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Cited by 566

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

A foundation model for atomistic materials chemistry

Open access
Batatia, Ilyes, Benner, Philipp, Chiang, Yuan, Elena, Alin M., Kovács, Dávid P., Riebesell, Janosh, Advincula, Xavier R., Asta, Mark, Avaylon, Matthew, Baldwin, William J., Berger, Fabian, Bernstein, Noam, Bhowmik, Arghya, Bigi, Filippo, Blau, Samuel M., Cărare, Vlad, Ceriotti, Michele, Chong, Sanggyu, Darby, James P., De, Sandip, Della Pia, Flaviano, Deringer, Volker L., Elijošius, Rokas, El-Machachi, Zakariya, Fako, Edvin, Falcioni, Fabio, Ferrari, Andrea C., Gardner, John L. A., Gawkowski, Mikołaj J., Genreith-Schriever, Annalena, George, Janine, Goodall, Rhys E. A., Grandel, Jonas, Grey, Clare P., Grigorev, Petr, Han, Shuang, Handley, Will, Heenen, Hendrik H., Hermansson, Kersti, Ho, Cheuk Hin, Hofmann, Stephan, Holm, Christian, Jaafar, Jad, Jakob, Konstantin S., Jung, Hyunwook, Kapil, Venkat, Kaplan, Aaron D., Karimitari, Nima, Kermode, James R., Kourtis, Panagiotis, Kroupa, Namu, Kullgren, Jolla, Kuner, Matthew C., Kuryla, Domantas, Liepuoniute, Guoda, Lin, Chen, Margraf, Johannes T., Magdău, Ioan-Bogdan, Michaelides, Angelos, Moore, J. Harry, Naik, Aakash A., Niblett, Samuel P., Norwood, Sam Walton, O’Neill, Niamh, Ortner, Christoph, Persson, Kristin A., Reuter, Karsten, Rosen, Andrew S., Rosset, Louise A. M., Schaaf, Lars L., Schran, Christoph, Shi, Benjamin X., Sivonxay, Eric, Stenczel, Tamás K., Sutton, Christopher, Svahn, Viktor, Swinburne, Thomas D., Tilly, Jules, van der Oord, Cas, Vargas, Santiago, Varga-Umbrich, Eszter, Vegge, Tejs, Vondrák, Martin, Wang, Yangshuai, Witt, William C., Wolf, Thomas, Zills, Fabian, Csányi, Gábor·2025·The Journal of Chemical Physics
DOI 10.1063/5.0297006
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Abstract

Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here, we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model—and its qualitative and at times quantitative accuracy—on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces, and even the dynamics of a small protein. The model can be applied out of the box as a starting or “foundation” model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users obtain reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step toward democratizing the revolution in atomic-scale modeling that has been brought about by ML force fields.

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Authors
Batatia, I., Benner, P., Chiang, Y., Elena, A. M., Kovács, D. P., Riebesell, J., Advincula, X. R., Asta, M., Avaylon, M., Baldwin, W. J., Berger, F., Bernstein, N., Bhowmik, A., Bigi, F., Blau, S. M., Cărare, V., Ceriotti, M., Chong, S., Darby, J. P., De, S., Della Pia, F., Deringer, V. L., Elijošius, R., El-Machachi, Z., Fako, E., Falcioni, F., Ferrari, A. C., Gardner, J. L. A., Gawkowski, M. J., Genreith-Schriever, A., George, J., Goodall, R. E. A., Grandel, J., Grey, C. P., Grigorev, P., Han, S., Handley, W., Heenen, H. H., Hermansson, K., Ho, C. H., Hofmann, S., Holm, C., Jaafar, J., Jakob, K. S., Jung, H., Kapil, V., Kaplan, A. D., Karimitari, N., Kermode, J. R., Kourtis, P., Kroupa, N., Kullgren, J., Kuner, M. C., Kuryla, D., Liepuoniute, G., Lin, C., Margraf, J. T., Magdău, I.-B., Michaelides, A., Moore, J. H., Naik, A. A., Niblett, S. P., Norwood, S. W., O’Neill, N., Ortner, C., Persson, K. A., Reuter, K., Rosen, A. S., Rosset, L. A. M., Schaaf, L. L., Schran, C., Shi, B. X., Sivonxay, E., Stenczel, T. K., Sutton, C., Svahn, V., Swinburne, T. D., Tilly, J., van der Oord, C., Vargas, S., Varga-Umbrich, E., Vegge, T., Vondrák, M., Wang, Y., Witt, W. C., Wolf, T., Zills, F., & Csányi, G.
Venue
The Journal of Chemical Physics
Publisher
AIP Publishing
Published
2025-11-13
Volume
163
Issue
18
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
DOI
10.1063/5.0297006
OpenAlex
W4416191329
Cited by
566
References
22
FWCI
103.17
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A foundation model for atomistic materials chemistry. https://app.cochat.ai/papers/10.1063/5.0297006
The paper
Batatia, I., Benner, P., Chiang, Y., Elena, A. M., Kovács, D. P., Riebesell, J., Advincula, X. R., Asta, M., Avaylon, M., Baldwin, W. J., Berger, F., Bernstein, N., Bhowmik, A., Bigi, F., Blau, S. M., Cărare, V., Ceriotti, M., Chong, S., Darby, J. P., . . . Csányi, G. (2025). A foundation model for atomistic materials chemistry. The Journal of Chemical Physics. https://doi.org/10.1063/5.0297006

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