New methods and applications of energy decomposition analysis based on large-scale first principles quantum mechanics

Abstract

Molecular systems with functional domains serve as a practical motivation for understanding the factors that contribute to the interaction energy. The ability to decompose the interaction energy of a group of interacting subsystems is an important method in studying the chemical nature of the interactions. Energy decomposition analysis (EDA) is a family of schemes that allows such dissection of the interaction energy into chemically relevant components depending on the scheme used. Since different EDA schemes decompose the interaction energy differently, the interpretation of the resulting components differs among schemes. However, various EDA schemes provide complementary insights into the interactions between chemical entities. In this work, two EDA schemes are developed or extended: Hybrid Absolutely Localized Molecular Orbitals (HALMO) and Combined Localized Molecular Orbitals (CLMO). Both EDA schemes have been implemented as part of a linkable library alongside the computational chemistry package, ONETEP. Since ONETEP is a linear-scaling software package, an important application of such decomposition analysis is in the study of large, nontrivial molecular systems for more insightful understanding of chemical interactions, which in turn can lead to more accurate and focused design of chemical systems. Systems such as biomolecules usually contain several self-stabilizing domains that can fold independently and have important functions. Defining the fragments of a supermolecule is necessary in EDA, and if done appropriately given the context of a particular application, the fragmentation of a biomolecule can elucidate the intramolecular interactions that contribute to the functions of the system as a whole. Two major methods of self-consistent field for molecular interaction (SCF MI) are examined and made more mathematically transparent. SCF MI was originally designed to exclude basis set superposition error (BSSE) from molecular interactions. However, SCF MI is also used in separating charge transfer from polarization in HALMO EDA. Studying several SCF MI methods provides HALMO EDA alternatives for separating charge transfer as an EDA component. Due to ONETEP’s linear scaling, large biomolecules or large samples of biomolecules could be studied for their interactions or distributions of specific properties. The primary type of biomolecule studied in this work is double-stranded DNA (dsDNA) and how its stability relates to guanine-cytosine (GC) content, which is a measure of the amount of guanines or cytosines in nucleic acids. By examining the interaction energies in terms of EDA components, contributions to the variabilities within and across GC-content groups are examined and are correlated with differing stabilities despite having same GC content. Ensemble density-functional theory (EDFT) optimizes the molecular orbitals of a system at finite electronic temperatures and allows occupancies to be fractional when the band gap is sufficiently small. EDA methods are normally developed for the pure state and pose difficulties in decomposing the interaction energy of a conductor due to the fractional occupancies that are part of the optimization process in EDFT. As such, fractional occupancies have been incorporated in the EDA optimization process of the fragmented species, thereby allowing EDA to be applied to systems of relevance to catalysis and metallic systems. The adaptations of EDA and SCF MI to metallic systems are novel and were validated using samples from catalysis and batteries, and HALMO EDA has provided reasonable decompositions of interaction energies and revealed some trends from SCF MI that correlate with charge distributions and chemical intuition.

More information

Identifiers

ORCID for Han Chen: orcid.org/0000-0002-1152-7575

ORCID for Chris-Kriton Skylaris: orcid.org/0000-0003-0258-3433

Catalogue record

Export record