Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session B43: Inverse Problems: From Biomedicine to Materials
11:30 AM–2:30 PM,
Monday, March 14, 2022
Room: McCormick Place W-375B
Sponsoring
Units:
GMED DCOMP
Chair: Wojciech Zbijewski, Johns Hopkins University
Abstract: B43.00004 : Materials physics from microscopy: statistical and machine learning methods for tackling inverse problems
1:18 PM–1:54 PM
Presenter:
Rama K Vasudevan
(Oak Ridge National Laboratory)
Author:
Rama K Vasudevan
(Oak Ridge National Laboratory)
In this talk, I will highlight our recent advances at both accelerating knowledge acquisition through Bayesian optimization methods, as well as providing better insight into materials physics via Bayesian inference, Bayesian model selection, and statistical physics-based methods. Generative models that combine both local and global characterization data allow ‘stochastic’ model matching by comparing statistics of between target configurations and model predictions at the atomic and mesoscopic scale, and promise the ability to autonomously guide sample characterization towards proving or disproving available models describing the system and its dynamics. These improvements suggest that the next decade of microscopy will be greatly enriched by a close coupling between analytics at the edge, computational modeling, and machine learning methods. This work was conducted at and supported (RKV) at the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory, a US DOE Office of Science User Facility.
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