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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2024

Gold-Thiolate Nanocluster Dynamics Dataset and Supplementary Files

Supplementary information accompanying the article “Gold-Thiolate Nanocluster Dynamics and Intercluster Reactions Enabled by a Machine Learned Interatomic Potential” including the training/testing dataset, potential files, and simulation results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Revolutionizing Materials Design: The Intersection of Quantum Mechanics and Data Modeling

The field of materials design is currently experiencing a notable evolution, driven by the convergence of sophisticated computational methodologies based on first principles and data-driven modeling approaches. I will review our recent endeavors employing AI/ML to expedite first-principles simulations and mitigate traditional methods' temporal and spatial limitations. Central to our efforts is developing and utilizing ML interatomic potentials (MLPs) across a diverse spectrum of materials. We show that MLPs serve as invaluable tools for navigating the complexities of the simulations, such as understanding the behavior of MgO at extreme environments of ~1 terapascal and temperatures >10,000 Kelvin. Moreover, we show that MLPs can provide precise details of the intricate dynamics governing the oxidation processes of binary alloy systems due to the competition between surface segregation and reconstruction tendencies. In summation, advancements in MLPs open the door to fresh possibilities in material modeling and, ultimately, discovery.

Saidi, Wissam↗
DOE OSTI2024

Next-Generation Materials Design: Quantum Mechanics and Data-Driven Modeling

The future of materials design is rapidly advancing through the combination of quantum mechanics and data-driven modeling. These approaches integrate quantum principles with advanced data analysis, enabling precise insights into material behavior. This talk will highlight recent progress in using these methods for computational design, particularly in high-entropy alloy catalysts, emphasizing the role of hierarchical machine-learning architectures for accurate predictions. Additionally, I will discuss our work on developing machine learning interatomic potentials (MLPs) for single-element metals, metal oxides, and alloys under extreme conditions, focusing on melting behavior and phase properties at high temperatures and pressures. We have also refined our MLP models to capture dynamic surface interactions, such as CO2 and CO adsorption on MgO, using both static and molecular dynamics simulations. These models maintain high accuracy while significantly reducing computational costs compared to first-principles calculations. By enabling efficient and accurate simulations, this work supports broader community adoption, optimizes datasets for materials discovery, and extends the accessible time, size, and environmental conditions beyond the limits of experiments and traditional simulations.

machine learning↗
DOE OSTI2025

Atomistic Modeling of the Interphase Structure between Alumina and Al12Fe2Cr Quasicrystal Approximant

Molecular dynamics simulations are performed to study the stability of an fcc metallic interlayer phase between an iron aluminide quasicrystal approximant (QCA) phase (84.2 Al, 5.7 Fe, 5.4 Ni, and 4.7 at.% Cr) and aluminum oxides (α-Al 2 O 3 and γ-Al 2 O 3 ). The presence of the interlayer phase was experimentally observed in some regions of the inner diameter surface of a TPBAR cladding tube. The simulations employed existing many-body (MEAM and EAM) interatomic potentials to describe atomic interactions in the interlayer and QCA phases, and Buckingham+Coulomb pair interactions for the alumina and between the alumina and the QCA (or fcc). Interface systems of QCA/alumina, fec/alumina, and QCA/fcc are modeled and the fracture energy of the interfaces is calculated. Based on the fracture energies, for the γ-Al 2 O 3 , both MEAM and EAM suggest that the fcc interlayer phase would not form. For the α-Al 2 O 3 , the MEAM predicts that the fcc phase would form, however, the EAM predicts that it forms only if the α-Al 2 O 3 is Al-terminated at the interface. For the O-terminated α-Al 2 O 3 , the EAM predicts the fcc phase would not form, consistent with the results for γ-Al 2 O 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Lithium–Divertor Interactions and Helium/Hydrogen Trapping in Lithiated Metals (Final Technical Report)

The goal of this project was to develop a fundamental understanding of helium and hydrogen behavior in lithium, both in bulk and at interfaces with tungsten, in order to inform the design of lithium based plasma facing components for fusion devices. Over the course of the award, the project produced the first comprehensive, peer reviewed dataset describing helium energetics, migration behaviors, and defect interactions in lithium. The research demonstrated that helium behaves in ways not previously observed in any other body centered cubic (BCC) metal: its interstitial configurations are more stable than substitutional ones, and its migration barriers are extraordinarily low, in some cases more than an order of magnitude below those in tungsten or iron. These discoveries reveal that helium in lithium diffuses so rapidly that its transport may be dominated by translational motion rather than the vibrationally activated mechanisms that underpin conventional solid state diffusion. This work lays a scientific foundation for understanding gas retention, bubble formation, and wall evolution in lithium based fusion environments and provides new computational tools, most notably a newly developed Li–He interatomic potential, for advancing future modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

User Manual - HydraGNN v5.0: Distributed Implementation of Multi-Tasking Graph Neural Networks

This document serves as the user manual for HydraGNN v5.0, a scalable graph neural network (GNN) architecture for simultaneous prediction of multiple target properties using multi-task learning (MTL). This version of HydraGNN has been developed primarily to support the development, training, and deployment of predictive graph-based deep learning (DL) models for atomistic materials modeling. HydraGNN is templated over 13 message-passing policies, including invariant models (GIN, PNA, PNAPlus, GAT, MFC, CGCNN, SAGE, SchNet, DimeNet) and equivariant models (EGNN, PNAEq, PAINN, MACE), and supports distributed training via distributed data parallelism (DDP), DeepSpeed, and Fully Sharded Data Parallelism (FSDP) on leadership-class supercomputers. Although HydraGNN can be applied to problems beyond atomistic materials modeling, its current use is confined to homogeneous graphs. Additional capabilities include machine-learned interatomic potentials with energy-conserving forces, General, Powerful, and Scalable Graph Transformer (GraphGPS) global attention, periodic boundary conditions, hyperparameter optimization, mixed-precision training, and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Data and Code for Atomic Scale Etching of Diamond: Insights from Molecular Dynamics Simulations

This work investigates the effects of argon ions, hydrogen atoms, and hydrogen ions on the diamond (100) surface using classical molecular dynamics simulations. The purpose of this investigation was to asses plasma processing techniques for applications in quantum device manufacturing. The simulations suggest that combining argon ion smoothing with selective, near threshold energy H removal of amorphous C could be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices. Results were found to differ significantly with interatomic potential, and an analysis of these differences was also carried out. Included in this repository are LAMMPS source files, input scripts, and plotting scripts required to reproduce the data. Also included are the output data required to make all the plots included in the associated publication.

Brenner↗
NASA NTRS1975

Lattice model theory of the equation of state covering the gas, liquid, and solid phases

The three stable states of matter and the corresponding phase transitions were obtained with a single model. Patterned after Lennard-Jones and Devonshires's theory, a simple cubic lattice model containing two fcc sublattices (alpha and beta) is adopted. The interatomic potential is taken to be the Lennard-Jones (6-12) potential. Employing the cluster variation method, the Weiss and the pair approximations on the lattice gas failed to give the correct phase diagrams. Hybrid approximations were devised to describe the lattice term in the free energy. A lattice vibration term corresponding to a free volume correction is included semi-phenomenologically. The combinations of the lattice part and the free volume part yield the three states and the proper phase diagrams. To determine the coexistence regions, the equalities of the pressure and Gibbs free energy per molecule of the coexisting phases were utilized. The ordered branch of the free energy gives rise to the solid phase while the disordered branch yields the gas and liquid phases. It is observed that the triple point and the critical point quantities, the phase diagrams and the coexistence regions plotted are in good agreement with the experimental values and graphs for argon.

Bonavito, N. L.↗
NASA NTRS1976

Computer simulation of screw dislocation in aluminum

The atomic structure in a 110 screw dislocation core for aluminum is obtained by computer simulation. The lattice statics technique is employed since it entails no artificially imposed elastic boundary around the defect. The interatomic potential has no adjustable parameters and was derived from pseudopotential theory. The resulting atomic displacements were allowed to relax in all three dimensions.

Esterling, D. M.↗
NASA NTRS1978

Solid-liquid phase transition in argon

Starting from the Lennard-Jones interatomic potential, a modified cell theory has been used to describe the solid-liquid phase transition in argon. The cell-size variations may be evaluated by a self-consistent condition. With the inclusion of cell-size variations, the transition temperature, the solid and liquid densities, and the liquid-phase radial-distribution functions have been calculated. These ab initio results are in satisfactory agreement with molecular-dynamics calculations as well as experimental data on argon.

Tsang, T.↗
NASA NTRS1980

Dislocation dissociation in some f.c.c. metals

The dissociation of a perfect screw dislocation into a stacking fault in an f.c.c. lattice is modeled by the modified lattice statics. The interatomic potentials are obtained from the work of Esterling and Swaroop and differ substantially from those empirical potentials usually employed in defect simulations. The calculated stacking fault widths for aluminum, copper, and silver are in good agreement with weak beam microscopy results.

Esterling, D. M.↗
NASA NTRS1980

Time correlation functions in classical dense fluids

The velocity autocorrelation functions and memory functions of dense classical fluids may be directly obtained from the static radial distribution function g(r) in an approximate way. Following the Mori projection operator formalism, the memory functions may be related to the fluctuating force correlation. At low densities, these functions may be evaluated by following the trajectories of particle pairs in the interatomic potential. At higher densities, the force correlation functions can be evaluated approximately from particle pair trajectories via the potential of the mean force. The results for argon fluids at various densities and temperatures agree satisfactorily with the molecular dynamics and the Enskog values. The decrease of the diffusion coefficient with density is partly due to the nature of g(r) which reflects the stronger clustering of atoms at higher densities.

Tsang, T.↗
NASA NTRS1981

Far wing depolarization of light - Generalized absorption profiles

An absorption (and/or emission) event which takes place during a strong collision is called a 'correlated event'. It is discussed how correlated events affect the far red wing depolarization of fluorescence. Attention is given to an atomic vapor which is irradiated by linearly polarized light of a frequency on the red side of the resonance line. Two limiting cases are considered, corresponding to excitation in the impact region and in the quasi-static wing. In the quasi-static wing, absorption of a photon followed by fluorescence (rather than Rayleigh scattering), occurs mostly during a collision. Correlated events dominate the scattering process. Expressions derived for the polarization of the fluorescent light are applied to far red wing depolarization. It is found that the polarization of the fluorescent light does not go to zero in the far wing, but depends crucially on the detailed nature of the anisotropy in the long-range part of the interatomic potential.

Thomann, P.↗
NASA NTRS1982

A study pertaining to a very low temperature hydrogen maser feasibility

Very low temperature atomic hydrogen masers were developed. The advantages over room temperature hydrogen masers include higher radiated power due to the higher beam intensities possible using low temperature techniques and the much smaller electron spin flip cross section at low temperatures, lower cavity and amplifier noise temperatures, increased stability against mechanical creep at low temperatures, and opportunities to extend H atom collision studies to low temperatures, where quantum effects and details of the interatomic potentials are much more important.

Crampton, S. B.↗
NASA NTRS1982

Anharmonic properties of solids from measurements of the stress acoustic constant

The equations of elastic motion and their solutions are generalized in order to include nonzero homogeneous initial stresses and redefine the stress acoustic constants to include the effect of initial stress. In deriving the relationship between the stress acoustic constants and the strain-generalized Gruneisen parameters, implications in material anharmonicity and nonlinear thermoelasticity are discovered. It is found that the linear change in velocity obtained from these measurements is a nonlinear process resulting from anharmonicity in the interatomic potential. In addition, the thermal expansion coefficient can also be expressed in terms of linear combinations.

Cantrell, J. H., Jr.↗
NASA NTRS1985

Statistical mechanics of light elements at high pressure. VIII - Thomas-Fermi-Dirac theory for binary mixtures of H with He, C, and O

We present three-dimensional Thomas-Fermi-Dirac calculations of lattice mixing energies of hydrogen with carbon and oxygen atoms, respectively. The results are used to derive effective interatomic potentials for use in liquid-state mixture calculations. We then use the potentials to derive analytic expressions for binary mixture-free energies and to map out the phase diagrams of mixtures of hydrogen with, respectively, helium, carbon, and oxygen, over a pressure range of about 5 to about 10 to the 3rd Mbar. Within this pressure range, all three of the latter elements are found to have unlimited solubility in metallic hydrogen over a temperature range which lies above their pure-element melting temperatures, and which includes likely interior temperatures in the Jovian planets.

Hubbard, W. B.↗