MRS Meetings and Events

 

DS04.10.04 2023 MRS Fall Meeting

Confocal Raman Microscopy and Machine Learning Analysis for Spatiochemical Characterization of Battery Electrodes

When and Where

Nov 29, 2023
8:00pm - 10:00pm

Hynes, Level 1, Hall A

Presenter

Co-Author(s)

Steven King1,Lei Wang2,1,Esther Takeuchi1,2,David Bock2,1,Shan Yan2,1,Amy Marschilok1,2,Kenneth Takeuchi1,2

Stony Brook University1,Brookhaven National Laboratory2

Abstract

Steven King1,Lei Wang2,1,Esther Takeuchi1,2,David Bock2,1,Shan Yan2,1,Amy Marschilok1,2,Kenneth Takeuchi1,2

Stony Brook University1,Brookhaven National Laboratory2
Battery electrodes are extremely complex and dynamic chemical environments, typically comprised of a broad range of different materials, often representing more than one chemical or physical phase, in a heterogeneous spatial configuration. Comprehensive study of such devices necessitates the use of a probe which can capture and resolve information arising from each of these physiochemical components in a way which permits consideration of the electrode as being greater than the sum of its parts. Confocal Raman microscopy provides just such a probe; it is chemically sensitive to nearly all materials regardless of their phase or crystallinity, permits spatially-constrained measurements with 3-dimensional resolution on the order of single microns, and is intrinsically capable of measuring all chemical components present in a sample in a single measurement. Moreover, the large datasets which result from such analyses are well-suited for processing using SVD-like machine learning techniques, especially non-negative matrix factorization, for rapid signal deconvolution and accurate measurement and mapping of individual chemical components. In this presentation, studies will be presented which highlight the capabilities and utility of confocal Raman microscopy combined with machine learning-assisted analysis for the study of electrodes for electrochemical energy storage devices.<br/><b>References</b><br/>(1) Lutz, D. M.; Dunkin, M. R.; King, S. T.; Stackhouse, C. A.; Kuang, J.; Du, Y.; Bak, S. M.; Bock, D. C.; Tong, X.; Ma, L.; Ehrlich, S. N.; Takeuchi, E. S.; Takeuchi, K. J.; Marschilok, A. C.; Wang, L. Hybrid MoS2+ XNanosheet/Nanocarbon Heterostructures for Lithium-Ion Batteries. <i>ACS Appl. Nano Mater.</i> <b>2022</b>, <i>5</i> (4), 5103–5118. https://doi.org/10.1021/acsanm.2c00141.<br/>(2) Zhang, X.; Hui, Z.; King, S. T.; Wu, J.; Ju, Z.; Takeuchi, K. J.; Marschilok, A. C.; West, A. C.; Takeuchi, E. S.; Wang, L.; Yu, G. Gradient Architecture Design in Scalable Porous Battery Electrodes. <i>Nano Lett.</i> <b>2022</b>, <i>22</i> (6), 2521–2528. https://doi.org/10.1021/acs.nanolett.2c00385.<br/>(3) Luo, J.; Arnot, D. J.; King, S. T.; Kingan, A.; Nicoll, A.; Tong, X.; Bock, D. C.; Takeuchi, E. S.; Marschilok, A. C.; Yan, S.; Wang, L.; Takeuchi, K. J. Two-Dimensional Siloxene Nanosheets: Impact of Morphology and Purity on Electrochemistry. <i>ACS Appl. Mater. Interfaces</i> <b>2023</b>, <i>15</i> (20), 24306–24318. https://doi.org/10.1021/acsami.3c00355.<br/>(4) Ju, Z.; King, S. T.; Xu, X.; Zhang, X.; Raigama, K. U.; Takeuchi, K. J.; Marschilok, A. C.; Wang, L.; Takeuchi, E. S.; Yu, G. Vertically Assembled Nanosheet Networks for High-Density Thick Battery Electrodes. <i>Proc. Natl. Acad. Sci. U. S. A.</i> <b>2022</b>, <i>119</i> (40), 1–9. https://doi.org/10.1073/pnas.2212777119.<br/>(5) Dunkin, M. R.; King, S. T.; Takeuchi, K. J.; Takeuchi, E. S.; Wang, L.; Marschilok, A. C. Improved Ionic Conductivity and Battery Function in a Lithium Iodide Solid Electrolyte via Particle Size Modification. <i>Electrochem. Acta</i> <b>2021</b>, <i>388</i>, 138569. https://doi.org/10.1016/j.electacta.2021.138569.

Keywords

spectroscopy

Symposium Organizers

Andrew Detor, GE Research
Jason Hattrick-Simpers, University of Toronto
Yangang Liang, Pacific Northwest National Laboratory
Doris Segets, University of Duisburg-Essen

Symposium Support

Bronze
Cohere

Publishing Alliance

MRS publishes with Springer Nature