Automated Characterization of Chemical Bonding in Inorganic Crystals.

Abstract

We propose two interrelated projects that would (i) enhance capabilities of the UT Austin Partial Charge Analysis Code, bader, and (ii) expand the growing list of materials properties served through the AFLOW.org repositories. Specifically, the bader package will be expanded to include an analysis of the charge density critical points, through which chemical bonding can be characterized. The procedure will be integrated into the high-throughput ab-initio framework AFLOW, and validated against the plethora of compounds stored in the AFLOW.org repositories. The critical points, along with other bonding properties, will be published online via AFLOW.org and made accessible through the AFLOW RESTful API. These descriptors capture chemical information mostly orthogonal to existing properties, and thus are expected to offer substantialenhancement of machine-learning methods powering materials-design workflows.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 26, 2018
Source ID
N000141812573

Entities

People

  • Stefano Curtarolo

Organizations

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

Tags

Readers

  • Database Systems and Applications
  • Distributed Systems and Data Platform Development
  • Quantum Chemistry

Technology Areas

  • AI & ML