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Using physical property surrogate models to perform accelerated multi-fidelity optimization of force field parameters

Digital Discovery(2023)10.1039/d2dd00138aSource: DataRank Database

Using physical property surrogate models to perform accelerated multi-fidelity optimization of force field parameters is a research paper published in Digital Discovery (2023). On theSindex it has a DataRank of 0. It has been cited 14 times.

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0DataRank · unranked

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Open Access14 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 2.42)OA: goldTopics (17)IDs (PubMed, PMC, OpenAlex)Annotations (1)

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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Authors (2)

Michael R. Shirts ORCID,Owen Madin ORCID

Live enrichment

PubMed:37312680 PMC:PMC10259372 OpenAlex:https://openalex.org/W4375810057

National Institutes of Health

Grant: R01GM132386

National Institutes of Health

Grant: P30CA008748

FWCI

2.42

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://pubs.rsc.org/en/content/articlepdf/2023/dd/d2dd00138a

publisherhttps://pubs.rsc.org/en/content/articlepdf/2023/dd/d2dd00138a

publisherhttp://pubs.rsc.org/en/content/articlepdf/2023/DD/D2DD00138A

journalhttps://doi.org/10.1039/d2dd00138a

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37312680

Fields of Study

Advanced Multi-Objective Optimization AlgorithmsHeat Transfer and OptimizationModel Reduction and Neural Networks

Keywords

FidelityProperty (philosophy)Surrogate modelField (mathematics)Force field (fiction)Computer sciencePhysical propertyMathematical optimizationHigh fidelityMathematicsArtificial intelligenceEngineeringPhysicsMachine learning

Using physical property surrogate models to perform accelerated multi-fidelity optimization of force field parameters

FAIR Checklist

Authors (2)

Funding (2 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)