Article pubs.acs.org/EF
Quantifying Curvature in High-Resolution Transmission Electron Microscopy Lattice Fringe Micrographs of Coals Chang’an Wang,†,‡ Thomas Huddle,§ Edward H. Lester,§ and Jonathan P. Mathews*,‡ †
School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China The EMS Energy Institute and Department of Energy and Mineral Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States § Energy and Sustainability Research Division, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, U.K. ‡
ABSTRACT: The observation of high-resolution transmission electron microscopy (HRTEM) lattice fringe images for coals has aided the rationalization of structure and order. Within the hundreds of lattice fringes (edge-on view of the aromatic structures) in a typical micrograph, apparent curvature is common. Traditional image analysis approaches do not appropriately quantify curvature. Tortuosity is functional for the quantification of single-inflection-point smooth lines but poor for complex or undulating lines. Here we present an image analysis method that can identify the points of inflection, angles, and segment lengths that constitute curved lattice fringes. Four coals from the Argonne Premium suite (Pocahontas No. 3, Upper Freeport, Illinois No. 6, and Beulah-Zap) and example anthracites were examined, and curvature was present in 17−24% of the fringes. These curved fringes were further classified as having low (90°) on the basis of cumulative angle changes. For the Argonne Premium coals, Pocahontas had the greatest portion of fringes with low curvature (74%), with the other coals being between 55 and 65%. In all cases, low curvature was the predominant class. High curvature contributed between 8 and 19%. The majority of the curved fringes (84 to 87%) were located in the range defined by fringes with lengths of 6.0−12.5 Å and cumulative angles of 4−125°. The Argonne Premium coals examined have similar distributions of angle change between adjacent segments. Angle changes of 10−20° account for the largest contribution. The coals had similar tortuosity distributions with fringe length. The majority of curved fringes for Argonne Premium coals (>90%) were defined by fringes with lengths of 6.0−22.5 Å and tortuosities of 1.001−2.0, while the curved fringes of anthracite with lengths of 6−52.5 Å and tortuosities of 1.001−1.5 accounted for 90%. These observations have implications for the frequency and placement of nonsix-membered rings in aromatic structures.
1. INTRODUCTION The examination of lattice fringe micrographs (obtained from image processing of high-resolution transmission electron microscopy (HRTEM) micrographs) shows that for many carbonaceous materials a significant portion of the lattice fringes have apparent curvature. The term “apparent curvature” is used here to convey the expectation that although much of this curvature is likely to be real, there are opportunities for curvature to be artificially created from both viewing angle/depth of field issues and image processing. End caps and near-neighbor atoms of nanotubes are the extreme of high curvature, ultimately allowing a transformation of 180°. For most of the curvature, it is expected that non-six-membered rings contribute,1 with the curvature extent being dependent on frequency, nature, neighbor defects, and “defect” placement. Sympathetic curvature is also possible with overlapping linear and curved polyaromatic hydrocarbon (PAH) molecules (energy minimization of the linear molecule results in a slight curvature to maximize interactions). Capturing curvature via image analysis approaches is traditionally limited to tortuosity2−7 or occasionally the curvature radius.1,3,8 Most of the work is focused on soot, with limited work3 on coal. It is expected that tortuosity from curves with single or multiple inflection points (that produce curves following a single bias) is an appropriate structural measurement. However, in the case of undulating lines, the presence of negative and positive bias does not © 2016 American Chemical Society
allow a single value to effectively capture the structure. Lattice fringes of complex carbonaceous structures (with fringes that are long enough to comprise multiple rings) are often a mixture of linear and curved fringes, with the curved fringes containing both singlebias (simple curves) and undulating structures. For soot, fringes are often well-defined around a central core. In such cases, an alternative parameter linking the length and the radius of curvature has been suggested, for which a value of 1 denotes a linear fringe and a value of 0 indicates a closed shell (circle).1,8 Here we improve upon existing image analysis techniques for undulating fringes by identifying the segment frequency, segment lengths, angles between segments, frequency of inflection points, relative locations, and overall angle changes. For consistency and comparison with the bulk of the literature, tortuosity was also determined. All of the measurements were performed on lattice fringe micrographs using an in-house MATLAB code written at the University of Nottingham.
2. METHODS Many techniques have been proposed to extract quantitative information from HRTEM lattice fringe micrographs.9−11 Here, four Argonne Premium coal samples were evaluated: Pocahontas No. 3 Received: December 13, 2015 Revised: March 7, 2016 Published: March 8, 2016 2694
DOI: 10.1021/acs.energyfuels.5b02907 Energy Fuels 2016, 30, 2694−2704
Article
Energy & Fuels
Figure 2. Initial image refinement of the lattice fringe images using standard binary morphology operations. The diagonal fill operation eliminates multiple 8-pixel connectivity while maintaining the Euler number.
Figure 3. MATLAB’s regionprops function measures the properties of connected components (8-pixel connectivity) within the image. Four separate fringes are identified in this example, each enclosed in a red bounding box. samples were analyzed likewise: Si Wang Zhang (SWZ), Men Tou Gou (MTG), and Guo Er Zhuang (GEZ). The HRTEM lattice fringe micrographs of coals were obtained as discussed by Sharma and co-workers,12,13 and a coal char micrograph was obtained from Roberts et al.14 Example HRTEM micrographs and example lattice fringe extracted images are shown in Figure 1. The original micrographs were obtained using a 200 kV transmission electron microscope (JEOL JEM2010).12 The image processing to obtain the lattice fringe images was also performed by that group utilizing an image filtration and processing approach. Distributions were obtained by evaluating three to four micrographs for each coal obtained from different coal particles in each coal. Lattice fringe images were calibrated using Photoshop and the Fovea Pro plugin suite, and fringes with lengths of 16 Å are shown for ease of viewing. The approach appropriately captures the extent of curvature and
Figure 10. Example fringes with various curvatures (black lines are the lattice fringes, and red lines are segments): (a) low-curvature fringes; (b) medium-curvature fringes; (c) high-curvature fringes.
Figure 11. Comparison of (a) fringe length and (b) cumulative angle distributions with a segment length of 4.2 Å and a minimum angle threshold of 0°. For anthracite, the combined results for the three different anthracite samples are shown. 2698
DOI: 10.1021/acs.energyfuels.5b02907 Energy Fuels 2016, 30, 2694−2704
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Energy & Fuels
Figure 12. Comparison of the distributions of angle changes between segments. For anthracite, the combined results for the three different anthracite samples are shown.
analysis was performed for BZ coal with angles between 0 and 180°. When the angle difference between adjacent segments is smaller than the minimum angle threshold, the two segments merge to form one longer segment. Figure 9a shows the expected sensitivity. It can be seen from Figure 9a that the majority of the fringes had only one segment (i.e., were linear) and that curvature was present in 50% of the curved fringes. For the Argonne Premium coals, the fringes of POC coal exhibit the least curvature followed by BZ coal. The UF and IL coals present similar fringe distributions and the highest overall extents of curvature for the curved fringes. The Argonne Premium coals have similar distributions of angle changes between adjacent segments. The frequency of inflection points first increases and then decreases with increasing angle change, and angle changes of 10−20° account for the largest portion. The majority of the curved fringes for Argonne Premium coals (84−87%) are located in the range defined by fringes with lengths of 6−12.5 Å and cumulative angles of 4−125°. These observations have implications for the frequency and placement of non-six-membered rings in aromatic structures. The Argonne Premium coal samples have similar tortuosity distributions with variation of the fringe length, while the majority of the curved fringes (>90%) are located in the range defined by fringes with lengths of 6−22.5 Å and tortuosities of 1.001−2.0. The curved fringes of anthracite having lengths of 6−52.5 Å and tortuosities of
describe more complex or undulating lines. Therefore, the use of only the tortuosity is insufficient, and quantification of the curvature can be better performed using the present enhanced image analysis approach. Ultimately, it is desirable to apply the quantification (specifically the distribution) of curvature to automated atomistic construction protocols (which possess a high degree of structural control)16−19 to improve their appropriateness and to capture the influences of curvature on char reactivity and pore shape. Other image-guided approaches also exist.5,20−23 Curvature is also of interest in a range of other fields, including plant structure/growth,24 curvature of the spine,25 and the curving and looping of blood vessels in the eye for disease detection.26 Thus, applications of an improved curvature analysis method may be beneficial elsewhere.
4. CONCLUSIONS Here a new approach for the quantification of curvature from HRTEM lattice fringe micrographs of coal has been demonstrated. The approach identifies the points of inflection, numbers of segments, segment lengths, segment centroids, and segment and 2703
DOI: 10.1021/acs.energyfuels.5b02907 Energy Fuels 2016, 30, 2694−2704
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(13) Aso, H.; Matsuoka, K.; Sharma, A.; Tomita, A. Evaluation of size of graphene sheet in anthracite by a temperature-programmed oxidation method. Energy Fuels 2004, 18 (5), 1309−1314. (14) Roberts, M. J.; Everson, R. C.; Neomagus, H.; Van Niekerk, D.; Mathews, J. P.; Branken, D. J. Influence of maceral composition on the structure, properties and behaviour of chars derived from South African coals. Fuel 2015, 142, 9−20. (15) Gaddam, C. K. Electron Microscopic and Spectroscopic Characterization for Soot Source Differentiation by Laser Derivatization. Ph.D. Thesis, The Pennsylvania State University, University Park, PA, 2015. (16) Wang, C.; Watson, J. K.; Louw, E.; Mathews, J. P. Construction strategy for atomistic models of coal chars capturing stacking diversity and pore size distribution. Energy Fuels 2015, 29, 4814−4826. (17) Huang, Y.; Cannon, F. S.; Watson, J. K.; Reznik, B.; Mathews, J. P. Activated carbon efficient atomistic model construction that depicts experimentally-determined characteristics. Carbon 2015, 83, 1−14. (18) Castro-Marcano, F.; Winans, R. E.; Chupas, P.; Chapman, K.; Calo, J. M.; Watson, J. K.; Mathews, J. P. Fine structure evaluation of the pair distribution function with molecular models of the Argonne Premium coals. Energy Fuels 2012, 26, 4336−4345. (19) Fernandez-Alos, V.; Watson, J. K.; vander Wal, R.; Mathews, J. P. Soot and char molecular representations generated directly from HRTEM lattice fringe images using Fringe3D. Combust. Flame 2011, 158 (9), 1807−1813. (20) Leyssale, J. M.; Da Costa, J. P.; Germain, C.; Weisbecker, P.; Vignoles, G. L. An image-guided atomistic reconstruction of pyrolytic carbons. Appl. Phys. Lett. 2009, 95, 231912. (21) Leyssale, J. M.; Da Costa, J. P.; Germain, C.; Weisbecker, P.; Vignoles, G. L. An atomistic reconstruction of the nanostructure of pyrolytic carbons guided by HRTEM data. MRS Symp. Proc. 2010, 1231, 50−59. (22) Leyssale, J. M.; Da Costa, J. P.; Germain, C.; Weisbecker, P.; Vignoles, G. L. Structural features of pyrocarbon atomistic models constructed from transmission electron microscopy images. Carbon 2012, 50 (12), 4388−4400. (23) Da Costa, J. P.; Weisbecker, P.; Farbos, B.; Leyssale, J. M.; Vignoles, G. L.; Germain, C. Investigating carbon materials nanostructure using image orientation statistics. Carbon 2015, 84, 160−173. (24) Basu, P.; Pal, A.; Lynch, J. P.; Brown, K. M. A novel image-analysis technique for kinematic study of growth and curvature. Plant Physiol. 2007, 145 (2), 305−316. (25) Vrtovec, T.; Likar, B.; Pernuš, F. Quantitative analysis of spinal curvature in 3D: Application to CT images of normal spine. Phys. Med. Biol. 2008, 53 (7), 1895−1908. (26) Koreen, S.; Gelman, R.; Martinez-Perez, M. E.; Jiang, L.; Berrocal, A. M.; Hess, D. J.; Flynn, J. T.; Chiang, M. F. Evaluation of a computerbased system for plus disease diagnosis in retinopathy of prematurity. Ophthalmology 2007, 114 (12), e59−67.
1.001−1.5 account for 90%. The tortuosity shows good performance for simple fringes but poor ability for more complex or undulating lines. Therefore, using only the tortuosity is insufficient, and quantification of the curvature can be better performed using the present enhanced image analysis approach. Thus, it is expected to have utility in improving the structural characterization of chars, carbons, and soots.
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AUTHOR INFORMATION
Corresponding Author
*Fax: +1 814 865 3248. E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The authors thank Drs. Atul Sharma and Mok Roberts for access to HRTEM lattice fringe micrographs. Financial support from the National Natural Science Foundation of China under Grant 51506163 and the China Scholarship Council under Grant 201406285040 is acknowledged. Also acknowledged is the European Union’s Seventh Framework Programme (FP7/ 2007−2013), Grant Agreement FP7-NMP4-LA-2012-280983, the SHYMAN Project.
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DOI: 10.1021/acs.energyfuels.5b02907 Energy Fuels 2016, 30, 2694−2704
