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README.md
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@@ -40,7 +40,7 @@ table. MatPES is an initiative by the [Materials Virtual Lab] and the [Material
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1. **Accuracy.** MatPES is computed using static DFT calculations with stringent converegence criteria.
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Please refer to the `MatPESStaticSet` in [pymatgen] for details.
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2. **Comprehensiveness.** MatPES structures are sampled using a 2-stage version of DImensionality-Reduced
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Encoded Clusters with sTratified ([DIRECT]) sampling from a greatly expanded configuration of MD structures.
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3. **Quality.** MatPES includes computed data from the PBE functional, as well as the high fidelity r2SCAN meta-GGA
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functional with improved description across diverse bonding and chemistries.
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[M3GNet]: http://dx.doi.org/10.1038/s43588-022-00349-3
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[CHGNet]: http://doi.org/10.1038/s42256-023-00716-3
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[TensorNet]: https://arxiv.org/abs/2306.06482
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[DIRECT]: https//doi.org/10.1038/s41524-024-01227-4
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[maml]: https://materialsvirtuallab.github.io/maml/
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[MatGL]: https://matgl.ai
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[MatPES]: https://matpes.ai
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1. **Accuracy.** MatPES is computed using static DFT calculations with stringent converegence criteria.
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Please refer to the `MatPESStaticSet` in [pymatgen] for details.
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2. **Comprehensiveness.** MatPES structures are sampled using a 2-stage version of DImensionality-Reduced
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+
Encoded Clusters with sTratified ([DIRECT](https//doi.org/10.1038/s41524-024-01227-4)) sampling from a greatly expanded configuration of MD structures.
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3. **Quality.** MatPES includes computed data from the PBE functional, as well as the high fidelity r2SCAN meta-GGA
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functional with improved description across diverse bonding and chemistries.
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[M3GNet]: http://dx.doi.org/10.1038/s43588-022-00349-3
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[CHGNet]: http://doi.org/10.1038/s42256-023-00716-3
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[TensorNet]: https://arxiv.org/abs/2306.06482
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[maml]: https://materialsvirtuallab.github.io/maml/
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[MatGL]: https://matgl.ai
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[MatPES]: https://matpes.ai
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