31-Jan-2026
Happy 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.
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.
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