Experimental instrumentation for Topological Decompositions and Spectral Sampling Algorithms for Element

Abstract

ABSTRACT The University of Maryland PI (Takeuchi) seeks support for instrumentation to enhance the development of novel materials-by-design efforts being carried out within the MURI program titled Topological Decompositions and Spectral Sampling Algorithms for Element Substitution in Critical Technologies (ONR N00014-13-1-0635; Program Manager: Kenny Lipkowitz). As a central part of the new methodology, the MURI team is developing an integrated approach to materials discoveries, where high-throughput computational techniques are carried out in parallel with combinatorial materials experimentation. The frequent interactions between the two paths provide critical feedback to rapidly zoom in on new compositions of functional materials with enhanced physical properties. The proposed instrumentation will allow quick screening of a variety of testbed materials systems being pursued within the MURI program including transparent conductors, ionic conductors, and battery materials. As a novel approach to data mining of materials properties, high-throughput experimental data collected using the proposed instrumentation will be combined with computational data from the AFLOWLIB.ORG for applying machine learning techniques to arrive at accurate materials predictions. The acquisition of the instrumentation will also facilitate education and training of graduate students and postdocs pursuing both experimental and computational projects.

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 12, 2016
Source ID
N000141512882

Entities

People

  • Ichiro Takeuchi

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Maryland

Tags

Readers

  • Nanocomposite Materials Science
  • Neural Network Machine Learning.
  • Research Science/Academic Research

Technology Areas

  • AI & ML