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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Forces from Stochastic Density Functional Theory under Nonorthogonal Atom-Centered Basis Sets.

Ben Shpiro¹, Marcel David Fabian¹, Eran Rabani^2,3,4

¹Fritz Haber Center for Molecular Dynamics and Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.

Journal of Chemical Theory and Computation

|January 31, 2022

Summary

This summary is machine-generated.

We developed a method for calculating nuclear forces using linear-scaling stochastic density functional theory (sDFT). This approach minimizes statistical errors, ensuring accurate molecular simulations for systems like the Trp-zip2 peptide.

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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Area of Science:

Computational Chemistry
Quantum Chemistry
Materials Science

Background:

Linear-scaling stochastic density functional theory (sDFT) offers a computationally efficient approach for large molecular systems.
Accurate calculation of forces on nuclei is crucial for molecular dynamics simulations and predicting molecular properties.
Nonorthogonal atom-centered basis sets are often employed in electronic structure calculations.

Purpose of the Study:

To develop and validate a formalism for calculating nuclear forces within linear-scaling sDFT using a nonorthogonal basis set.
To assess the accuracy and statistical errors of the developed method when applied to a realistic peptide system.
To determine the feasibility of using sDFT for reliable molecular dynamics simulations.

Main Methods:

Development of a formalism for force calculations in linear-scaling sDFT.
Application of an embedded-fragment approach to mitigate statistical errors.
Systematic analysis of statistical errors, including fluctuation and systematic bias.
Langevin molecular dynamics simulations using sDFT-calculated forces.

Main Results:

The developed formalism enables force calculations in linear-scaling sDFT with nonorthogonal basis sets.
An embedded-fragment approach effectively reduces statistical errors.
A systematic bias of approximately 0.065 eV/Å was observed with 120 stochastic orbitals, independent of system size.
The calculated bias is small enough to ensure bond length deviations below 1% compared to deterministic methods.

Conclusions:

The developed sDFT formalism provides accurate nuclear forces for molecular simulations.
The embedded-fragment approach is effective in controlling statistical errors in sDFT.
Stochastic DFT is a viable and accurate method for molecular dynamics simulations of complex systems like peptides.