AI and ML for Materials Characterization and Spectroscopies

Presentations

• Toward Intelligent X-ray Spectroscopy: An Agentic AI Platform for Automated and Multimodal Analysis

  Invited-In-person · Invited

  March 16, 2026, 8:00 AM – March 16, 2026, 8:36 AM

  Presenters

  • Juanjuan Huang

    • Argonne National Laboratory

  Authors

  • Juanjuan Huang

    • Argonne National Laboratory

  • Xufan Lu

  • Nina Andrejevic

    • Argonne National Laboratory

  • Hassan Harb

  • Yanna Chen

    • Canadian Light Source

  • Shelly Kelly

    • Argonne National Laboratory

  • George Sterbinsky

    • Argonne National Laboratory

  • Mark Wolfman

  • Luca Rebuffi

  • Mathew Cherukara

  • Ryotaro Okabe

    • Massachusetts Institute of Technology

  View abstract →

• TIDMAD: A Sandbox for Physics-Informed LLM Agents in Dark Matter Searches

  Invited-In-person · Invited

  March 16, 2026, 8:36 AM – March 16, 2026, 9:12 AM

  Publication: Fry, J. T., Fu, X. H., Fu, Z., West Pappas, K. M., Winslow, L., & Li, A. (2025).
  Tidmad: Time series dataset for discovering dark matter with AI denoising.
  To appear in Advances in Neural Information Processing Systems. Spotlight.
  OpenReview preprint retrieved from openreview.net.

  Presenters

  • Yue Ma

    • University of California, San Diego

  Authors

  • Yue Ma

    • University of California, San Diego

  • Aobo Li

    • University of California, San Diego

  View abstract →

• Data-efficient surrogate modeling of spectral functions using Gaussian processes: An application to the t-t′-t′′-J model

  Oral-In-person

  March 16, 2026, 9:12 AM – March 16, 2026, 9:24 AM

  Publication: Data-efficient surrogate modeling of spectral functions using Gaussian processes: An application to the t-t′-t′′-J model, N. Aryal, S. Jantre, N. Urban, W, Yin, In preparation.

  Presenters

  • Niraj Aryal

    • Brookhaven National Laboratory (BNL)

  Authors

  • Niraj Aryal

    • Brookhaven National Laboratory (BNL)

  • Weiguo Yin

    • Brookhaven National Laboratory (BNL)

  View abstract →

• Autonomous Bayesian Optimization for Physics-Guided Discovery in Functional Materials

  Oral-In-person

  March 16, 2026, 9:24 AM – March 16, 2026, 9:36 AM

  Presenters

  • Kamyar Barakati

    • University Tennessee-Knoxville

  Authors

  • Kamyar Barakati

    • University Tennessee-Knoxville

  • Haochen Zhu

  • Philip Rack

  • Yu Liu

  • Sergei Kalinin

    • University of Tennessee

  View abstract →

• Restricted Boltzmann Machines as Robust Generative Surrogates for Spectral-Function: An application to the t − t′ − t′′ − J model

  Oral-In-person

  March 16, 2026, 9:36 AM – March 16, 2026, 9:48 AM

  Presenters

  • Maximilian Cederholm

  Authors

  • Niraj Aryal

    • Brookhaven National Laboratory (BNL)

  • Maximilian Cederholm

  View abstract →

• Deep Learning for X-ray-Based Material Analysis and CNN Approaches.

  Oral-In-person

  March 16, 2026, 9:48 AM – March 16, 2026, 10:00 AM

  Presenters

  • Chethana Johannas

    • Mid Sweden University (Mittuniversitetet)

  Authors

  • Chethana Johannas

    • Mid Sweden University (Mittuniversitetet)

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• Hamiltonian parameter inference from resonant inelastic x-ray scattering with active learning

  Oral-In-person

  March 16, 2026, 10:00 AM – March 16, 2026, 10:12 AM

  Publication: Physical Review B
  https://doi.org/10.1103/tnqm-ttj3
  
  arxiv preprint: 2507.16021

  Presenters

  • Marton Kalman Lajer

    • Brookhaven National Laboratory

  Authors

  • Marton Kalman Lajer

    • Brookhaven National Laboratory

  • Xin Dai

  • Kipton Barros

    • Los Alamos National Lab

  • Matthew Carbone

    • Brookhaven National Lab

  • Steven Johnston

    • University of Tennessee

  • Mark Dean

    • Brookhaven National Laboratory (BNL)

  View abstract →

• Improving Spectral Resolution from Real-Time Evolution for Correlated Systems

  Oral-In-person

  March 16, 2026, 10:12 AM – March 16, 2026, 10:24 AM

  Publication: arXiv:2509.15539 [cond-mat.str-el]

  Presenters

  • Brian Moritz

    • SLAC National Accelerator Laboratory

  Authors

  • Brian Moritz

    • SLAC National Accelerator Laboratory

  • Ta Tang

    • Stanford University

  • Chunjing Jia

    • University of Florida

  • Thomas Devereaux

    • Stanford University

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• Attention is not all you need: Comparing the performance of transformers and CNNs in classifying space groups from powder diffraction data

  Oral-In-person

  March 16, 2026, 10:24 AM – March 16, 2026, 10:36 AM

  Presenters

  • William Ratcliff

    • National Institute of Standards and Technology (NIST)

  Authors

  • William Ratcliff

    • National Institute of Standards and Technology (NIST)

  • Elizabeth Baggett

    • Boston College

  • Edward Friedmann

  • Vanellsa Acha

  • Derrick Chan-Sew

  • Abhishek Shetty

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• Symmetry-constrained machine learning on 3D-ΔPDF to identify short range correlations

  Oral-In-person

  March 16, 2026, 10:36 AM – March 16, 2026, 10:48 AM

  Presenters

  • Yusu Wang

    • Argonne National Laboratory

  Authors

  • Yusu Wang

    • Argonne National Laboratory

  • Zachary Anderson

    • Argonne National Laboratory, Materials Science Division

  • Vishwas Rao

  • Mihai Anitescu

  • Stephan Rosenkranz

    • Argonne National Laboratory

  • Raymond Osborn

    • Argonne National Laboratory

  View abstract →

• Alexandria 2.0: AI-Driven Discovery and Open Data Infrastructure for Materials Design

  Oral-In-person

  March 16, 2026, 10:48 AM – March 16, 2026, 11:00 AM

  Publication: AI-Driven Expansion of the Alexandria Database, to be submitted.

  Presenters

  • Aldo Romero

    • West Virginia University

  Authors

  • Aldo Romero

    • West Virginia University

  • Theo Cavignac

  • Jonathan Schmidt

  • Pierre-Paul De Breuck

    • Universite catholique de Louvain

  • Antoine Loew

  • Tiago F. T. Cerqueira

  • Hai-Chen Wang

  • Silvana Botti

  • Miguel A. L. Marques

  View abstract →