Many-Body Molecular Dynamics Simulations of Ionic Systems: From Clusters to Bulk and Interfaces

Abstract

The objective of this research is the development of a methodology for the molecular-level modeling of molecular ions with internal degrees of freedom from the gas to the condensed phase using a manybody molecular dynamics (MB-MD) approach. MB-MD combines machine-learning manybody (MB) potentials derived entirely from “first principles” with quantum molecular dynamics (MD) methods based on the path-integral formalism.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 15, 2016
Source ID
FA95501610327

Entities

People

  • Francesco Paesani

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of California, San Diego

Tags

Fields of Study

  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Distributed Systems and Data Platform Development
  • Molecular Photonics/Laser Physics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks
  • Quantum Computing
  • Quantum Science - Quantum Key Distribution