Academic Journal
HEA-Bench: An AI-Agent-Optimized Calculator of High-Entropy Alloy and Oxide Descriptors and Phase-Prediction Rules.
| Title: | HEA-Bench: An AI-Agent-Optimized Calculator of High-Entropy Alloy and Oxide Descriptors and Phase-Prediction Rules. |
|---|---|
| Authors: | Fieser, David, Dewanjee, Unmanaa, Hu, Anming |
| Source: | Materials (1996-1944); Jul2026, Vol. 19 Issue 14, p3075, 18p |
| Subject Terms: | High-entropy alloys, Entropy, Atomic radius, Python programming language |
| Abstract: | The empirical descriptors of high-entropy alloys and oxides, from the mixing entropy and atomic-size mismatch to the Miedema enthalpies and the Ω , Φ , and φ stability parameters, are quoted in nearly every design study, yet they are reimplemented ad hoc by individual groups, by closed web calculators, and now inside language-model agent frameworks, where fabrication of property values is a documented failure mode. The resulting numbers disagree and cannot be traced or reproduced. We present HEA-Bench, an open calculator in which every descriptor is a closed-form expression over a curated, literature-cited element-property table, with the six canonical phase-prediction rules reported alongside their thresholds and sources rather than as predictions. One calculation core is delivered as a dependency-free Python (version 3.10 or later) library, a zero-install browser application, an offline desktop executable, and a Model Context Protocol server that exposes it to AI agents as deterministic tools, returning every value with its unit, citation key, and version so an agent's reasoning trace can be audited. The implementation reproduces published per-alloy and per-oxide anchor values to their printed precision and extends to high-entropy oxides in four structure families. The numerical instability of Ω near zero mixing enthalpy is quantified and exposed as a callable check. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: HEA-Bench: An AI-Agent-Optimized Calculator of High-Entropy Alloy and Oxide Descriptors and Phase-Prediction Rules. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Fieser%2C+David%22">Fieser, David</searchLink><br /><searchLink fieldCode="AR" term="%22Dewanjee%2C+Unmanaa%22">Dewanjee, Unmanaa</searchLink><br /><searchLink fieldCode="AR" term="%22Hu%2C+Anming%22">Hu, Anming</searchLink> – Name: TitleSource Label: Source Group: Src Data: Materials (1996-1944); Jul2026, Vol. 19 Issue 14, p3075, 18p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22High-entropy+alloys%22">High-entropy alloys</searchLink><br /><searchLink fieldCode="DE" term="%22Entropy%22">Entropy</searchLink><br /><searchLink fieldCode="DE" term="%22Atomic+radius%22">Atomic radius</searchLink><br /><searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The empirical descriptors of high-entropy alloys and oxides, from the mixing entropy and atomic-size mismatch to the Miedema enthalpies and the Ω , Φ , and φ stability parameters, are quoted in nearly every design study, yet they are reimplemented ad hoc by individual groups, by closed web calculators, and now inside language-model agent frameworks, where fabrication of property values is a documented failure mode. The resulting numbers disagree and cannot be traced or reproduced. We present HEA-Bench, an open calculator in which every descriptor is a closed-form expression over a curated, literature-cited element-property table, with the six canonical phase-prediction rules reported alongside their thresholds and sources rather than as predictions. One calculation core is delivered as a dependency-free Python (version 3.10 or later) library, a zero-install browser application, an offline desktop executable, and a Model Context Protocol server that exposes it to AI agents as deterministic tools, returning every value with its unit, citation key, and version so an agent's reasoning trace can be audited. The implementation reproduces published per-alloy and per-oxide anchor values to their printed precision and extends to high-entropy oxides in four structure families. The numerical instability of Ω near zero mixing enthalpy is quantified and exposed as a callable check. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Materials (1996-1944) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/ma19143075 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 3075 Subjects: – SubjectFull: High-entropy alloys Type: general – SubjectFull: Entropy Type: general – SubjectFull: Atomic radius Type: general – SubjectFull: Python programming language Type: general Titles: – TitleFull: HEA-Bench: An AI-Agent-Optimized Calculator of High-Entropy Alloy and Oxide Descriptors and Phase-Prediction Rules. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fieser, David – PersonEntity: Name: NameFull: Dewanjee, Unmanaa – PersonEntity: Name: NameFull: Hu, Anming IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 07 Text: Jul2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961944 Numbering: – Type: volume Value: 19 – Type: issue Value: 14 Titles: – TitleFull: Materials (1996-1944) Type: main |
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