Materials Science and Spectroscopy Using Deep Learning
FOCUS · MAR-G37 · ID: 3091570
Presentations
-
Physics-Guided Machine Learning Framework for Real-Time Multi-Scale Materials Characterization at Light Sources
ORAL · Invited
–
Publication: https://doi.org/10.1063/5.0132433<br>https://link.springer.com/article/10.1007/s11837-021-04889-3<br>https://doi.org/10.1016/j.scriptamat.2020.10.028<br>https://doi.org/10.1063/5.0014725<br>https://doi.org/10.1016/j.actamat.2019.03.026<br>https://doi.org/10.21203/rs.3.rs-4555290/v1
Presenters
-
Reeju Pokharel
Los Alamos National Laboratory
Authors
-
Alexander Scheinker
Los Alamos National Laboratory (LANL)
-
Reeju Pokharel
Los Alamos National Laboratory
-
-
Novel approaches to studying frustrated charge interactions in strongly correlated materials
ORAL · Invited
–
Publication: S. J. Gomez Alvarado, G. Pokharel, B. R. Ortiz, J. A. M. Paddison, S. Sarker, J. P. C. Ruff, and S. D. Wilson, Frustrated Ising charge correlations in the kagome metal ScV6Sn6. Phys. Rev. B 110 (2024) L140304. [DOI: 10.1103/PhysRevB.110.L140304] [arXiv: 2407.12099]<br><br>S. J. Gomez Alvarado, J. R. Chamorro, A. R. Jackson, G. Pokharel, R. Gomez, B. R. Ortiz, S. Sarker, L. Kautzsch, L. Gallington, R. Seshadri, and S. D. Wilson, Interleaved lattice and magnetic frustration in LnCd3P3 (Ln = La, Ce, Pr, Nd). (In preparation)
Presenters
-
Steven J Gomez Alvarado
University of California, Santa Barbara, Materials Department, University of California, Santa Barbara, CA 93106-5050, U.S.A.
Authors
-
Steven J Gomez Alvarado
University of California, Santa Barbara, Materials Department, University of California, Santa Barbara, CA 93106-5050, U.S.A.
-
-
Graph and Generative Large Language Models for Data-Driven Materials Discovery
ORAL
–
Presenters
-
Yong Wei
University of North Georgia
Authors
-
Yong Wei
University of North Georgia
-
Mingyuan Yan
University of North Georgia
-
Yuewei Lin
Brookhaven National Laboratory
-
Hanning Chen
University of Texas at Austin
-
-
Abstract Withdrawn
ORAL Withdrawn
–
-
Leveraging Generative AI for Stress Prediction and Design of Architected Graphene Structures
ORAL
–
Publication: Masrouri, Milad, Kamalendu Paul, and Zhao Qin. "Generative AI model trained by molecular dynamics for rapid mechanical design of architected graphene." Extreme Mechanics Letters 72 (2024): 102230.
Presenters
-
Kamalendu Paul
Syracuse University
Authors
-
Kamalendu Paul
Syracuse University
-
Milad Masrouri
Syracuse University
-
Zhao Qin
Syracuse University
-
-
Prediction of Frictional Contact Networks Using Deep Graph Convolutional Neural Network in Dense Suspensions. Part 1: Methods and Scalability
ORAL
–
Publication: 1- A. Aminimajd, J. Maia, A. Singh, "Scalability of Graph Neural Network in Accurate Prediction of Force Chain Network in Suspensions.", Physical Review Letter (Under Review)<br>2- https://arxiv.org/abs/2409.13160
Presenters
-
Armin Aminimajd
Case Western Reserve University
Authors
-
Armin Aminimajd
Case Western Reserve University
-
Joao M Maia
Case Western Reserve University
-
Abhinendra Singh
Case Western Reserve University
-
-
Abstract Withdrawn
ORAL Withdrawn
–
-
Deep Learning Approach to Identifying New Infrared Spectroscopic Features Produced by Accelerated Aging of Cross-linked Polyethylene Pipe
ORAL
–
Publication: [1] M. Grossutti et al., ACS Appl. Mater. Interfaces 15, 22532 (2023).
Presenters
-
Zachery Evans
University of Guelph
Authors
-
Zachery Evans
University of Guelph
-
Isaac Mercier
University of Guelph
-
Lauren Kauth
University of Waterloo
-
Michael Grossutti
University of Guelph
-
John R Dutcher
University of Guelph
-
-
Abstract Withdrawn
ORAL Withdrawn
–