ABOUT

The KIM Initiative

The founding conceptual structure of the Materials Innovation Infrastructure. SOURCE: National Science and Technology Council, 2021, Materials Genome Initiative Strategic Plan, A Report by the Subcommittee on the Materials Genome Initiative Committee on Technology, Washington, DC: Executive Office of the President, https://www.mgi.gov/sites/default/files/documents/MGI-2021-Strategic-Plan.pdf. Courtesy of the Materials Genome Initiative.SOURCE: NSTC Council, MGI Strategic Plan, 2021During the California Gold Rush, Levi Strauss provided tough pants, later called blue jeans, to help prospectors seeking gold do their work. A similar gold rush to discover new advanced materials is underway through the White House Materials Genome Initiative (MGI), supercharged by the artificial intelligence (AI) revolution. Through a collection of companion projects, the Knowledgebase of Interatomic Models (KIM) Initiative is providing the “blue jeans” for the community of materials science prospectors who are seeking to revolutionize technologies across the sciences.

The MGI vision is for “discovering, manufacturing, and deploying advanced materials twice as fast and at a fraction of the cost compared to traditional methods.” To do so, scientists must work together, combining advanced computations, experiments, and data. A key tool in the materials discovery toolbox are molecular simulations in which the behavior of a material is modeled by considering the interactions between its constituent atoms. This allows scientists to do “what if” experiments in a computer, trying out different material compositions without having to physically manufacture them, thereby saving time, money, and energy.

The collection of projects under the KIM INITIATIVE provide tools and resources to researchers in materials science and chemistry who are using molecular simulations to revolutionize technologies across the sciences.

FUNDING

The KIM INITIATIVE family of projects has been funded through the generous support of the National Science Foundation (NSF) and U.S. Department of Energy (DOE) through a series of grants:

    2014–2018, NSF Award 1408211, Collaborative Research: CDS&E: Systematic Multiscale Modeling using the Knowledgebase of Interatomic Models (KIM), E. B. Tadmor (PI), R. S. Elliott, J. P. Sethna
    2018–2024, NSF Award 1834251 Collaborative Research: Reliable Materials Simulation based on the Knowledgebase of Interatomic Models (KIM), E. B. Tadmor (PI), R. S. Elliott, G. Karypis, M. K. Transtrum
    2019–2024, NSF Award 1931304, Collaborative Research: Framework: Cyberloop for Accelerated Bionanomaterials Design, H. Heinz (PI), W. Im, E. B. Tadmor
    2020–2024, NSF Award 2039575, Data CI Pilot: CI-Based Collaborative Development of Data-Driven Interatomic Potentials for Predictive Molecular Simulations, E. B. Tadmor (PI), R. S. Elliott, S. Martiniani
    2022–2025, under the auspices of the DOE by LLNL under Contract DE-AC52-07NA27344, funded by LLNL LDRD tracking code 23-SI-006, Infrastructure for the LDRD-SI Automated Framework for Predictive Atomistic Materials Simulations with Uncertainty Quantification, E. B. Tadmor (PI)
    2023–2028, NSF Award 2311632, GOALI: Frameworks: At-Scale Heterogeneous Data based Adaptive Development Platform for Machine Learning Models for Material and Chemistry Discovery, S. Martiniani (PI), E. B. Tadmor, G. Karypis, E. Fuemmeler, A. Gupta, A. E. Roitberg, R. Hennig, M. Liu, M. K. Transtrum, H. Rangwala