Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

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A neural network potential energy surface for the NaH 2 system and dynamics studies on the H( 2 S) + NaH(X 1 Σ + ) → Na( 2 S) + H 2 (X 1 Σ g + ) reaction

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Insight into the Solvation Structure of Tetraglyme-Based Electrolytes via First-Principles Molecular Dynamics Simulation

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Neural Network Based in Silico Simulation of Combustion ReactionsPreprint

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TensorAlloy: An automatic atomistic neural network program for alloys

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Storage and diffusion of CO2 in covalent organic frameworks—A neural network-based molecular dynamics simulation approach

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Hydrogen-induced degradation dynamics in silicon heterojunction solar cells via machine learning

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Reactive Many-Body Expansion for a Protonated Water Cluster

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Role of structural symmetry breaking in the structurally induced robust superlubricity of graphene and h-BN homo- and hetero-junctions

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Sampling algorithms for validation of supervised learning models for Ising-like systems

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Modeling the Complex Adsorption Dynamics of Large Organic Molecules: Cyclooctyne on Si(001)

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Constructing feed-forward artificial neural networks to fit potential energy surfaces for molecular simulation of high-temperature gas flows

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Fitting potential energy surfaces to sum-of-products form with neural networks using exponential neurons

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Classification of spatially resolved molecular fingerprints for machine learning applications and development of a codebase for their implementation

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TensorKMC

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Neural Network Potentials in Materials Modeling

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GPU-accelerated artificial neural network potential for molecular dynamics simulation

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Accelerating training of MLIPs through small-cell training

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Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter

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Machine-learned atomic cluster expansion potentials for fast and quantum-accurate thermal simulations of wurtzite AlN

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Modeling Gas Adsorption and Mechanistic Insights into Flexibility in Isoreticular Metal–Organic Frameworks Using High-Dimensional Neural Network Potentials

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Reproducing global potential energy surfaces with continuous-filter convolutional neural networks

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Machine learning approach for describing vibrational solvatochromism

Kwac, K., & Cho, M. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0005591 · Cited by 16

Machine learning phase space quantum dynamics approaches

Liu, X., Zhang, L., & Liu, J. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0046689 · Cited by 16

A neural network potential for searching the atomic structures of pure and mixed nanoparticles. Application to ZnMg nanoalloys with an eye on their anticorrosive properties

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Closing the Gap Between Modeling and Experiments in the Self-Assembly of Biomolecules at Interfaces and in Solution

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Classification of clusters in collision cascades

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Investigation of adsorption of Fluorouracil as anticancer drug on C82, Si82, Ti-C82 and Ti-Si82 nanocages

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Toward fast and accurate machine learning interatomic potentials for atomic layer deposition precursors

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No Headache for PIPs: A PIP Potential for Aspirin Runs Much Faster and with Similar Precision Than Other Machine-Learned Potentials

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Hydrogen diffusion on Ni(100): A combined machine-learning, ring polymer molecular dynamics, and kinetic Monte Carlo study

Steffen, J., & Alibakhshi, A. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0226314 · Cited by 15

Melting simulations of high-entropy carbonitrides by deep learning potentials

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Application of First-Principles-Based Artificial Neural Network Potentials to Multiscale-Shock Dynamics Simulations on Solid Materials

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Neural network potential for studying the thermal conductivity of Sn

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Ready, Set and no Action: A Static Perspective on Potential Energy Surfaces commonly used in Gas-Surface Dynamics

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A neural-network potential through charge equilibration for WS2: From clusters to sheets

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In‐Depth Knowledge of Strong Metal‐Support Interaction Effect in Heterogeneous Catalysis

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MLRNet: Combining the Physics-Motivated Potential Models with Neural Networks for Intermolecular Potential Energy Surface Construction

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Prediction of thermal conductivity in CALF-20 with first-principles accuracy via machine learning interatomic potentials

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H + H2 quantum dynamics using potential energy surfaces based on the XYG3 type of doubly hybrid density functionals: Validation of the density functionals

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A six-dimensional potential energy surface for Ru(0001)(2×2):CO

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Using principal component analysis for neural network high-dimensional potential energy surface

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Time-dependent density matrix renormalization group coupled with n -mode representation potentials for the excited state radiationless decay rate: Formalism and application to azulene

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Conical intersection seams in spin–orbit coupled systems with an even number of electrons: A numerical study based on neural network fit surfaces

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Mechanical Properties of Single and Polycrystalline Solids from Machine Learning

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Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights

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Halide-Induced Step Faceting and Dissolution Energetics from Atomistic Machine Learned Potentials on Cu(100)

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MULTIMODE Calculations of Vibrational Spectroscopy and 1d Interconformer Tunneling Dynamics in Glycine Using a Full-Dimensional Potential Energy Surface

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Multitask Deep Ensemble Prediction of Molecular Energetics in Solution: From Quantum Mechanics to Experimental Properties

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Ultrafast Electronic Coupling Estimators: Neural Networks versus Physics-Based Approaches

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New Algorithms to Generate Permutationally Invariant Polynomials and Fundamental Invariants for Potential Energy Surface Fitting

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Outlier-detection for reactive machine learned potential energy surfaces

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Dynamically Polarizable Force Fields for Surface Simulations via Multi-output Classification Neural Networks

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Machine Learning and Big-Data in Computational Chemistry

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Ab Initio Investigation of O–H Dissociation from the Al–OH 2 Complex Using Molecular Dynamics and Neural Network Fitting

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Artificial Neural Networks as Mappings between Proton Potentials, Wave Functions, Densities, and Energy Levels

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Three-dimensional diabatic potential energy surfaces of thiophenol with neural networks

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Steric Effects in CO Oxidation on Pt(111) by Impinging Oxygen Atoms Lead to an Exclusive Hot Atom Mechanism

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Application of modern artificial intelligence techniques in the development of organic molecular force fields

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Enabling Rapid and Accurate Construction of CCSD(T)-Level Potential Energy Surface of Large Molecules Using Molecular Tailoring Approach

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Quantum Gaussian process model of potential energy surface for a polyatomic molecule

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Machine Learning and Big-Data in Computational Chemistry

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Physics-based, neural network force fields for reactive molecular dynamics: Investigation of carbene formation from [EMIM+][OAc−]

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Machine Learning Forces Trained by Gaussian Process in Liquid States: Transferability to Temperature and Pressure

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A potential function of MoS2 based on machine learning

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Transfer learning for predicting reorganization energy

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Partial melting nature of phase-change memory Ge-Sb-Te superlattice uncovered by large-scale machine learning interatomic potential molecular dynamics

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Near Spectroscopically Accurate Ab Initio Potential Energy Surface for NH4+ and Variational Calculations of Low-Lying Vibrational Levels

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Machine learning enhanced empirical potentials for metals and alloys

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Taking materials dynamics to new extremes using machine learning interatomic potentials

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Machine-learning-assisted molecular design of phenylnaphthylamine-type antioxidants

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Neural Network Prediction of Interatomic Interaction in Multielement Substances and High-Entropy Alloys: A Review

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Thermal transport across TiO2–H2O interface involving water dissociation: Ab initio-assisted deep potential molecular dynamics

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Photodesorption of water from rutile(110): ab initio calculation of five-dimensional potential energy surfaces of ground and excited electronic states and wave packet studies

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Dynamics of carbon monoxide dissociation on Co(1120)

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Artificial neural network for the configuration problem in solids

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VIB5 database with accurate ab initio quantum chemical molecular potential energy surfaces

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Global optimization of Tan clusters by deep neural network

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Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

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Gaussian process regression adaptive density-guided approach: Toward calculations of potential energy surfaces for larger molecules

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Dynamics Studies of O2 Collision on Pt(111) Using a Global Potential Energy Surface

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Rapid enthalpy prediction of transition states using molecular graph convolutional network

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