Emergent Topics in Machine Learning for Molecular Systems and Materials

Presentations

• Ab initio-driven machine-learning models for aqueous systems, interfaces, and molten salts

  ORAL · Invited

  March 6, 2024, 3:00 PM – March 6, 2024, 3:36 PM

  Publication: 1. I. Sanchez-Burgos, M. C. Muniz, J. R. Espinosa, and A. Z. Panagiotopoulos, "A Deep Potential Model for Liquid-vapor Equilibrium and Cavitation Rates of Water," J. Chem. Phys. (2023). https://doi.org/10.1063/5.0144500
  2. T. E. Gartner, P. M. Piaggi, R. Car, A. Z. Panagiotopoulos and P. G. Debenedetti, "Liquid-Liquid Transition in Water from First Principles," Phys. Rev. Lett., 129: 255702 (2022). http://dx.doi.org/10.1103/PhysRevLett.129.255702
  3. R. Mathur, M. Muniz, S. Yue, R. Car, and A. Z. Panagiotopoulos, "First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2," J. Phys. Chem. B, https://doi.org/10.1021/acs.jpcb.3c04629 (2023).
  4. A. Z. Panagiotopoulos and S. Yue, "Dynamics of Aqueous Electrolyte Solutions: Challenges for Simulations," J. Phys. Chem. B 127: 430-37 (2023). https://doi.org/10.1021/acs. jpcb.2c07477
  5. P. M. Piaggi, J. Weis, A. Z. Panagiotopoulos, P. G. Debenedetti, and R. Car, "Homogeneous ice nucleation in an ab initio machine-learning model of water," Proc. Natl. Acad. Sci., 119: e2207294119 (2022). https://doi.org/10.1073/pnas.2207294119

  Presenters

  • Athanassios Panagiotopoulos

    • Princeton University

  Authors

  • Athanassios Panagiotopoulos

    • Princeton University

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• Machine learning for molecular and materials science

  ORAL · Invited

  March 6, 2024, 3:36 PM – March 6, 2024, 4:12 PM

  Presenters

  • Adrian E Roitberg

    • University of Florida

  Authors

  • Adrian E Roitberg

    • University of Florida

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• Self-assembly of electronic materials and the power of machine learning

  ORAL · Invited

  March 6, 2024, 4:12 PM – March 6, 2024, 4:48 PM

  Publication: M. Sharma Priyadarshini, O.V. Romiluyi, Y. Wang, K. Miskin, P. Clancy. A new approach to incorporate physical domain knowledge for Bayesian optimization searches in high-dimensional chemical materials system, under revision (2023)

  Presenters

  • Paulette Clancy

    • The Johns Hopkins University

  Authors

  • Paulette Clancy

    • The Johns Hopkins University

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• Exploration of New High-Entropy Materials Enabled by Quantum Computing

  ORAL · Invited

  March 6, 2024, 4:48 PM – March 6, 2024, 5:24 PM

  Presenters

  • Houlong Zhuang

    • Arizona State University

  Authors

  • Houlong Zhuang

    • Arizona State University

  • Payden Brown

    • Arizona State University

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• Mary Jo Ondrechen

  ORAL · Invited

  March 6, 2024, 5:24 PM – March 6, 2024, 6:00 PM

  Publication: "Identification and characterization of alternative sites and molecular probes for SARS-CoV-2 target proteins," Suhasini M. Iyengar, Kelly K. Barnsley, Hoang Yen Vu, Ian Jef A. Bongalonta, Alyssa S. Herrod, Jasmine A. Scott, Mary Jo Ondrechen, Frontiers in Chemistry 10, https://doi.org/10.3389/fchem.2022.1017394 (2022).
  "Functional annotation of haloacid dehalogenase superfamily structural genomics proteins," Lakindu S. Pathira Kankanamge, Lydia A. Ruffner, Mong Mary Touch, Manuel Pina, Penny J. Beuning and Mary Jo Ondrechen, Biochemical Journal 480, 1553-1569 (2023).

  Presenters

  • Mary Jo Ondrechen

    • Northeastern University

  Authors

  • Mary Jo Ondrechen

    • Northeastern University

  • Lakindu Pathira Kankanamge

    • Northeastern University

  • Atif Shafique

    • Northeastern University

  • Suhasini M Iyengar

    • Northeastern University

  • Kelly K Barnsley

    • Northeastern University

  • Penny J Beuning

    • Northeastern University

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