LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

2021/09/22 by Aidan P. Thompson, Hasan Metin Aktulga, H. Metin Aktulga +20 · 11,982 citations
Biochemistry, Genetics and Molecular Biology · Materials Science · #Advanced Electron Microscopy Techniques and Applications #Atomic model #Computational science #Computer science #Electron and X-Ray Spectroscopy Techniques #Flexibility (engineering) #Fortran #Machine Learning in Materials Science #Massively parallel #Molecular dynamics #Parallel computing #Physics #Programming language #Python (programming language) #Source code

paper · pdf · doi:10.1016/j.cpc.2021.108171

published in Computer Physics Communications 271, 108171 (Elsevier BV)

openalex publication_date 2021/09/22 · openalex created_date 2021/09/27 · openalex updated_date 2026/08/05

Abstract

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials. Program Title: Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) CPC Library link to program files: 10.17632/cxbxs9btsv.1 Developer's repository link: https://github.com/lammps/lammps Licensing provisions: GPLv2 Programming language: C++, Python, C, Fortran Supplementary material: https://www.lammps.org Nature of problem: Many science applications in physics, chemistry, materials science, and related fields require parallel, scalable, and efficient generation of long, stable classical particle dynamics trajectories. Within this common problem definition, there lies a great diversity of use cases, distinguished by different particle interaction models, external constraints, as well as timescales and lengthscales ranging from atomic to mesoscale to macroscopic. Solution method: The LAMMPS code uses parallel spatial decomposition, distributed neighbor lists, and parallel FFTs for long-range Coulombic interactions [1]. The time integration algorithm is based on the Størmer-Verlet symplectic integrator [2], which provides better stability than higher-order non-symplectic methods. In addition, LAMMPS supports a wide range of interatomic potentials, constraints, diagnostics, software interfaces, and pre- and post-processing features. Additional comments including restrictions and unusual features: This paper serves as the definitive reference for the LAMMPS code. S. Plimpton, Fast parallel algorithms for short-range molecular dynamics. J. Comp. Phys. 117 (1995) 1–19. L. Verlet, Computer experiments on classical fluids: I. Thermodynamical properties of Lennard–Jones molecules, Phys. Rev. 159 (1967) 98–103.

Citations

• Electronegativity: The density functional viewpoint
• Correlations in the Motion of Atoms in Liquid Argon
• Aspherical particle models for molecular dynamics simulation

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• Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials
• FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials
• Phase behavior and dynamics of active Brownian particles in an alignment field
• Charging and discharging a supercapacitor in molecular simulations
• Surface stratification determines the interfacial water structure of simple electrolyte solutions
• Graph atomic cluster expansion for foundational machine learning interatomic potentials
• Trefoil polymers from a knotted synthon
• A foundation model for atomistic materials chemistry
• Atomistic mechanisms of oxidation and chlorine corrosion in Ni-based superalloys: The role of boron and light interstitial segregation
• Water structuring at stacked graphene interfaces unveiled by machine-learning molecular dynamics
• Twist-angle transferable continuum model and second flat Chern band in twisted MoTe2 and WSe2
• Intermittent Viscoelastic Turbulence in Strongly Coupled Plasmas
• Bridging Simulation and Silicon: A Study of RISC-V Hardware and FireSim Simulation
• Interface and Thermophysical Properties of R32 Refrigerant
• How Realistic are Idealized Copper Surfaces? A Machine Learning Study of Rough Copper-Water Interfaces
• Incorporating Coulomb interactions with fixed charges in Moment Tensor Potentials and Equivariant Tensor Network Potentials
• Vibrational Fingerprints of Strained Polymers: A Spectroscopic Pathway to Mechanical State Prediction
• A universal machine learning model for the electronic density of states
• Inverse Design of Amorphous Materials with Targeted Properties
• Using molecular dynamics to investigate the driving force for graphene auto-kirigami
• Benchmarking thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former model
• Spectral Analysis of Light Interstitial Segregation Energies in Ni: The Role of Local Cr Coordination for Boron and Carbon
• Descriptor and Graph-based Molecular Representations in Prediction of Copolymer Properties Using Machine Learning
• Effects of training machine-learning potentials for radiation damage simulations using different pseudopotentials
• Achieving DFT accuracy in short range ordering and stacking fault energy using moment tensor potential for CoCrFeNi and CoCrNi
• Amorphization-Mediated Si-I to Si-V Phase Transition and Reversible Amorphous-Si-V Phase Memory in Silicon Nanoparticles
• Fine Particle Percolation Dynamics in Porous Media
• Physical embedding machine learning force fields for organic systems
• Generative Quasi-Continuum Modeling of Confined Fluids at the Nanoscale
• Accelerating first-principles molecular-dynamics thermal conductivity calculations for complex systems
• Electronic Fluctuations and Ionic Dynamics in Molten Silver Iodide
• Ions leaving no tracks
• 3D Mapping of Defects and Moiré Corrugations via Electron Ptychography Atomic Coordinate Retrieval
• Towards High-Performance and Portable Molecular Docking on CPUs through Vectorization
• Non-linear jog-dragging effect on the mobility law of edge dislocations in face-centered cubic nickel
• Transitional patterns on a spherical surface: from scars to domain defects of mixed lattices
• Ionic glass formers show an inverted relation between fragility and relaxation broadness
• Glassy interphases reinforce elastomeric nanocomposites by enhancing percolation-driven volume expansion under strain
• A generalized and adaptable tensor-contraction-based cluster expansion formalism for multicomponent solids
• Low-rank matrix and tensor approximations: advancing efficiency of machine-learning interatomic potentials
• Shape spectra of elastic shells with surface-adsorbed semiflexible polymers
• Decomposition of low-angle grain boundaries
• Medium-range structural order in amorphous arsenic
• Confinement Reveals Hidden Splay-Bend Order in Twist-Bend Nematics
• When Energy and Information Revolutions Meet 2D Janus
• Hybrid Monte Carlo Metadynamics (hybridMC-MetaD)
• Jetting with gels: Soft microgel networks stabilize and extend nozzle-free water jets
• Intermolecular Interactions between Polyethylene, Water, and Potential Antistatic and Slip Additives: a Molecular Dynamics Study
• Decoding local framework dynamics in the ultra-small pore MOF MIL-120(Al) CO2 sorbent with Machine Learned Potentials
• Atomistic understanding of hydrogen bubble-induced embrittlement in tungsten enabled by machine learning molecular dynamics
• Metatensor and metatomic: foundational libraries for interoperable atomistic machine learning
• Data for Physics-informed Hamiltonian learning for large-scale optoelectronic property prediction
• Migration as a Probe: A Generalizable Benchmark Framework for Specialist vs. Generalist Machine-Learned Force Fields
• Kinetic pathways of coesite densification from metadynamics
• Ultrafast Solvent Dynamics Drives the Formation of the Hydrated Electron in Photoexcited Water
• Atomistic insights into hydrogen migration in IGZO from machine-learning interatomic potential: linking atomic diffusion to device performance
• Striking Similarities in Dynamics and Vibrations of 2D Quasicrystals and Supercooled Liquids
• Asymmetric stress engineering of dense dislocations in brittle superconductors for strong vortex pinning
• Evaluating Moment Tensor Potential in Ag-Cu Alloy: Accuracy, Transferability, and Phase Diagram Fidelity
• GridFF: Efficient Simulation of Organic Molecules on Rigid Substrates
• Polymer translocation through extended patterned pores in two dimensions: scaling of the total translocation time
• Physics-Informed ML Exploration of Structure-Transport Relationships in Hard Carbon
• When wall slip wins over shear flow: A temperature-dependent Eyring slip law and a thermal multiscale model for diamond-like carbon lubricated by a polyalphaolefin oil
• Modeling of silver transport in cubic SiC: Integrating molecular dynamics, bounds averaging, and uncertainty quantification
• Visualizing Poloidal Orientation in DNA Minicircles
• Atomistic mechanisms of phase transitions in all-temperature barocaloric material KPF₆
• Order-Disorder Transitions and Thermal Pathways in Frustrated 2D Colloidal Crystals
• Dislocation-mediated short-range order evolution during thermomechanical processing
• Towards Routine Condensed Phase Simulations with Delta-Learned Coupled Cluster Accuracy: Application to Liquid Water
• pylimer-tools: A Python Package for Generating and Analyzing Bead-Spring Polymer Networks
• Phonon interference effects in GaAs-GaP superlattice nanowires
• A new computational approach for evaluating bending rigidity of graphene sheets incorporating disclinations
• Insights into the pyrolysis/gasification mechanism of cation ion exchange resins based on ReaxFF simulation and DFT computation
• Thermal Conductivity of C5-6-Ring Two-Dimensional Carbon: Molecular Dynamics, Machine Learning, and Multi-Objective Optimization
• Secondary finite-size effects and multi-barrier free energy landscapes in molecular simulations of hindered ion transport
• Physical Signatures of Supercritical Fluid Boundaries
• Unveiling the Puzzle of Brittleness in Single Crystal Iridium
• VASPilot: MCP-Facilitated Multi-Agent Intelligence for Autonomous VASP Simulations
• ToPolyAgent: AI agents for coarse-grained bead-spring topological polymer simulations
• Comparative study of ensemble-based uncertainty quantification methods for neural network interatomic potentials
• Revealing the Staging Structural Evolution and Li (De)Intercalation Kinetics in Graphite Anodes via Machine Learning Potential
• TorchSim: An efficient atomistic simulation engine in PyTorch
• Advancing Material Modeling in Hydrocodes Beyond Equations of State
• Unveiling the Lithium-Ion Transport Mechanism in Li2ZrCl6 Solid-State Electrolyte via Deep Learning-Accelerated Molecular Dynamics Simulations
• Diffusion in a d-dimensional rough potential
• Model Accuracy and Data Heterogeneity Shape Uncertainty Quantification in Machine Learning Interatomic Potentials
• Machine learning potential for predicting thermal conductivity of θ-phase and amorphous Tantalum Nitride
• Pseudo-grand canonical molecular dynamics via volumetrically controlled osmotic pressure
• Comparative molecular dynamics simulations of charged solid-liquid interfaces with different water models
• Efforts in Modeling the Mechanics and Chemistry of Energetic Materials Across Scales
• Learning the action for long-time-step simulations of molecular dynamics
• Etching-to-deposition transition in SiO₂/Si₃N₄ using CH_xF_y ion-based plasma etching: An atomistic study with neural network potentials
• Arrested Ostwald Ripening in Non-Equilibrium Systems
• Relationship between Structure and Dynamics of an Icosahedral Quasicrystal using Unsupervised Machine Learning
• Deriving effective electrode-ion interactions from free-energy profiles at electrochemical interfaces
• Transverse Self-Propulsion Enhances the Aggregation of Active Dumbbells
• Heterogeneous Ensemble Enables a Universal Uncertainty Metric for Atomistic Foundation Models
• Molecular dynamics of liquid–electrode interface by integrating Coulomb interaction into universal neural network potential
• Influence of Dispersity on the Relaxation of Entangled Polymers from Molecular Dynamics Simulations
• Defect migration in supercrystalline nanocomposites
• Tensor Networks for Liquids in Heterogeneous Systems
• Dynamically phase-separated states in driven binary dusty plasma
• Modulation of Non-equilibrium Structures of Active Dipolar Particles by an External Field
• Machine learning interatomic potential for predicting the thermal properties of uranium nitride
• Machine Learning Workflow for Analysis of High-Dimensional Order Parameter Space: A Case Study of Polymer Crystallization from Molecular Dynamics Simulations
• PEMD: a high-throughput simulation and analysis framework for solid polymer electrolytes
• Silver-Based Self-Organized Resistive Switching Nanoparticle Networks with Neural-Like Spiking Behavior: Implications for Neuromorphic Computing
• Equilibrium and kinetic aspects of Am( iii )/Eu( iii ) pair extraction by a bipyridine-based N,O-donor ligand in different solvents
• Flow-induced anisotropy in a carbon black-filled silicone elastomer: Weak structural anisotropy causes strong piezoresistive anisotropy
• Phonon density of states of magnetite (\ceFe3O4) nanoparticles via molecular dynamics simulations
• Atomistic Simulations of Short-range Ordering with Light Interstitials in Inconel Superalloys
• Segregation and Ordering of Light Interstitials (B, C, H, and N) in Cr-Ni Alloys: Implications for Grain Boundary Stability in Superalloy Design
• Understanding Flow Behaviors of Supercooled Liquids by Embodying Solid-Liquid Duality at Particle Level
• Predicting temperature-dependent failure and transformation zones in 2D silica glass through quasistatic Gaussian Phase Packets
• Machine learning many-body potentials for charged colloids in primitive 1:1 electrolytes
• Atomistic modeling of uranium monocarbide with a machine learning interatomic potential
• Liquid water under vibrational strong coupling: an extended cavity Born-Oppenheimer molecular dynamics study
• A general model for frictional contacts in colloidal systems
• Enhanced Phonon-Assisted Tunneling in Metal -- Twisted Bilayer Graphene Junctions
• Origin of Suppressed Ferroelectricity in k-Ga₂O₃: Interplay Between Polarization and Lattice Domain Walls
• Crossover in growth law in the vapor-liquid phase separation inside complex porous medium
• Cold self-lubrication of sliding ice
• MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling
• Effects of Epoxy Composition on the Thermal and Network Properties of Crosslinked Thermosets: A Molecular-Dynamics Study
• Atomistic characterization of hydration-dependent fuel cell ionomer nanostructure: validation by vibrational spectroscopy
• Understanding stable adsorption states in flexible soft porous coordination polymers through free energy profiles
• Designing Corrosion-Resistant CoCrNi Medium Entropy Alloys via Short-Range Order Modification
• Comparing classical and machine learning force fields for modeling deformation of metal–organic frameworks relevant for direct air capture
• Revealing nanoscale slip within Taylor–Aris dispersion
• Aging of amorphous materials under cyclic strain
• Non-Equilibrium Origin of Native Ring Anisotropy in Amorphous Systems
• Velocity effect on microscopic damage mechanisms of gallium nitride under swift heavy ion irradiation
• Molecular integral equations theory in the near critical region of CO2
• Cyclic Data Streaming on GPUs for Short Range Stencils Applied to Molecular Dynamics
• Graphene Design with Parallel Cracks: Abnormal Crack Coalescence and Its Impact on Mechanical Properties
• Deciphering the Small-Angle Scattering of Polydisperse Hard Spheres using Deep Learning
• Effects of knotting on the collapse of active ring polymers
• Phase Stability and Transformations in Lead Mixed Halide Perovskites from Machine Learning Force Fields
• Ultrafast Nonthermal Lattice Destabilization and Suppression of Polar Optical Scattering in Electronically Excited α-SiO₂ from First-Principles and Deep Neural Network Potential Modeling
• Machine Learning-driven Multiscale MD Workflows: The Mini-MuMMI Experience
• Fundamental of CO2 Adsorption and Diffusion in Sub-nanoporous Materials: Application to CALF-20
• Savi-Bhransha: Graph-Theoretic Dislocation-Loop Characterization in Crystals
• Compressibility of Confined Fluids from Volume Fluctuations
• On void formation during the simulated tensile testing of polymer-filler particle composites
• Dynamical and structural properties of an absorbing phase transition: a case study from granular systems
• Revealing the Void-Size Distribution of Silica Glass using Persistent Homology
• A Generative Diffusion Model for Amorphous Materials
• Growth and prediction of plastic strain in metallic glasses
• Numerical investigation of the equilibrium Kauzmann transition in a two-dimensional atomistic glass
• Incipient ionic conductors: Ion-constrained lattices achieving superionic-like thermal conductivity by extreme anharmonicity
• On the low cycle fatigue behaviour of an Al-Zn-Mg-Cu alloy processed via non-isothermal ageing
• Enhanced molecular diffusion near a soft fluctuating membrane
• Computational Modelling of Thixotropic Multiphase Fluids
• Spatiotemporal hierarchy of thermal avalanches
• Machine Learning Guided Multiscale Design of DNA-functionalized Nanoparticles for Targeted Self-Assembly of the Double Gyroid
• Mass Transfer Through Vapor-Liquid Interfaces From Hydrodynamic Density Functional Theory
• Charge Regulation Effect on Nanoparticles Interaction Mediated by Polyelectrolyte
• Probing aqueous interfaces with spin defects
• Decomposition of general grain boundaries
• Dynamical Heterogeneity in Supercooled Water and its Spectroscopic Fingerprints
• Atomistic study of dislocation formation during Ge epitaxy on Si
• PFAS self-assembly and adsorption dynamics on graphene: molecular insights into chemical and environmental influences
• Diffusion coefficient power laws and defect-driven glassy dynamics in swap acceleration
• Insights into Ionic Diffusion in C-S-H Gel Pore from Molecular Dynamics Simulations: Spatial Distributions, Energy Barriers, and Structural Descriptor
• Variational hydrodynamics of the classical Yukawa one-component plasma
• Surface curvature and secondary vortices in steady dense shallow granular flows
• Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications
• Molecular motion at the experimental glass transition
• Microphase Separation Controls the Dynamics of Associative Vitrimers
• STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations
• Shape-Determined Kinetic Pathways in 2D Solid-Solid Phase Transitions
• Impact of the damping function in dispersion-corrected density functional theory on the properties of liquid water
• Graphene structure modification under tritium exposure: 3H chemisorption dominates over defect formation by \beta-radiation
• Phenylalanine modification in plasma-driven biocatalysis revealed by solvent accessibility and reactive dynamics in combination with protein mass spectrometry
• A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers
• Probing Phonon Modes in Reconstructed twisted Homo and Hetero Bilayer System
• Pressure dependence of liquid iron viscosity from machine-learning molecular dynamics
• Exploring the impact of Ti/Al on L12 nanoprecipitation and deformation behavior in CoNiFeAlTi multi-principal element alloys through atomistic simulations
• Threshold Displacement Energies of Oxygen in YBa₂Cu₃O₇: A Multi-Physics Analysis
• Electrochemistry-Enhanced Dynamic Paths Sampling Unveiling Nuclear Quantum Effects in Electrocatalysis
• Machine Learning Potentials for Alloys: A Detailed Workflow to Predict Phase Diagrams and Benchmark Accuracy
• Unifying renormalized and bare viscosity in two-dimensional molecular dynamics simulations
• Devitrification and Melting Dynamics in Vapor Deposited Water Ice
• An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials
• Advanced Langevin thermostats: Properties, extensions to rheology, and a lean momentum-conserving approach
• ClusterRCA: An End-to-End Approach for Network Fault Localization and Classification for HPC System
• Cyclically sheared colloidal gels: structural change and delayed failure time
• Thermal Conductivity Of Monolayer Hexagonal Boron Nitride: Four-Phonon Scattering And Quantum Sampling Effects
• Faceting transition in aluminum as a grain boundary phase transition
• Viscosity, breakdown of Stokes-Einstein relation and dynamical heterogeneity in supercooled liquid Ge₂Sb₂Te₅ from simulations with a neural network potential
• Quantifying stored energy release in irradiated YBa₂Cu₃O₇ through molecular dynamics annealing simulations
• Monte Carlo Simulations of Crystal Defects in Open Ensembles
• Analytical coarse grained potential parameterization by Reinforcement Learning for anisotropic cellulose
• Crossover between Solid-like and Liquid-like Behavior in Supercooled Liquids
• Scalable Canonical and Isothermal-Isobaric Sampling of Coupled Spin-Lattice Systems with Machine-Learning Potentials
• Asymmetric Effects Underlying Dynamic Heterogeneity in Miscible Blends of Poly(methyl methacrylate) with Poly(ethylene oxide)
• Universal scaling laws on the rotational energy landscape for twisted van der Waals bilayers
• Rules of Connectivity-Dependent Phonon Interference in Molecular Junctions
• Precision Atomistic Structures of Actinium-/Radium-/Barium-Doped Lanthanide Nanoconstructs for Radiotherapeutic Applications
• Mechanical modulation of 2D transition metal dichalcogenide alloys
• Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study
• Deep Potential-Driven Molecular Dynamics of CO Ice Analogues: Investigating Desorption Following Vibrational Excitation
• Coupled reaction and diffusion governing interface evolution in solid-state batteries
• Machine learning accelerated finite-field simulations for electrochemical interfaces
• Going beyond density functional theory accuracy: Leveraging experimental data to refine pre-trained machine learning interatomic potentials
• Critical surface phase behavior governs hydrophobic attraction between extended solutes
• Scaling the glassy dynamics of active particles: Tunable fragility and reentrance
• Machine learning-enabled atomistic insights into phase boundary engineering of solid-solution ferroelectrics
• Mean Force Emission Theory for Classical Bremsstrahlung in Electron-Ion Plasmas
• A Combined DFT and MD Study on Interface Stability in Ferrite-Cementite Systems
• Thermoplasmonics of Gold-Core Silica-Shell Colloidal Nanoparticles under Pulse Illumination
• Fast and Fourier Features for Transfer Learning of Interatomic Potentials
• Observation of a low energy nuclear recoil peak in the neutron calibration data of an Al₂O₃ crystal in CRESST-III
• Enhanced strain rate sensitivity due to platelet linear complexions in Al-Cu
• Lattice and Orientational Defects Mediate Collective Transport of Confluent Cells
• chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations
• Linear Analysis of Stochastic Verlet-Type Integrators for Langevin Equations
• Large-scale exponential correlations of nonaffine elastic response of strongly disordered materials
• Manipulating the interfacial structures in titanium alloys containing interstitial solutes delivers ultra-high strength and ductility
• Cell-Scale Dynamic Modeling of Membrane Interactions with Arbitrarily Shaped Particles
• A Concurrent Multiscale Framework Coupling Direct Simulation Monte Carlo and Molecular Dynamics
• Adsorbate phase transitions on nanoclusters from nested sampling
• How important is the dielectric constant in water modeling? Evaluation of the performance of the TIP4P/ε force field and its compatibility with the Joung-Cheatham NaCl model
• Atomistic Study of Radiation-Induced Ductile-to-Brittle Transition in Austenitic Steel
• Atom-by-atom Imaging of Moiré Phasons using Electron Ptychography
• A theory for diffusion-controlled reactions within nonequilibrium steady states
• Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials
• Thermophysical Properties and Phase Behavior of CO2 with Impurities: Insight from Molecular Simulations
• DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials
• Roadmap for warm dense matter physics
• Determination of melting temperature of hexagonal ice using Lee-Yang phase transition theory
• Breaking the Curse of Dimensionality: Solving Configurational Integrals for Crystalline Solids by Tensor Networks
• Dynamical Data for More Efficient and Generalizable Learning: A Case Study in Disordered Elastic Networks
• Atomistic and experimental study of microstructural evolution in nanocrystalline iron subjected to irradiation
• Mass-Zero constrained molecular dynamics for electrostatic interactions
• Structure and Elastic properties of Titanium MXenes: evaluation of COMB3, REAXFF and MEAM force fields
• Beyond the Electric Dipole Approximation: Electric and Magnetic Multipole Contributions Reveal Biaxial Water Structure from SFG Spectra at the Air-Water Interface
• ACCES: Non-Invasive Simulation Calibration via Optimisation using Evolutionary Algorithms and Metaprogramming
• Universal Symmetries in Twisted Moiré Materials
• STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation
• Efficient local atomic cluster expansion for BaTiO₃ close to equilibrium
• Extending Quantum Computing through Subspace, Embedding and Classical Molecular Dynamics Techniques
• Real-time dynamics of the two-step charge-density-wave transition in bulk 1T-TaS₂
• Multicrossmodal Automated Agent for Integrating Diverse Materials Science Data
• Nanoconfined superionic water is a molecular superionic
• Pressure Waves During Granular Flows in Varying Gravity Environments
• Deep machine learning, molecular dynamics and experimental studies of liquid Al-Cu-Co alloys
• Nanoindentation simulations for copper and tungsten with adaptive-precision potentials
• A Deep Learning Potential for Accurate Shock Response Simulations in Tin
• Dislocation dynamics in Ni: Parameterizing dislocation trajectories from atomistic simulations
• From oligomers to entangled polymers: How to train a transferable machine learning interatomic potential
• Electronic origin of reorganization energy in interfacial electron transfer
• Efficient and Accurate Machine Learning Interatomic Potential for Graphene: Capturing Stress-Strain and Vibrational Properties
• Dislocation Glides in Monolayered Granular Media: Effect of Lattice Constant
• Diffusion-entropy scaling across dimensions
• Droplet slipperiness despite surface heterogeneity at molecular scale
• Exploration of amorphous V₂O₅ as cathode for magnesium batteries
• MatTools: Benchmarking Large Language Models for Materials Science Tools
• Structure and dynamics of ionic liquids under shear flow
• Weighted Active Space Protocol for Multireference Machine-Learned Potentials
• FlashMD: long-stride, universal prediction of molecular dynamics
• Accelerating Fast Ewald Summation with Prolates for Molecular Dynamics Simulations
• 3D‐Printed Inherently Porous Structures with Tetrahedral Lattice Architecture: Experimental and Computational Study of Their Mechanical Behavior
• Writing Into Water
• Learned Free-Energy Functionals from Pair-Correlation Matching for Dynamical Density Functional Theory
• The structure and migration of twin boundaries in tetragonal β-Sn: an application of machine learning based interatomic potentials
• Neural Network-Driven Molecular Insights into Alkaline Wet Etching of GaN: Toward Atomistic Precision in Nanostructure Fabrication
• ATLAHS: An Application-centric Network Simulator Toolchain for AI, HPC, and Distributed Storage
• Unraveling the impact of competing interactions on non-equilibrium colloidal gelation
• Pyrite Bismuth Telluride Heterojunction for Hybrid Electromagnetic to Thermoelectric Energy Harvesting
• Modern Software Engineering in the LAMMPS Molecular Dynamics Software Package: Development Process, Refactoring, Testing, and Deployment
• Efficient Parallelization of Message Passing Neural Network Potentials for Large-scale Molecular Dynamics
• Control of encounter kinetics by chemically active droplets
• Hexagonal ice density dependence on inter atomic distance changes due to nuclear quantum effects
• Development and application of Δ-machine-learned interatomic potentials to platinum-Nafion interfaces
• Coarse-grained graph architectures for all-atom force predictions
• Tailoring Heat Transfer at Silica-Water Interfaces via Hydroxyl and Methyl Surface Groups
• Machine-Learned Interatomic Potentials for Predicting Physicochemical Properties of Molten Metal-Salt Systems for Calcium Electrolysis
• Interpretable Inverse Design of Metal-Organic Frameworks with Large Language Model Agents
• MDArena: Evaluating Coding Agents on Realistic Molecular Dynamics Workflows
• Bottlenecks in Hamiltonian-Adaptive Resolution Simulation Method for Modeling Interfaces
• Solvation Lies Within: Simulating Condensed-Phase Properties from Local Electronic Structures
• The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project
• Large Language Models as AI Agents for Digital Atoms and Molecules: Catalyzing a New Era in Computational Biophysics
• Hydride formation and phase separation in palladium nanoparticles from a transferable atomic cluster expansion potential
• Synthetic design of force-responsive hydrogels with ring-forming catch bonds
• Accurate Modeling of Interfacial Thermal Transport in van der Waals Heterostructures via Hybrid Machine Learning and Registry-Dependent Potentials
• An adaptive, data-driven multiscale approach for dense granular flows
• NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
• No Evidence of Anomalous Diffusion in Yukawa Crystals
• MLM: Multi-Layer Moire -- A Python Package for Generating Commensurate Supercells of Twisted Multilayer Two-Dimensional Materials
• Molecular dynamic simulation of multicomponent CoCrFeNiMn high-entropy alloy thin film deposition
• Data-Driven Thermal and Mechanical Modeling of Defective Covalent Organic Frameworks
• Partially reactive force field for the UiO-66 metal-organic framework
• Can Coding Agents Reproduce Findings in Computational Materials Science?
• Multiscale modelling of thermally stressed superelastic polyimide
• A rigorous data-driven approach to the nucleation of defects in metals exploiting the link between kinetic properties and (dis)order parameters
• Evolution of cavities in BCC-Fe with coexisting H and He under fusion environments
• On phase separation and crystallization of Ge-rich GeSbTe alloys from atomistic simulations with a machine learning interatomic potential
• Complex segregation patterns in confined nonuniform granular shearing flows
• Clustering of the T-cell receptor complex may facilitate T-cell activation by stretching of CD3ζ cytoplasmic tails
• High-Temperature Deformation Behavior of Co-Free Non-Equiatomic CrMnFeNi Alloy
• Spall strength of symmetric tilt grain boundaries in 6H silicon carbide
• Consistency between the Green-Kubo formula and Lorentz model for predicting the infrared dielectric function of polar materials
• Unveiling the Role of Friction in Coarse-Grained Clay: A Hybrid Framework Integrating Long-Range Interactions and Granular Contact Mechanics
• Resolving coupled transport in space and time from molecular fluctuations in confined fluids
• From populations to absolute binding affinities in molecular simulations: exact volumetric terms and practical estimators
• SimMOF: AI agent for Automated MOF Simulations
• Ultra-high dose rate 6 MeV electron irradiation generates stable [1-¹³C]alanine radicals suitable for medical imaging with dissolution Dynamic Nuclear Polarisation
• Energetics of the nucleation and glide of disconnection modes in symmetric tilt grain boundaries
• High-performance training and inference for deep equivariant interatomic potentials
• Thermal rectification and phonon properties in partially perforated graphene
• Molecular dynamics simulation of silicon nanoparticle crystallization during laser-induced forward transfer printing
• Moment Tensor Potential and Equivariant Tensor Network Potential with explicit dispersion interactions
• Unconventional mechanical and thermal behaviours of MOF CALF-20
• Exploring Charge Density Waves in two-dimensional NbSe2 with Machine Learning
• A new thermodynamic function for binary mixtures: the co-molar volume
• Compression of refractory high-entropy alloy nanoparticles: Size and short-range order effects
• Extracting flow stress surfaces of pristine materials using deformation paths in MD simulations
• Polytetrafluoroethylene (PTFE) Lubrication of Rolling Point Contacts by Double Transfer Films: Relationships between Friction and Lubricant Film Distribution Revealed by Spacer Layer Imaging and Molecular Dynamics
• Correlation between plastic rearrangements and local structure in a cyclically driven glass
• Understanding compression behavior and structural transitions of clay-rich media with varying moisture contents through large-scale molecular dynamics simulations
• Accurate Modeling of LEGO-like vdW Heterostructures: Integrating Machine Learned with Anisotropic Interlayer Potentials
• Calculations of the Krypton Phase Diagram and Novel Plasticity
• Interface Engineering of Helium Confinement in Argon-Preplated MCM-41 Nanopores
• Fine-Tuning Small Language Models for Reliable VASP INCAR Generation
• Topology as a Design Variable for Multiproperty Engineering in Synthesized 4-5-6-8 Carbon Nanoribbons
• Reconstructions and Dynamics of β-Lithium Thiophosphate Surfaces
• Influence of packing protocol on fractal exponents in dense polydisperse packings
• Harnessing Machine Learning for Quantum-Accurate Predictions of Non-Equilibrium Behavior in 2D Materials
• Exact large-scale correlations in diffusive systems with general interactions: explicit characterisation without the Dean--Kawasaki equation
• Significant ballistic thermal transport across graphene layers: effect of nanoholes and lithium intercalation
• Elasticity of bidisperse attractive particle systems
• An Efficient Integrator Scheme for Sampling the (Quantum) Isobaric-Isothermal Ensemble in (Path Integral) Molecular Dynamics Simulations
• Inverse Design of Block Polymer Materials with Desired Nanoscale Structure and Macroscale Properties
• Mechanical Amorphization of Glass-Forming Systems Induced by Oscillatory Deformation: The Energy Absorption and Efficiency Control
• Flow-driven Stretch Fluctuations Cause Anomalous Rate-Thinning In Elongating Associative Polymers
• Spectral Similarity Masks Structural Diversity at Hydrophobic Water Interfaces
• Towards "on-demand" van der Waals epitaxy with hpc-driven online ensemble sampling
• Imbibition of Oil in Dry and Prewetted Calcite Nanopores
• Uncovering the roughness effect on inelastic phonon scattering and thermal conductance at interface via spectral energy exchange
• Data-Driven Molecular Dynamics and TEM Analysis of Crystal Growth and Hydrogen Sensing in Pt-Functionalized Graphene Chemiresistive Sensors
• On the Connection Between Diffusion Models and Molecular Dynamics
• Modelling Interfacial Dynamics Using Hydrodynamic Density Functional Theory: Dynamic Contact Angles and the Role of Local Viscosity
• Newton-X Platform: New Software Developments for Surface Hopping and Nuclear Ensembles. [europepmc]
• Cohesin and CTCF control the dynamics of chromosome folding. [europepmc]
• Detecting and quantifying liquid-liquid phase separation in living cells by model-free calibrated half-bleaching. [europepmc]
• A Guide to In Silico Drug Design. [europepmc]
• Non-polar ether-based electrolyte solutions for stable high-voltage non-aqueous lithium metal batteries. [europepmc]
• Diversity of platinum-sites at platinum/fullerene interface accelerates alkaline hydrogen evolution. [europepmc]
• Role of Strong Localized vs Weak Distributed Interactions in Disordered Protein Phase Separation. [europepmc]
• Enabling selective zinc-ion intercalation by a eutectic electrolyte for practical anodeless zinc batteries. [europepmc]
• Realistic phase diagram of water from "first principles" data-driven quantum simulations. [europepmc]
• Ultra-long-range interactions between active regulatory elements. [europepmc]
• MBX: A many-body energy and force calculator for data-driven many-body simulations. [europepmc]
• DeePMD-kit v2: A software package for deep potential models. [europepmc]
• First-principles spectroscopy of aqueous interfaces using machine-learned electronic and quantum nuclear effects. [europepmc]
• Multiscale simulations reveal TDP-43 molecular-level interactions driving condensation. [europepmc]
• Neighbor List Artifacts in Molecular Dynamics Simulations. [europepmc]
• A complex network of interdomain interactions underlies the conformational ensemble of monomeric TDP-43 and modulates its phase behavior. [europepmc]
• Surface stratification determines the interfacial water structure of simple electrolyte solutions. [europepmc]
• Direct prediction of intrinsically disordered protein conformational properties from sequence. [europepmc]
• Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations. [europepmc]
• Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. [europepmc]
• Biomolecular condensates form spatially inhomogeneous network fluids. [europepmc]
• CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed. [europepmc]
• Introductory Tutorials for Simulating Protein Dynamics with GROMACS. [europepmc]
• General-purpose machine-learned potential for 16 elemental metals and their alloys. [europepmc]
• Microenvironmental modulation breaks intrinsic pH limitations of nanozymes to boost their activities. [europepmc]

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