Dataset Information

Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom Acetylacetone.

ABSTRACT: Machine-learned potential energy surfaces (PESs) for molecules with more than 10 atoms are typically forced to use lower-level electronic structure methods such as density functional theory (DFT) and second-order Møller-Plesset perturbation theory (MP2). While these are efficient and realistic, they fall short of the accuracy of the "gold standard" coupled-cluster method, especially with respect to reaction and isomerization barriers. We report a major step forward in applying a Δ-machine learning method to the challenging case of acetylacetone, whose MP2 barrier height for H-atom transfer is low by roughly 1.1 kcal/mol relative to the benchmark CCSD(T) barrier of 3.2 kcal/mol. From a database of 2151 local CCSD(T) energies and training with as few as 430 energies, we obtain a new PES with a barrier of 3.5 kcal/mol in agreement with the LCCSD(T) barrier of 3.5 kcal/mol and close to the benchmark value. Tunneling splittings due to H-atom transfer are calculated using this new PES, providing improved estimates over previous ones obtained using an MP2-based PES.

SUBMITTER: Qu C

PROVIDER: S-EPMC8279733 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom Acetylacetone.

Qu Chen C Houston Paul L PL Conte Riccardo R Nandi Apurba A Bowman Joel M JM

The journal of physical chemistry letters 20210518 20

Machine-learned potential energy surfaces (PESs) for molecules with more than 10 atoms are typically forced to use lower-level electronic structure methods such as density functional theory (DFT) and second-order Møller-Plesset perturbation theory (MP2). While these are efficient and realistic, they fall short of the accuracy of the "gold standard" coupled-cluster method, especially with respect to reaction and isomerization barriers. We report a major step forward in applying a Δ-machine learni ...[more]

PMID: 34006096

Similar Datasets

Project description:Semilocal and random phase approximation (RPA) density functional theory (DFT) and complete active space (CASSCF + NEVPT2) methodologies were applied to investigate a new class of extended metal atom chain (EMAC) complexes. A novel triferrous complex has been synthesized recently that does not utilize the usual 2,2'-dipyridylamine (dpa) ligand framework, which essentially always results in a tetragonal coordination environment and general formula M3(dpa)4X2, where X is an anion. Instead, the triferrous complex utilizes a dianionic, 2,6-bis(trimethylsilylamido)pyridine ligand (L2-) resulting in the formation of trigonal complexes with general formula Fe3L3. To better understand the electronic structure of this complex, calculations were utilized to explore the experimentally isolated Fe3L3, and a smaller theoretical complex, in order to compare and contrast with the traditional dpa-based EMACs. Due to the absence of anionic, axial ligands, the sigma nonbonding orbitals formed from the metal d orbitals are lower in energy than in the dpa complexes, and compete with the pi bonding orbitals for occupation in the Fe3L3 complex. While the idealized geometry of these complexes is D3h, a helical distortion of the ligands and subsequent electronic symmetry breaking due to Jahn-Teller distortions are predicted utilizing both semilocal and RPA DFT methods, ending in a C2 structure that closely matches the reported crystal structure. Predicted Mössbauer isomer shifts and ultraviolet/visible (UV/vis) spectra also agree with the experimental data available in the literature. Magnetic coupling constants also indicate ferromagnetic coupling between nearest neighbor irons. Two-dimensional (2D) potential energy surfaces were calculated for a range of fixed Fe-Fe bond lengths, revealing a flat potential energy surface over a wide range of Fe-Fe bond lengths and verifying the ability of RPA to act as a higher-level check on semilocal DFT results. In order to verify the predicted high-spin ground state, CASSCF + NEVPT2 was applied to selected molecular configurations and confirmed the predictions made by DFT. These calculations shed light on the physical ground state electron configuration of Fe3L3 and correlate this electronic configuration with the available experimental data.

Project description:We selected 145 reference organic molecules that include model fragments used in computer-aided drug design. We calculated 158 conformational energies and barriers using force fields, with wide applicability in commercial and free softwares and extensive application on the calculation of conformational energies of organic molecules, e.g. the UFF and DREIDING force fields, the Allinger's force fields MM3-96, MM3-00, MM4-8, the MM2-91 clones MMX and MM+, the MMFF94 force field, MM4, ab initio Hartree-Fock (HF) theory with different basis sets, the standard density functional theory B3LYP, the second-order post-HF MP2 theory and the Domain-based Local Pair Natural Orbital Coupled Cluster DLPNO-CCSD(T) theory, with the latter used for accurate reference values. The data set of the organic molecules includes hydrocarbons, haloalkanes, conjugated compounds, and oxygen-, nitrogen-, phosphorus- and sulphur-containing compounds. We reviewed in detail the conformational aspects of these model organic molecules providing the current understanding of the steric and electronic factors that determine the stability of low energy conformers and the literature including previous experimental observations and calculated findings. While progress on the computer hardware allows the calculations of thousands of conformations for later use in drug design projects, this study is an update from previous classical studies that used, as reference values, experimental ones using a variety of methods and different environments. The lowest mean error against the DLPNO-CCSD(T) reference was calculated for MP2 (0.35 kcal mol-1), followed by B3LYP (0.69 kcal mol-1) and the HF theories (0.81-1.0 kcal mol-1). As regards the force fields, the lowest errors were observed for the Allinger's force fields MM3-00 (1.28 kcal mol-1), ΜΜ3-96 (1.40 kcal mol-1) and the Halgren's MMFF94 force field (1.30 kcal mol-1) and then for the MM2-91 clones MMX (1.77 kcal mol-1) and MM+ (2.01 kcal mol-1) and MM4 (2.05 kcal mol-1). The DREIDING (3.63 kcal mol-1) and UFF (3.77 kcal mol-1) force fields have the lowest performance. These model organic molecules we used are often present as fragments in drug-like molecules. The values calculated using DLPNO-CCSD(T) make up a valuable data set for further comparisons and for improved force field parameterization.

Dataset Information

Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom Acetylacetone.

Publications

Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom Acetylacetone.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets