Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery DOI
Daniel B. K. Chu, David Alfredo Gonzalez-Narvaez, Ralf Meyer

et al.

Journal of Chemical Information and Modeling, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

Methods that accelerate the evaluation of molecular properties are essential for chemical discovery. While some degree ligand additivity has been established transition metal complexes, it is underutilized in asymmetric such as square pyramidal coordination geometries highly relevant to catalysis. To develop predictive methods beyond simple additivity, we apply a many-body expansion octahedral and complexes introduce correction based on adjacent ligands (i.e., cis interaction model). We first test model adiabatic spin-splitting energies Fe(II) predicting DFT-calculated values unseen binary within an average error 1.4 kcal/mol. Uncertainty analysis reveals optimal basis, comprising homoleptic mer symmetric complexes. next show solved basis) infers both DFT- CCSD(T)-calculated catalytic reaction 1 kcal/mol average. The predicts low-symmetry with outside range complex energies. observe trans interactions unnecessary most monodentate systems but can be important combinations ligands, containing mixture bidentate ligands. Finally, demonstrate may combined Δ-learning predict CCSD(T) from exhaustively calculated DFT same fraction needed model, achieving around 30% using alone.

Language: Английский

PhyNEO: A Neural-Network-Enhanced Physics-Driven Force Field Development Workflow for Bulk Organic Molecule and Polymer Simulations DOI
Junmin Chen, Kuang Yu

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 20(1), P. 253 - 265

Published: Dec. 20, 2023

An accurate, generalizable, and transferable force field plays a crucial role in the molecular dynamics simulations of organic polymers biomolecules. Conventional empirical fields often fail to capture precise intermolecular interactions due their negligence important physics, such as polarization, charge penetration, many-body dispersion, etc. Moreover, parameterization these relies heavily on top-down fittings, limiting transferabilities new systems where experimental data are unavailable. To address challenges, we introduce general fully ab initio construction strategy, named PhyNEO. It features hybrid approach that combines both physics-driven data-driven methods is able generate bulk potential with chemical accuracy using only quantum chemistry very small clusters. Careful separations long-/short-range nonbonding/bonding key success By mitigate limitations pure long-range interactions, thus largely increasing efficiency scalability machine learning models. The thoroughly tested poly(ethylene oxide) polyethylene glycol systems, giving superior accuracies microscopic properties compared conventional fields. This work offers promising framework for development advanced wide range systems.

Language: Английский

Citations

11
The Near-Sightedness of Many-Body Interactions in Anharmonic Vibrational Couplings DOI
R. Spencer, Asylbek A. Zhanserkeev, Emily L. Yang

et al.

Journal of the American Chemical Society, Journal Year: 2024, Volume and Issue: 146(22), P. 15376 - 15392

Published: May 21, 2024

Couplings between vibrational motions are driven by electronic interactions, and these couplings carry special significance in energy transfer, multidimensional spectroscopy experiments, simulations of spectra. In this investigation, the many-body contributions to analyzed computationally context clathrate-like alkali metal cation hydrates, including Cs+(H2O)20, Rb+(H2O)20, K+(H2O)20, using both analytic quantum-chemistry potential surfaces. Although harmonic spectra one-dimensional anharmonic depend strongly on mode-pair were, perhaps surprisingly, found be dominated one-body effects, even cases low-frequency modes that involved motion multiple water molecules. The origin effect was traced mainly geometric distortion within monomers cancellation effects differential couplings, also shown agnostic identity ion. These outcomes provide new understanding suggest possibility improved computational methods for simulation infrared Raman

Language: Английский

Citations

3
MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations DOI
Shreya Gupta, Ethan F. Bull-Vulpe, Henry Agnew

et al.

Journal of Chemical Theory and Computation, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 14, 2025

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these functions integrate physics-based machine-learned terms trained on electronic structure data calculated at "gold standard" coupled-cluster level of theory. Recent advancements in have focused optimizing its performance, resulting release v1.2. While inherently nature ensures high accuracy, it poses computational challenges. v1.2 addresses challenges with significant performance improvements, including enhanced parallelism that fully harnesses power modern multicore CPUs. These enable simulations nanosecond time scales condensed-phase systems, significantly expanding scope high-accuracy, predictive complex systems powered by

Language: Английский

Citations

0
The evolution of machine learning potentials for molecules, reactions and materials DOI
Junfan Xia, Yaolong Zhang, Bin Jiang

et al.

Chemical Society Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

This review offers a comprehensive overview of the development machine learning potentials for molecules, reactions, and materials over past two decades, evolving from traditional models to state-of-the-art.

Language: Английский

Citations

0
Assessing the environmental influence on ‘local-monomer’ vibrational spectra via many-body potentials DOI
Alexandria G. Watrous,

Ryan P. Steele

Molecular Physics, Journal Year: 2025, Volume and Issue: unknown

Published: April 29, 2025

Language: Английский

Citations

0
A perspective marking 20 years of using permutationally invariant polynomials for molecular potentials DOI
Joel M. Bowman, Chen Qu, Riccardo Conte

et al.

The Journal of Chemical Physics, Journal Year: 2025, Volume and Issue: 162(18)

Published: May 13, 2025

This Perspective is focused on permutationally invariant polynomials (PIPs). Since their introduction in 2004 and first use developing a fully potential for the highly fluxional cation CH5+, PIPs have found widespread machine learned potentials (MLPs) isolated molecules, chemical reactions, clusters, condensed phase, materials. More than 100 been reported using PIPs. The popularity of MLPs stems from fundamental property being with respect to permutations like atoms; this energy surfaces. achieved global descriptors and, thus, without an atom-centered approach (which manifestly invariant). used directly linear regression fitting electronic energies gradients complex landscapes reactions numerous product channels. also as inputs neural network Gaussian process methods many-body (atom-centered, water monomer, etc.) applications, notably gold standard water. Here, we focus progress usage since 2018, when last review was done by our group.

Language: Английский

Citations

0
A transferrable range-separated force field for water: Combining the power of both physically-motivated models and machine learning techniques DOI
Lan Yang, Jichen Li, Feiyang Chen

et al.

The Journal of Chemical Physics, Journal Year: 2022, Volume and Issue: 157(21)

Published: Nov. 16, 2022

An accurate, transferrable, and computationally efficient potential energy surface is of paramount importance for all molecular mechanics simulations. In this work, by using water as an example, we demonstrate how one can construct a reliable force field combining the advantages both physically motivated data-driven machine learning methods. Different from existing models based on many-body expansion, adopt separation scheme that completely distances, which more convenient generic systems. The geometry dependence atomic charges dispersion coefficients are also introduced to improve accuracy long-range part potential. new provides interpretable decomposition, it accurate than conventional motived potentials. Most importantly, through study, show information learn small clusters be extrapolated into larger systems, thus providing general recipe intermolecular development at coupled-cluster singles doubles plus perturbative triples level theory in future.

Language: Английский

Citations

15
Toward Data-Driven Many-Body Simulations of Biomolecules in Solution: N-Methyl Acetamide as a Proxy for the Protein Backbone DOI
Ruihan Zhou, Marc Riera, Francesco Paesani

et al.

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(13), P. 4308 - 4321

Published: June 29, 2023

The development of molecular models with quantum-mechanical accuracy for predictive simulations biomolecular systems has been a long-standing goal in the field computational biophysics and biochemistry. As first step toward transferable force biomolecules entirely derived from "first-principles", we introduce data-driven many-body energy (MB-nrg) potential function (PEF) N-methylacetamide (NMA), peptide bond capped by two methyl groups that is commonly used as proxy protein backbone. MB-nrg PEF shown to accurately describe energetics structural properties an isolated NMA molecule, including normal modes both cis trans isomers variation along isomerization path, well multidimensional landscape NMA–H2O dimer gas phase. Importantly, show fully transferable, enabling dynamics solution accuracy. Comparisons results obtained popular pairwise-additive classical polarizable demonstrate ability represent effects interactions at short long distances, which key guaranteeing full transferability phase liquid

Language: Английский

Citations

7
Quantum phase diagram of water DOI Creative Commons
Sigbjørn Løland Bore, Francesco Paesani

Published: Jan. 11, 2023

Since the experimental characterization of low-pressure region phase diagram water in early 1900s, scientists have been on a quest to understand thermodynamic stability ice polymorphs molecular level. In this study, we demonstrate that combining MB-pol data-driven many-body potential for water, which was rigorously derived from “first principles” and exhibits chemical accuracy, with advanced enhanced-sampling algorithms, correctly describe quantum nature motion equilibria, enables computer simulations an unprecedented level realism. Besides providing unique insights into how enthalpic, entropic, nuclear effects shape free-energy landscape recent progress potentials simulation algorithms has effectively opened door realistic computational studies complex systems, thus bridging gap between experiments simulations.

Language: Английский

Citations

7
Accelerating Anharmonic Spectroscopy Simulations via Local-Mode, Multilevel Methods DOI
Asylbek A. Zhanserkeev, Emily L. Yang, Ryan P. Steele

et al.

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(16), P. 5572 - 5585

Published: Aug. 9, 2023

Ab initio computer simulations of anharmonic vibrational spectra provide nuanced insight into the behavior molecules and complexes. The computational bottleneck in such simulations, particularly for ab potentials, is often generation mode-coupling potentials. Focusing specifically on two-mode couplings this analysis, combination a local-mode representation multilevel methods demonstrated to be symbiotic. In approach, low-level quantum chemistry method employed predict pairwise that should included at target level theory self-consistent field (and similar) calculations. Pairs are excluded by approach "recycled" low theory. Furthermore, because pre-screening will eventually become sufficiently large chemical systems, distance-based truncation applied these predictions without substantive loss accuracy. This yield sub-wavenumber fidelity with reference transitions when including only small fraction target-level couplings; overhead predicting couplings, employing distance-based, cutoffs, trivial added cost. combined assessed series test cases, ethylene, hexatriene, alanine dipeptide. Vibrational (VSCF) were obtained an RI-MP2/cc-pVTZ potential dipeptide, approximately 5-fold reduction Considerable optimism increased accelerations larger systems higher-order also justified, based investigation.

Language: Английский

Citations

6