is a useful sites metric have for inherently surface and lower internal reactivity structure than characterization edge sites. of With carbon reference blacks. to oxygen, the basal planeNanostructure sites have has nearly been shown 10×–100 to govern× lower bulk reactivity reactivity in than oxidation edge [24,25] sites [.25 Many], dependent HRTEM upon temperature.studies Thoughhave shown nanostructure a radial variation is strictly in carbon an lamellae interior length property, and organization; it does pertain each increasing to initial surface outward. Basal plane sites have inherently lower reactivity than edge sites. With reference to oxygen, reactivity,the basal as the plane surface sites have reflects nearly the 10× unbounded,–100× lower reactivity exposed than lamellae, edge sites with [25], edge-to-basaldependent upon sites as representedtemperature. by the Though near-surface nanostructure nanostructure. is strictly an Whether interior property, by gas it phase does pertain oxidants, to initial aqueous surface chemical attack,reactivity or electrochemical, as the surface reaction, reflects edge the unbounded, sites display exposed higher lamellae, reactivity with andedge determine-to-basal sites the as nascent reactivityrepresented of the carbon by the near black.-surface This nanostructure. is directly relevantWhether by to gas the phase uses oxidants, of carbon aqueous black. chemical For instance, when usedattack as, or fillers electrochemical in rubber reaction, or plastics, edge its sites edge-to-basal display higher site reactivity content and determines determine bondingthe nascent potential reactivity of the carbon black. This is directly relevant to the uses of carbon black. For instance, when and its matrix compatibility in applications such as graphite and electrode manufacture, dictated used as fillers in rubber or plastics, its edge-to-basal site content determines bonding potential and by its interactionits matrix compatibility with thematrix. in applications Matrix such interaction as graphite depends and electrode upon manufacture, surface functionalization dictated by its and surfaceinteraction energy, which with the in turnmatrix. are Matrix dependent interaction on thedepends number upon of surface edge-to-basal functionalization plane sites, and surface hence making their representationenergy, which in by turn near-surface are dependent nanostructure on the number relevant.of edge-to-basal Offering plane representativesites, hence making nanostructure, their many carbonrepresentation blacks by are near also-surface used nanostructure as surrogates releva fornt. sootOffering in oxidationrepresentative studies, nanostructure activated, many carbon in absorptioncarbon studies, blacks are etc. also [24 used,26– 32as ].surrogates An illustration for soot in of oxidation edge and studies, basal activated plane sites carbon is shownin absorption in Figure 11. studies, etc. [24,26–32]. An illustration of edge and basal plane sites is shown in Figure 11.

Edge Sites

Basal Plane Sites

FigureFigure 11. A11. schematic A schematic illustrating illustrating edge edge and and basal basal plane plane carbon carbon sites. sites.

As a final note, carbon black is neither soot nor so-called black carbon [33], despite the seemingly similar morphology and structure of these combustion-produced aerosols. “Soot” and “black carbon” are the two most common names applied to emissions from fires and incomplete anthropogenic combustion of carbon-containing fuels (e.g., natural gas, LPG, gasoline, diesel, kerosene, coal). Such emissions contain some elemental carbon, but also significant quantities of organics and other compounds. “Soot” refers to carbon-rich particles produced by a variety of different combustion processes, including diesel engine exhaust, coal-fired power plant particulate matter (PM) emissions, and oil-fired boilers. “Black carbon” is a term used to describe airborne carbonaceous particulate that has been measured in many recent studies of ambient and indoor particulate matter. As a manufactured material, carbon black consists almost exclusively of pure elemental carbon (>98%). Carbon black generally consists of <1% extractable organic compounds, including polycyclic aromatic hydrocarbons (PAHs). On the contrary, soot particles can consist of >50% organic species which may be dependent upon source and fuel, contain significant concentrations of metals and PAHs. While diesel soot has long been a known carrier for biologically active PAHs, in vitro studies indicate that C 2019, 5, 2 10 of 12

As a final note, carbon black is neither soot nor so-called black carbon [33], despite the seemingly similar morphology and structure of these combustion-produced aerosols. “Soot” and “black carbon” are the two most common names applied to emissions from fires and incomplete anthropogenic combustion of carbon-containing fuels (e.g., natural gas, LPG, gasoline, diesel, kerosene, coal). Such emissions contain some elemental carbon, but also significant quantities of organics and other compounds. “Soot” refers to carbon-rich particles produced by a variety of different combustion processes, including diesel engine exhaust, coal-fired power plant particulate matter (PM) emissions, and oil-fired boilers. “Black carbon” is a term used to describe airborne carbonaceous particulate that has been measured in many recent studies of ambient and indoor particulate matter. As a manufactured material, carbon black consists almost exclusively of pure elemental carbon (>98%). Carbon black generally consists of <1% extractable organic compounds, including polycyclic aromatic hydrocarbons (PAHs). On the contrary, soot particles can consist of >50% organic species which may be dependent upon source and fuel, contain significant concentrations of metals and PAHs. While diesel soot has long been a known carrier for biologically active PAHs, in vitro studies indicate that the PAHs contained on carbon black are adhered strongly to the carbon black, and the PAHs are not bioavailable [3].

5. Conclusions Carbon black manufacture and its growth is heavily tied to the automotive industry, but has numerous other applications in everyday life, making it an integral part of materials and manufactured goods. With a now-favorable industrial environment and increasing demand for automotive and specialty products, the industry is expected to grow at an average rate of ~6% worldwide and ~14% in developing countries like India, for instance, by the early-to-mid-2020 s [3,34]. Given its low cost of production and wide use, studying carbon black to decode its structure and reactivity not only helps understanding it as a material, but also aids in developing the material towards potential unrealized applications. Nanostructure determines the behavior of the material, which translates to the bulk of the material and therefore plays an integral role in its characterization and further development. TEM and related quantiﬁcation of images using fringe analysis as illustrated here provide a measure towards this purpose.

Author Contributions: R.L.V.W. conceptualized the work and provided guidance for data collection and analysis. M.S. acquired TEM images, performed related analysis and interpreted results in consultation with R.L.V.W. M.S. and R.L.V.W. wrote the paper. Funding: The authors gratefully acknowledge support for this work through an Institutes for Energy and the Environment (IEE) seed grant. Acknowledgments: The authors gratefully acknowledge the characterization facilities of the Materials Research Institute and personnel, Ronnie Wasco and Bradley Maben, of the EMS Energy Institute at The Pennsylvania State University. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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