A topological method defines local entanglements via Gaussian Linking Number, locates force centers, and distills CGMD polymer networks into efficient discrete network models reproducing virial stress predictions.
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35 Pith papers cite this work, alongside 11,528 external citations. Polarity classification is still indexing.
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representative citing papers
Local surrogate models for harmonic vibrational entropy in multilattices achieve linear scaling with sublattice-resolved locality proofs and controlled truncation error on finite-range models.
MD simulations with ML force fields reveal non-monotonic friction-load curves in MX2/metal heterostructures arising from coexistence of longitudinal, lateral-slip, and zig-zag sliding modes.
Simulation-informed Bayesian analysis of polarized QENS data resolves anisotropic spinning and tumbling diffusion coefficients in liquid benzene, revealing stronger rotational anisotropy than prior work.
MALOQ introduces a scalable SO(2)-equivariant ML framework with custom kernels and edge-wise graph distribution for predicting large-scale quantum transport operators.
A modified Euler-Maruyama method is proposed and proven to converge weakly with order 1 to one-dimensional sticky diffusions.
Machine-learned many-body potentials from Poisson-Boltzmann calculations on clusters up to 48 colloids show that higher-order interactions reduce cohesion and eliminate broad gas-liquid phase separation, consistent with primitive model pair and triplet potentials.
The authors define slip velocity in NEMD systems from the equality of macroscale frictional power and microscale interfacial work dissipation to remove arbitrariness in boundary-layer velocity choice.
Portable Ewald summation algorithms for Stokes flow achieve ~8M particles/sec on H200 GPU with a novel P2G kernel providing 16x speedup and good multi-GPU scaling.
SIGA is a coding-agent adapter using retrieval, procedural memory, and validation gates that raises success rate on GEOS from 0.720 to 0.789 while cutting variance 16x and matching expert quality in minutes instead of hours.
SKMD adapts Stein variational gradient descent into molecular dynamics with asynchronous updates and global atomic descriptor kernels to acquire non-redundant training configurations while preserving the Boltzmann distribution, yielding higher MLIP accuracy with fewer samples than baselines.
Machine learning force field molecular dynamics simulations reveal anisotropic crystallization in Sb2S3 with [100] facet fastest growth and interface-controlled kinetics with activation energy 0.55-0.57 eV.
Monte-Carlo simulations with an ML potential demonstrate that coherency strain removes the Ag-Cu miscibility gap in Ag_xCu_{1-x}GaSe2, producing complete mixing.
ColPackAgent integrates a custom colpack Python package wrapping HOOMD-blue with MCP tools and an agent skill to enable reliable autonomous workflows for colloidal packing simulations across interactive, prompt-driven, and autoresearch modes.
GRAFT-ATHENA projects combinatorial method choices into factored trees that embed as fingerprints in a metric space, enabling an agentic system to accumulate experience across domains and autonomously discover new numerical techniques for physics-informed problems.
An updated LAMMPS version of H-AdResS enables dual-resolution simulations of interfaces in porous solids, keeping atomistic accuracy while raising efficiency.
QCOF ML potentials tuned on COF data outperform general MACE models for defective systems and reveal higher thermal defect sensitivity in CTF-1 versus COF-LZU1 with nearly invariant low-strain mechanics.
A transfer-learned ResNet-18 predicts a continuous disorder parameter from simulated nanobeam electron diffraction patterns of Cu-Zr metallic glasses, with a qualitative demonstration on experimental patterns.
Introduces torch-pme and jax-pme libraries that embed Ewald-based long-range methods and purified descriptors into atomistic ML for accurate handling of non-local physical interactions.
Crystal-melt stiffness of colloidal hard spheres gains a gravity-dependent term ˜γ = ˜γ0 + g''ξ² that reconciles long-standing experiment-simulation discrepancies.
ML model using ideal entropy plus simulation features (energy above hull, heat capacity change, icosahedral fraction) predicts metallic glass critical cooling rates with R²=0.78 in leave-one-chemical-system-out cross-validation on 34 alloys.
Quantum thermal conductivity of 2D monolayer amorphous carbon ranges 3.5-10 W/m/K at room temperature and is less than half the classical value, with distinct mode polarization behavior.
MD simulations of Pd yield nucleation rate maximum of 4e35 m^{-3}s^{-1} at 0.5 Tm, diffusion-limited growth, TTT nose at 100 ps, and reproduce experimental onset at 5e11 K/s cooling, indicating homogeneous nucleation.
Hybrid TTM-MD simulations of gold thin films show microstructure configuration and topology dominate over grain size and orientation in controlling laser-induced melting and expansion, with tensile stresses increasing and compressive stresses decreasing deformation.
citing papers explorer
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Physically-Motivated Primitive Path Analysis of Entangled Polymer Networks
A topological method defines local entanglements via Gaussian Linking Number, locates force centers, and distills CGMD polymer networks into efficient discrete network models reproducing virial stress predictions.
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Local Surrogates for Harmonic Vibrational Entropy in Multilattices
Local surrogate models for harmonic vibrational entropy in multilattices achieve linear scaling with sublattice-resolved locality proofs and controlled truncation error on finite-range models.
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Microscopic contributions to the deviation from Amontons friction law
MD simulations with ML force fields reveal non-monotonic friction-load curves in MX2/metal heterostructures arising from coexistence of longitudinal, lateral-slip, and zig-zag sliding modes.
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Lost in Translation: Simulation-Informed Bayesian Inference Improves Understanding of Molecular Motion From Neutron Scattering
Simulation-informed Bayesian analysis of polarized QENS data resolves anisotropic spinning and tumbling diffusion coefficients in liquid benzene, revealing stronger rotational anisotropy than prior work.
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MALOQ: Massively Accelerated Learning of Operators for Quantum Transport
MALOQ introduces a scalable SO(2)-equivariant ML framework with custom kernels and edge-wise graph distribution for predicting large-scale quantum transport operators.
-
A modified Euler-Maruyama method to simulate a one-dimensional sticky diffusion
A modified Euler-Maruyama method is proposed and proven to converge weakly with order 1 to one-dimensional sticky diffusions.
-
Many-body attractions do not stabilize gas-liquid phase separation in aqueous dispersions of charged colloids within the Poisson-Boltzmann framework
Machine-learned many-body potentials from Poisson-Boltzmann calculations on clusters up to 48 colloids show that higher-order interactions reduce cohesion and eliminate broad gas-liquid phase separation, consistent with primitive model pair and triplet potentials.
-
Extraction of slip velocity in NEMD Couette flow systems using frictional dissipation
The authors define slip velocity in NEMD systems from the equality of macroscale frictional power and microscale interfacial work dissipation to remove arbitrariness in boundary-layer velocity choice.
-
A performance portable fast Ewald summation for Stokes flow
Portable Ewald summation algorithms for Stokes flow achieve ~8M particles/sec on H200 GPU with a novel P2G kernel providing 16x speedup and good multi-GPU scaling.
-
Auto-Configuring Scientific Simulators with Lightweight Coding-Agent Adapters
SIGA is a coding-agent adapter using retrieval, procedural memory, and validation gates that raises success rate on GEOS from 0.720 to 0.789 while cutting variance 16x and matching expert quality in minutes instead of hours.
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Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials
SKMD adapts Stein variational gradient descent into molecular dynamics with asynchronous updates and global atomic descriptor kernels to acquire non-redundant training configurations while preserving the Boltzmann distribution, yielding higher MLIP accuracy with fewer samples than baselines.
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Anisotropic Crystallization Kinetics and Interfacial Dynamics of Phase-Change Material Sb$_2$S$_3$ from Machine Learning Force Field Simulations
Machine learning force field molecular dynamics simulations reveal anisotropic crystallization in Sb2S3 with [100] facet fastest growth and interface-controlled kinetics with activation energy 0.55-0.57 eV.
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Chemo-mechanical coupling stabilizes mixed $\mathrm{Ag}_{x}\mathrm{Cu}_{1-x}\mathrm{GaSe}_{2}$ solar-cell absorbers: Insights from Monte-Carlo simulations assisted by ab initio informed machine-learning potentials
Monte-Carlo simulations with an ML potential demonstrate that coherency strain removes the Ag-Cu miscibility gap in Ag_xCu_{1-x}GaSe2, producing complete mixing.
-
ColPackAgent: Agent-Skill-Guided Hard-Particle Monte Carlo Workflows for Colloidal Packing
ColPackAgent integrates a custom colpack Python package wrapping HOOMD-blue with MCP tools and an agent skill to enable reliable autonomous workflows for colloidal packing simulations across interactive, prompt-driven, and autoresearch modes.
-
GRAFT-ATHENA: Self-Improving Agentic Teams for Autonomous Discovery and Evolutionary Numerical Algorithms
GRAFT-ATHENA projects combinatorial method choices into factored trees that embed as fingerprints in a metric space, enabling an agentic system to accumulate experience across domains and autonomously discover new numerical techniques for physics-informed problems.
-
Extending Hamiltonian-Adaptive Resolution Simulation to Interfaces: An Updated LAMMPS Implementation and Application to Porous Solids
An updated LAMMPS version of H-AdResS enables dual-resolution simulations of interfaces in porous solids, keeping atomistic accuracy while raising efficiency.
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Data-Driven Thermal and Mechanical Modeling of Defective Covalent Organic Frameworks
QCOF ML potentials tuned on COF data outperform general MACE models for defective systems and reveal higher thermal defect sensitivity in CTF-1 versus COF-LZU1 with nearly invariant low-strain mechanics.
-
Extraction of a structural short-range order descriptor from nanobeam electron diffraction patterns using a transfer learning approach
A transfer-learned ResNet-18 predicts a continuous disorder parameter from simulated nanobeam electron diffraction patterns of Cu-Zr metallic glasses, with a qualitative demonstration on experimental patterns.
-
Fast and flexible long-range models for atomistic machine learning
Introduces torch-pme and jax-pme libraries that embed Ewald-based long-range methods and purified descriptors into atomistic ML for accurate handling of non-local physical interactions.
-
Sedimentation equilibrium and gravity dependent stiffness coefficients of colloidal hard-spheres
Crystal-melt stiffness of colloidal hard spheres gains a gravity-dependent term ˜γ = ˜γ0 + g''ξ² that reconciles long-standing experiment-simulation discrepancies.
-
Machine learning metallic glass critical cooling rates through elemental and molecular simulation based featurization
ML model using ideal entropy plus simulation features (energy above hull, heat capacity change, icosahedral fraction) predicts metallic glass critical cooling rates with R²=0.78 in leave-one-chemical-system-out cross-validation on 34 alloys.
-
Quantum Statistics and Structural Topology Govern Thermal Transport in Two-Dimensional Monolayer Amorphous Carbon
Quantum thermal conductivity of 2D monolayer amorphous carbon ranges 3.5-10 W/m/K at room temperature and is less than half the classical value, with distinct mode polarization behavior.
-
Crystallisation kinetics of supercooled liquid palladium
MD simulations of Pd yield nucleation rate maximum of 4e35 m^{-3}s^{-1} at 0.5 Tm, diffusion-limited growth, TTT nose at 100 ps, and reproduce experimental onset at 5e11 K/s cooling, indicating homogeneous nucleation.
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Delineating the interplay effects of microstructure topology and residual stresses in ultrafast laser irradiated thin films
Hybrid TTM-MD simulations of gold thin films show microstructure configuration and topology dominate over grain size and orientation in controlling laser-induced melting and expansion, with tensile stresses increasing and compressive stresses decreasing deformation.
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Thermal Transport in Defective Uranium Nitride: Effects of Point Defects, Anharmonicity, and Electronic Contributions
Point defects reduce lattice thermal conductivity in UN at low temperatures with uranium interstitials causing broadest scattering, while electronic contributions dominate above 600 K and match experiment when included, becoming negligible in defective cases.
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Activity enhances transport while competing interactions preserve structure in colloidal microphase formers
Activity in SALR colloidal suspensions enhances particle transport while preserving microphase structure, producing a structure-dynamics decoupling.
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Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators
GNN-based MD simulators achieve stable structure-only initialization and reliable OOD generalization through inference-time physics optimization and a GNN barostat on elastic network compression tasks.
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Enhancing Performance Insight at Scale: A Heterogeneous Framework for Exascale Diagnostics
An accelerated hpcanalysis framework ingests performance data from 100,000 MPI ranks in 9.69 seconds, delivers up to 314x GPU speedup, maps network congestion on Aurora, and uses a new tri-dimensional model to identify 32.28% potential speedup in a GAMESS workload on Frontier.
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Characterization of Real Communication Patterns and Congestion Dynamics in HPC Interconnection Networks
The work extends VEF traces to model and detect congestion in HPC communication patterns from runs of NEST, GROMACS, LAMMPS, and PATMOS.
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From Perception to Autonomous Computational Modeling: A Multi-Agent Approach
A multi-agent LLM framework autonomously completes the full computational mechanics pipeline from a photograph to a code-compliant engineering report on a steel L-bracket example.
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Benchmarking thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former model
Systematic benchmarking finds Grønbech-Jensen-Farago Langevin thermostat most consistent for temperature and energy sampling in binary LJ glass simulations, at roughly double the cost and with friction-dependent diffusion.
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Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries
MACE-MPA-0 predicts Li diffusion Ea of 0.22 eV in LiF, fine-tuned version with 300 points gives 0.20 eV, close to DeePMD reference of 0.24 eV, using far less training data.
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Bottlenecks in Hamiltonian-Adaptive Resolution Simulation Method for Modeling Interfaces
H-AdResS simulations of interfaces require Langevin thermostatting and careful electrostatic treatment; Nose-Hoover and short-range DSF models produce artifacts, and bonded-degree-of-freedom interpolation cannot be added to the Hamiltonian.
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Node-Level Performance and Energy Characterization of Flagship Science Applications on SuperMUC-NG Phase 2
GPU offload on the tested system yields 4-12x throughput and up to 15x energy-efficiency gains over CPU-only execution for gromacs, lammps, OpenGadget3, AthenaK and dealii-X, with gains sensitive to problem granularity.
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Molecular dynamic simulation of multicomponent CoCrFeNiMn high-entropy alloy thin film deposition
MD simulation of CoCrFeMnNi HEA thin film deposition on Al(100) using Morse potentials yields a 6.1 nm mixed-phase film whose structure matches experimental data.