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Transferability of MACE Graph Neural Network for Range Corrected Δ-Machine Learning Potential QM/MM Applications

The Journal of Physical Chemistry B(2025)10.1021/acs.jpcb.5c02006Source: DataRank Database

Transferability of MACE Graph Neural Network for Range Corrected Δ-Machine Learning Potential QM/MM Applications is a research paper published in The Journal of Physical Chemistry B (2025). On theSindex it has a DataRank of 0.416. It has been cited 15 times.

N/A

0.416DataRank · unranked

Scored on demand from live citation data

Open Access15 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 3.90)OA: hybridTopics (15)IDs (PubMed, PMC, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.416

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (3)

Jinzhe Zeng ORCID,Darrin M. York ORCID,Timothy J. Giese ORCID

Live enrichment

PubMed:40418048 PMC:PMC12333372 OpenAlex:https://openalex.org/W4410731683

National Institutes of Health

Grant: GM62248

National Science Foundation

Grant: 2209718

NIGMS NIH HHS

Grant: R01 GM062248

NIGMS NIH HHS

Grant: R01 GM107485

FWCI

3.90

Citation Percentile

0.9%

Citation Trend

2025

2026

hybridLicense: cc-by

journalhttps://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.5c02006

publisherhttps://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.5c02006

journalhttps://doi.org/10.1021/acs.jpcb.5c02006

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40418048

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12333372

Fields of Study

Machine Learning in Materials ScienceMachine Learning and ELMComputational Drug Discovery Methods

Keywords

TransferabilityMaceComputer scienceArtificial neural networkRange (aeronautics)GraphArtificial intelligenceMachine learningTheoretical computer sciencePsychologyEngineeringAerospace engineering