Molecular Dynamics Simulation

Ask about this topic

Overview

Molecular dynamics simulation follows atoms over time to reveal how molecules and materials change, and to estimate properties such as stability, transport, and reaction rates. Simulations use classical force fields or first-principles calculations, increasingly complemented by machine-learned potentials and neural models that predict forces or advance trajectories. Generative sampling, replica exchange, and learned free-energy methods help explore rare events and estimate equilibrium behavior in settings such as protein folding, peptide transitions, and material defects. A central challenge is making simulations faster and more transferable without losing physical accuracy, reliable long-time dynamics, or agreement with experiments.

Latest papers

CardsList

55 papers9 papers in the last four weeks, up 200% on the four weeks before. 0.1% of all new papers.

  1. mdRNAcat: A Molecular Dynamics RNA Catalog of REST2 Conformational Ensembles

    Oct 26, 2026Anton E. Dorn, Emile de Bruyn, Fabrice von der Lehr +3Molecular Dynamics Simulation

    Jülich Supercomputing Centre, Forschungszentrum Jülich (FZJ) · Faculty of Physics, Georg August University of Göttingen · Institute of Software Technology, Germany Aerospace Center (DLR) +2

  2. PULSES: multi-agent AI for autonomous excited-state model building and dynamics

    Oct 23, 2026Fangning Ren, Lechen Dong, Xu Chen +3AI Agents for Scientific DiscoveryAutonomous Research Agents

    Department of Chemistry, Emory University, Atlanta, GA, 30322, USA

  3. On the Theoretical Limits of Learning Unconstrained Interatomic Potentials

    Oct 10, 2026Prajwal Ananth, Shuwen YueMachine Learning Interatomic PotentialsMolecular Dynamics Simulation

    Center for Applied Mathematics, Cornell University, Ithaca, NY · R. F. Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY

  4. AtomWorld-Mirror: Macro-Step World Modeling of Critical Evolution Backbones for Materials Dynamics

    Oct 8, 2026Ziming Pan, Ruge Zhang, Haozhi Han +7Physics-Based SimulationComputational Materials Science

    Yonsei University, Seoul, Republic of Korea · Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China · Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China +4

  5. Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics

    Oct 7, 2026Simon Olsson, Frank Noé, Grant M. Rotskoff +1Molecular Dynamics SimulationGenerative AI Evaluation

    Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg SE-41296 Gothenburg, Sweden · Microsoft Research Berlin · Stanford University +1

  6. PEACE: Covariant learning of nonadiabatic manifolds with parity-resolved Hamiltonians

    Oct 7, 2026Rongzhi Gao, Shuguang Chen, Yang Zhou +3Molecular Dynamics SimulationQuantum Chemistry

    Department of Chemistry, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China · Hong Kong Quantum AI Lab, Pak Shek Kok, Hong Kong SAR, China · MattVerse Limited, Pak Shek Kok, Hong Kong SAR, China +1

  7. Learning consistent molecular mechanics force fields from first principles

    Oct 6, 2026Berkay Günes, Leif Seute, Jigyasa Nigam +1Parameter EstimationMolecular Dynamics Simulation

    Max Planck Institute for Polymer Research Mainz, Germany · Heidelberg University, Germany · Heidelberg Institute for Theoretical Studies, Germany +1

  8. Langevin Flow Maps: Efficient Molecular Dynamics and Transition Path Sampling

    Oct 5, 2026Sam McCallum, Niklas Rindtorff, Alexander Tong +1Stochastic Differential EquationsMachine Learning Interatomic Potentials

    University of Bath · AITHYRA

  9. RNADyn: A Benchmark for Generating and Understanding RNA Dynamics

    Oct 2, 2026Yiming Huang, Lennart Bastian, Hanqun Cao +2Molecular Dynamics SimulationMolecular Representation Learning

    Imperial College London · The Chinese University of Hong Kong · Technical University of Munich

  10. SupraTITO: Transferable Generative Molecular Dynamics for Supramolecular Systems

    Oct 1, 2026Weilong Chen, Nuno Costa, Julija ZavadlavOperator LearningMolecular Dynamics Simulation

    MFM Lab, TUM, Germany · AMC, TUM, Germany

  11. Neural Transport Nested Sampling

    Sep 24, 2026David Yallup, Will HandleyMarkov Chain Monte CarloBoltzmann Sampling

    Kavli Institute for Cosmology Cambridge Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, UK

  12. SPIBER: Reconstructing Free Energy Landscapes from Short, Unconverged Trajectories with Generative Flow Networks

    Sep 19, 2026Venkata Sai Sreyas Adury, Pratyush TiwaryFree Energy CalculationMolecular Dynamics Simulation

    Chemical Physics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA · Biophysics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA · Department of Chemistry and Biochemistry and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA +1

  13. Machine learning kinetics from molecular dynamics data

    Sep 15, 2026Jonathan Weare, Aaron R. DinnerMarkov ModelsMolecular Dynamics Simulation

    Courant Institute School of Mathematics, Computing, and Data Science, New York University, New York, New York 10012, United States · Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois 60637, United States

  14. Cross-Temperature Defect Identification in Atomistic Simulations via Multi-Level Domain Alignment

    Aug 22, 2026Yating Fang, Jungmin Kim, Qian Qian Zhao +4Domain AdaptationUnsupervised Domain Adaptation

    Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory, Rutgers University, Piscataway, 08854, NJ, USA. · Department of Industrial and Systems Engineering, Rutgers University, Piscataway, 08854, NJ, USA. · Department of Materials Science and Engineering, Rutgers University, Piscataway, 08854, NJ, USA.

  15. First-Principles Atomistic Structure and Dynamics of Polyethylene During High-Pressure Radical Polymerization via Machine Learning Force Fields

    Aug 22, 2026Bharatha K. Gunawardana, Teresa Shah, Bicha Azizova +6Materials ScienceComputational Materials Science

    Department of Chemistry, University of North Texas, Denton, TX 76203, USA · Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA 18015, USA

  16. Stochastic Control Policies for Robust Molecular Transition Path Sampling

    Aug 13, 2026Jingqian Liu, Yu-Hsiang Wang, Yanru Qu +1Stochastic Optimal ControlMolecular Dynamics Simulation

    Siebel School of Computing and Data Science, University of Illinois Urbana–Champaign · Department of Electrical and Computer Engineering, University of Illinois Urbana–Champaign

  17. Agent-MD: Selective LLM Intervention with Event-Driven Escalation for Stateful GCMC--MD Campaigns

    Aug 7, 2026Yijie Wang, Zhen-Yu Yin, Zhenheng Tang +1LLM Agent OrchestrationScientific Workflow Automation

    Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China · Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

  18. A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

    Aug 7, 2026Joohee Choi, Junhyeong Lee, Seunghwa RyuMolecular Dynamics Simulation

    Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea · KAIST InnoCORE PRISM-AI Center, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea · Department of AX, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

  19. MDArena: Evaluating Coding Agents on Realistic Molecular Dynamics Workflows

    Jul 31, 2026Nithishwer Mouroug Anand, Wei-Tse Hsu, Kyle Vaccaro +6Coding AgentsScientific Code Generation

    Department of Biochemistry, University of Oxford · Scripps Research Institute

  20. Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations

    Jul 31, 2026Johannes Maeß, Leon Werner, J. Thorben Frank +5Implicit Neural RepresentationsMachine Learning Interatomic Potentials

    BIFOLD, Berlin, Germany. · Machine Learning Group, TU Berlin, Berlin, Germany. · Department of Artificial Intelligence, Korea University, Seoul, South Korea. +1

  21. Graph-Theoretic Neural Network Fragmentation with Covariant Direct Molecular Force Learning: Enabling Coupled-Cluster Accuracy AIMD for Fluxional Systems

    Jul 23, 2026Xiao Zhu, Srinivasan S. IyengarMachine Learning Interatomic PotentialsEquivariant Neural Networks

    Department of Chemistry, Department of Physics, and the Indiana University Quantum Science and Engineering Center (IU-QSEC), Indiana University, 800 E. Kirkwood Ave, Bloomington, IN-47405

  22. Nuclear Quantum Effects as a Denoising Problem

    Jul 22, 2026Weizhou Wang, Jonathan Weare, Aaron R. DinnerDiffusion-Based DenoisingQuantum Chemistry

    Department of Chemistry, University of Chicago, Chicago, Illinois 60637, USA · Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA · James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA

  23. Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy

    Jul 12, 2026Jan Eckwert, Julija ZavadlavMachine Learning Interatomic PotentialsMolecular Dynamics Simulation

    1Multiscale Modeling of Fluid Materials, Department of Engineering Physics and Computation, TUM School of Engineering and Design and Department of Physics, TUM School of Natural Sciences, Technical University of Munich, Munich, 80333, Germany. · 2Atomistic Modeling Center, Munich Data Science Institute, Technical University of Munich, Garching, 85748, Germany.

  24. Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout

    Jun 28, 2026Wenjie XiFree Energy CalculationMolecular Dynamics Simulation

    Department of Physics and HK Institute of Quantum Science & Technology, The University of Hong Kong, Pokfulam Road, Hong Kong, China

  25. Autoregressive Boltzmann Generators

    Jun 25, 2026Danyal Rehman, Charlie B. Tan, Yoshua Bengio +2Autoregressive GenerationMolecular Generation

    Mila – Québec AI Institute · Broad Institute of MIT & Harvard · Aithyra +4

  26. ASTEROID: A Spatiotemporal Information Transformer for Forecasting Multi-Step Time Series of Molecular Dynamics

    Jun 16, 2026Kexin Wu, Luonan Chen, Renxiao WangSpatiotemporal ForecastingMolecular Dynamics Simulation

    Department of Medicinal Chemistry, School of Pharmaceutical Sciences, Fudan University, 826 Zhangheng Road, Shanghai 201203, People's Republic of China · School of Mathematical Sciences and School of AI, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China

  27. MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback

    Jun 11, 2026Zehong Wang, Yijun Ma, Connor R. Schmidt +7AI Agents for Scientific DiscoveryMolecular Dynamics Simulation

    University of Notre Dame · University of Connecticut

  28. Reactive Flux Matching: Mechanism Discovery and Adaptive Sampling of Rare Events

    Jun 4, 2026Rishal Aggarwal, David Ryan Koes, Nicholas M. Boffi +1Adaptive SamplingMolecular Dynamics Simulation

    CMU-Pitt Program in Computational Biology Dept. of Computational & Systems Biology University of Pittsburgh · Machine Learning Department Dept. of Mathematical Sciences Carnegie Mellon University · Courant Institute, New York University Machine Learning Lab +1

  29. Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials

    Jun 2, 2026Joanna Zou, Fraser Birks, Dallas Foster +1Machine Learning Interatomic PotentialsActive Learning

    Center for Computational Science & Engineering, Schwarzman College of Computing, MIT · Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick · NVIDIA

  30. Speculative Sampling For Faster Molecular Dynamics

    Jun 1, 2026Arthur Kosmala, Stephan Günnemann, Meng Gao +1Langevin DynamicsMolecular Dynamics Simulation

    1FAIR at Meta · School of Computation, Information & Technology, Technical University of Munich · 3Munich Data Science Institute +1