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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Evaluating Universal Machine Learning Force Fields Against Experimental Measurements

Authors: Sajid Mannan; Vaibhav Bihani; Carmelo Gonzales; Kin Long Kelvin Lee; Nitya Nand Gosvami; Sayan Ranu; Santiago Miret; +1 Authors

Evaluating Universal Machine Learning Force Fields Against Experimental Measurements

Abstract

The MinX dataset has been meticulously curated and handcrafted from different database to serve as a reliable benchmark data for validating UMLFFs against experimental mineral structures. The main goal of releasing this data is to reduce the complexity and inconsistencies often encountered with real-world minerals. By providing a experimentally validated structures, we aim to facilitate consistent and reproducible benchmarking across the community. 

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average