Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials.

J Chem Phys

Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, USA.

Published: April 2023

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. Our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

Download full-text PDF

Source
http://dx.doi.org/10.1063/5.0141616DOI Listing

Publication Analysis

Top Keywords

density functional
8
functional tight
8
tight binding
8
orders magnitude
8
enhancing accuracy
4
accuracy density
4
models
4
binding models
4
models chimes
4
chimes many-body
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!