2019 MRS Spring Meeting & Exhibit

Call for Papers

Symposium GI01—Advancing Materials Discovery with Data-Driven Science (NEW!)

Artificial intelligence offers a new and broad range of tools for materials design that require a new suite of experimental and simulation tools to be successfully employed. In particular, data must be made available in larger quantities than what is produced by conventional experiments, and communicated in forms accessible to computer software as well as humans. Additionally, the increased rates at which machine learning algorithms can adapt to new data and generate improved predictions also necessitate techniques that can evaluate material properties just as quickly. In this symposium, we propose to highlight research that demonstrates the full process of machine-learning-driven materials design: from data acquisition through model development to materials design. Of particular interest will be studies that demonstrate unique approaches for leveraging the unique capabilities of artificial intelligence, which illustrate the possible transformative role of AI will play in materials research.

Topics will include:

  • Automation of experiments and computations, including advancements in software and robotics

  • Machine-learning, data-mining and materials-screening for materials discovery

  • High-throughput synthesis and in-situ characterization

  • Integrating materials data from multiple sources

  • Data parsing, digitization, structuring, storing and dissemination in materials

  • New machine-learning methods for materials science

  • Advances in materials theory relevant for data-driven discovery

Invited Speakers:

  • Curtis Berlingette (The University of British Columbia, Canada)
  • William Chueh (Stanford University, USA)
  • Jacqueline Cole (University of Cambridge, UK)
  • John Gregoire (California Institute of Technology, USA)
  • Elizabeth Holm (Carnegie Mellon University, USA)
  • Anubhav Jain (Lawrence Berkeley National Laboratory, USA)
  • Sergei Kalinin (Oak Ridge National Laboratory, USA)
  • Bryce Meredig (Citrine Informatics, USA)
  • Chad Mirkin (Northwestern University, USA)
  • Joshua Schrier (Haverford University, USA)
  • Santosh Suram (Toyota Research Institute, USA)
  • Ichiro Takeuchi (University of Maryland, USA)

Symposium Organizers

Logan Ward
University of Chicago
Computation Institute
USA
773-864-4167, loganw@uchicago.edu

Muratahan Aykol
Toyota Research Institute
USA

Jason Hattrick-Simpers
National Institute of Standards and Technology
Materials for Energy and Sustainable Development Group
USA

Elsa Olivetti
Massachusetts Institute of Technology
Department of Materials Science and Engineering
USA
617-253-0877, elsao@mit.edu