Physics-Based Approach to Computational Design of Molecular Solids
Abstract
Major Goals: The overall goal of this project is to develop a comprehensive multi-layer physics-based computational method for modeling of molecular solids that will dramatically expand the current capabilities of in silico predictions. An exhaustive plan to reach this goal contains several elements, and we advanced work on some of them during the present funding period. (a) First, have completed a project in predicting crystal structures of an energetic molecule, 4-amino-2,3,6- trinitrophenol from first-principles electronic structure calculations and molecular simulation. This physics-based approach consists of a series of steps. First, a tailor-made two-body potential energy surface was constructed with recently developed software, autoPES, using symmetry-adapted perturbation theory based on density-functional theory description of monomers [SAPT (DFT)]. The fitting procedure ensures asymptotic correctness of the PES by employing a rigorous asymptotic multipole expansion which seamlessly integrates with SAPT(DFT) interaction energies. Given the PES, crystal structure prediction is then performed by generating possible crystal structures with rigid molecules, minimizing these structures using the SAPT(DFT) force field, and running isothermal-isobaric molecular dynamics simulations with flexible molecules based on the tailor-made SAPT(DFT) intermolecular force field and a generic intramolecular one. This workflow constitutes a first-principles, bottom-up approach to CSP. In the course of this study, we demonstrated the importance of the intermolecular potential, which we found could be used with a generic bonded/intramolecular potential without significantly compromising accuracy. (b) Kohn-Sham density functional theory (DFT) is a standard tool in most branches of chemistry, but accuracies for many molecules are limited to 2-3 kcal/mol with presently-available functionals.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 30, 2022
- Accession Number
- AD1221300
Entities
People
- Mark E Tuckerman
Organizations
- New York University