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Symposium MD02-Data-Driven Multiscale Studies of Materials—Computations and Experiments

Multiscale methods have been widely used in material studies, allowing us to gain insights into material behaviors at quantum, atomistic, micro-, meso- and macro-scales. The recent developments in data-driven methods, such as machine learning and artificial intelligence, and their integration with multiscale approaches are creating new research opportunities. Data-driven multiscale studies of materials have shown promising results in developing interatomic potentials for atomistic modeling, designing new materials, discovering new constitutive laws, identifying processing-structure-performance correlations, and analyzing microscopy images, among many others. In this symposium, we will include the new developments of data-driven methods in computational and experimental studies of materials, the data-driven studies crossing different scales, the studies bridging computations and experiments, and the new understandings of material behaviors enabled by the data-driven multiscale methods. This symposium will bring together researchers from a broad spectrum of disciplines with a data- or multiscale-relevant component in their research to exchange research progress and inspire new research ideas.









Topics will include:

  • Data-driven design of new materials
  • Data-driven characterization of materials
  • Data-driven identification of constitutive relations
  • Process-structure-performance correlations
  • The development of new data-driven methods for material studies
  • Machine-learning potentials for atomistic simulations
  • Model-order reduction in multiscale computations
  • Uncertainty quantifications in multiscale computations
  • Scale-bridging methods for material studies

Invited Speakers:

  • Christos Athanasiou (Georgia Institute of Technology, USA)
  • Ivano E. Castelli (Technical University of Denmark, Denmark)
  • Victor Fung (Oak Ridge National Laboratory, USA)
  • Wei Gao (Texas A&M University, USA)
  • Johann Guilleminot (Duke University, USA)
  • Ozgur Keles (San Jose State University, USA)
  • John Lambros (University of Illinois at Urbana-Champaign, USA)
  • Yen Ting Lin (Los Alamos National Laboratory, USA)
  • Nithin Mathew (Los Alamos National Laboratory, USA)
  • Shyue Ping Ong (University of California, San Diego, USA)
  • Danny Perez (Los Alamos National Laboratory, USA)
  • Brandon Runnels (University of Colorado Colorado Springs, USA)
  • Aidan Thompson (Sandia National Laboratories, USA)
  • Wenbin Yu (Purdue University, USA)

Symposium Organizers

Haoran Wang
Utah State University
Department of Mechanical and Aerospace Engineering
USA
No Phone for Symposium Organizer Provided , haoran.wang@usu.edu

Soumendu Bagchi
Los Alamos National Laboratory
USA
No Phone for Symposium Organizer Provided , sbagchi@lanl.gov

Huck Beng Chew
University of Illinois at Urbana-Champaign
Department of Aerospace Engineering
USA
No Phone for Symposium Organizer Provided , hbchew@illinois.edu

Jiaxin Zhang
Oak Ridge National Laboratory
Computer Science and Mathematics Division
USA
No Phone for Symposium Organizer Provided , zhangj@ornl.gov

Publishing Alliance

MRS publishes with Springer Nature