Jekyll2026-04-18T13:39:34-05:00https://openkim.org/news.xmlOpenKIM - The Knowledgebase of Interatomic Models | NewsOpenKIM is an online suite of open source tools for molecular simulation of materials. These tools help to make molecular simulation more accessible and more reliable. Within OpenKIM, you will find an online resource for standardized testing and long-term warehousing of interatomic models and data, and an application programming interface (API) standard for coupling atomistic simulation codes and interatomic potential subroutines.OpenKIMsupport@openkim.orghttps://openkim.orgNew PolyMLP Driver with various parameterizations now available2026-03-18T00:00:00-05:002026-03-18T00:00:00-05:00https://openkim.org/news/2026-03-18A new polynomial machine learning potential (PolyMLP) model driver with various parameterizations is now available in OpenKIM (DOI: 10.25950/948ad72c). Accompanying the driver are 837 parametrizations for 167 material systems imported from the PolyMLP Repository developed by Dr. Atsuto Seko (Kyoto University). Each material system except CuAgAu has several parametrizations which all lay on a Pareto front of computational time and RMS accuracy. For information regarding the different models available, as well as to see which one is recommended as the best trade-off between speed and accuracy, see the "disclaimer" metadata field of any model for the system you're interested in.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgkim-api-2.4.2 released: Bug fixes, retries and improved logs2026-03-06T00:00:00-06:002026-03-06T00:00:00-06:00https://openkim.org/news/2026-03-06This release adds logging of paths to the API and model libraries to facilitate debugging installation issues, for example in cases where two instances of the API are installed. The kim-api-collections-management utility will now attempt to download items several times before failing due to web errors. Finally, two bugs relating to the new base64-encode method of encoding model parameters were fixed: one that corrupted parameter files on ARM64 only, and one that corrupted citation info printed in LAMMPS on all platforms. See the NEWS file for a more complete summary of changes.

For installation instructions, see the Obtaining KIM Models page.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgA paper demonstrating a new approach to data selection during active learning of interatomic potentials has been published2026-02-18T00:00:00-06:002026-02-18T00:00:00-06:00https://openkim.org/news/2026-02-18A collaborative paper between the OpenKIM team and several other organizations has been published in Applied Physics Letters. Titled "An information-matching approach to optimal experimental design and active learning", the paper demonstrates the use of the Fisher information matrix to select the most informative training data to most accurately predict a specific quantity of interest (QoI). The paper demonstrates several applications across disciplines, including power systems, underwater acoustics, and interatomic potentials (IPs). The IP examples demonstrate fitting Stillinger-Weber potentials for MoS2 and Si to reproduce QoIs such as equations of state, elastic constants, and phonons using a minimal training dataset selected using the proposed method. The IP fitting workflow is enabled by the KLIFF fitting framework and the KIM API.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgKIM Quarterly Update (January 2026)2026-01-31T00:00:00-06:002026-01-31T00:00:00-06:00https://openkim.org/news/2026-01-31Happy new year! We hope you had a pleasant winter holiday and wish you a productive 2026. We have some exciting updates to share, especially for users interested in machine learning potentials.

Announcements

  • A new generalized embedded-atom method (GEAM) model driver with various parameterizations is now available in OpenKIM. Originally developed by Amit Samanta and coworkers at LLNL, GEAM is a data-driven interatomic potential aimed at modeling primarily BCC metals with accuracy comparable to machine learning potentials. See the announcement here.
  • The universal MACE-MP-0-a medium foundation model is now available as a KIM Portable Model using the TorchML Model Driver, enabling plug-and-play compatibility with any KIM API compliant simulator code for this venerable interatomic potential. See the announcement here.
  • Because providing the machine learning requirements for the TorchML Model Driver can be difficult on bare metal, we have developed a version of the KIM Developer Platform Docker image with all prerequisites installed. It can be used with Docker or other container software such as Singularity/Apptainer or Podman to run TorchML Portable Models out of the box, including support for utilizing the host GPU. See the documentation here.
  • We have significantly improved the reproducibility of computation results reported in OpenKIM by consolidating the containers that our calculations are run in. The "profiling.container-id" key reported with each result contains a version number that corresponds to a release of the KIM Developer Platform packaging the exact environment used for the computation. This key can be found by inspecting the "pipelinespec.edn" file provided with each result (see example here), or by querying the OpenKIM database.
  • A new Test Driver for computing monovacancies in arbitrary crystals under the Crystal Genome (XtalG) framework is now available. It computes the relaxed and unrelaxed formation energies and relaxation volumes for each symmetrically distinct site in any crystal, as well as relaxed and unrelaxed effective formation energies for a composition-preserving distribution of vacancies. Like all XtalG Test Drivers, it is available as a standalone Python class as part of the kimvv package for computations on users' own models and structures. See the announcement here.

Ongoing Developments

  • Additional Crystal Genome (XtalG) Test Drivers are in active development, including phonons and finite temperature properties such as Gibbs free energy, heat capacity, and anisotropic thermal expansion coefficients.

How to stay up-to-date

]]>OpenKIMsupport@openkim.orghttps://openkim.orgNew Crystal Genome Test Driver for vacancies now available2026-01-31T00:00:00-06:002026-01-31T00:00:00-06:00https://openkim.org/news/3A new Test Driver for computing monovacancies in arbitrary crystals is now available in OpenKIM (DOI: 10.25950/cea3ae2e). It computes the relaxed and unrelaxed formation energies and relaxation volumes for each symmetrically distinct site in any crystal, as well as relaxed and unrelaxed effective formation energies for a composition-preserving distribution of vacancies. It was developed by Eric Fuemmeler based on previous work by Junhao Li. As part of the Crystal Genome (XtalG) framework, results will become available on the material pages accessible through the "Search for Predictions" interface on openkim.org as they are computed. As with all XtalG Test Drivers, it is also available as a standalone Python class, in this case VacancyFormationEnergyRelaxationVolumeCrystal, as part of the kimvv Python package. This enables users to obtain these material properties for any crystal using their own interatomic model. Supported models include all KIM API compliant models, including any LAMMPS pair_style through the Simulator Model mechanism, as well as any ASE Calculator, including quantum-mechanical calculators.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgMACE-MP-0a medium now available in OpenKIM2026-01-31T00:00:00-06:002026-01-31T00:00:00-06:00https://openkim.org/news/2The MACE-MP-0a medium universal foundation model is now available in OpenKIM (DOI: 10.25950/ccbf69e7) as a Portable Model using the TorchML Model Driver. It is a Message Passing Neural Network (MPNN) trained on over 150,000 inorganic crystals, capable of zero-shot prediction for a wide range of chemical systems. The medium variant offers an optimal trade-off between computational cost and accuracy. Its publication on OpenKIM brings the plug-and-play compatibility with any KIM API compliant simulator code to this venerable interatomic potential.

Because providing the machine learning requirements for the TorchML Model Driver can be difficult on bare metal, we have also developed a version of the KIM Developer Platform Docker image with all prerequisites installed. It can be used with Docker or other container software such as Singularity/Apptainer or Podman to run TorchML Portable Models out of the box, including support for utilizing the host GPU. See the documentation here.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgNew GEAM Driver with a various parameterizations now available2026-01-30T00:00:00-06:002026-01-30T00:00:00-06:00https://openkim.org/news/2026-01-30A new generalized embedded-atom method (GEAM) model driver with various parameterizations is now available in OpenKIM (DOI: 10.25950/835fca74). The driver was adapted by Chloe Zeller and Woo Kyun Kim from a LAMMPS implementation of GEAM by Amit Samanta and coworkers at LLNL. This Driver is compatible with all simulators compatible with the KIM API. Currently (30-Jan-2026), there are seven parameterizations (KIM Models) available for this Driver for a variety of metallic material systems. GEAM is a data-driven interatomic potential aimed at modeling primarily BCC metals with accuracy comparable to machine learning potentials. It includes contributions from embedding energy, two- and three-body interactions, and nonlocal many-body interaction terms. The use of basis functions provides sufficient flexibility to model diverse atomic environments and simplifies the optimization of free parameters.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgKIM Quarterly Update (October 2025)2025-10-31T00:00:00-05:002025-10-31T00:00:00-05:00https://openkim.org/news/2025-10-31Welcome to the final KIM Quarterly Update for 2025! We hope your year has gone well and wish you a pleasant end of the year and holiday season. We have some exciting announcements regarding OpenKIM and related projects.

Announcements

  • The openkim.org front page has been redesigned to accommodate the ever-growing number of calculation results available for complex, multi-species crystals as part of the Crystal Genome framework. The streamlined interface allows users to navigate results for thousands of different materials using the new "Search for Predictions" button. All previous information and functionality is still present through the top menu bar and the content tabs below the new search bar.
  • The new Test Driver for computing crystal structure as a function of hydrostatic pressure for arbitrary crystals has been published. Unlike typical isotropic scans of potential energy vs. lattice constant, this Test Driver scans over a pressure range and reports resulting anisotropic changes in the lattice parameters, as well as internal degrees of freedom. As with all new OpenKIM test drivers developed under the Crystal Genome framework, it is available for use with custom potentials (ASE calculators or KIM API-compliant models) through the kimvv Python package.
  • A video of a tutorial introducing Crystal Genome, the new OpenKIM front page, and the kimvv package is available here, recorded as part of the 2025 LAMMPS Workshop and Symposium.
  • Julia bindings for the KIM API have been released as KIM_API.jl. This package complements the KIM ecosystem’s cross-language support, making the KIM API Portable Models usable seamlessly from Fortran, C, C++, Python, and now Julia. Examples for usage with the Molly.jl simulator, as well as low-level use, can be found here. Full documentation available here.
  • We are pleased to announce the public release of the Orchestrator Python framework for building, training, and analyzing interatomic potentials and running MD simulations. This software was developed as part of a Laboratory Directed Research and Development (LDRD) Strategic Initiative at Lawrence Livermore National Lab in collaboration with the OpenKIM and Colabfit teams.

Ongoing Developments

  • Additional Crystal Genome Test Drivers are in active development, including vacancy formation energy, phonons, and finite temperature properties such as Gibbs free energy, heat capacity, and anisotropic thermal expansion coefficients.

How to stay up-to-date

]]>OpenKIMsupport@openkim.orghttps://openkim.orgKIM_API.jl 1.0: Bringing KIM API support to Julia2025-10-27T00:00:00-05:002025-10-27T00:00:00-05:00https://openkim.org/news/2025-10-27We are pleased to announce the release of KIM_API.jl, the official Julia binding for the KIM API. This package complements the KIM ecosystem’s cross-language support, making the KIM API Portable Models usable seamlessly from Fortran, C, C++, Python, and now Julia. Researchers and developers can build, test, and deploy interatomic models in their preferred environment without compromising reproducibility or performance.

KIM_API.jl provides both low-level and high-level interfaces to KIM models, simplifying the integration of OpenKIM Portable Models into Julia-based atomistic simulation workflows. It offers out-of-the-box support for popular Julia-based simulators such as Molly.jl, and features robust memory safety, multi-unit support, and efficient neighbor-list generation, all while maintaining full compatibility with the established KIM API.

This release represents a significant milestone toward KIM’s vision of a unified, language-independent framework for portable and reproducible interatomic models. For installation and usage details, visit the documentation site.

]]>OpenKIMsupport@openkim.orghttps://openkim.orgNew OpenKIM front page launched2025-08-07T00:00:00-05:002025-08-07T00:00:00-05:00https://openkim.org/news/2025-08-07We are pleased to unveil our new https://openkim.org front page. The streamlined interface allows users to navigate results for thousands of different materials using the new "Search for Predictions" button. All previous information and functionality is still present through the top menu bar and the content tabs below the new search bar. We encourage you to explore all the new results!

]]>OpenKIMsupport@openkim.orghttps://openkim.org