Academic Journal

HEA-Bench: An AI-Agent-Optimized Calculator of High-Entropy Alloy and Oxide Descriptors and Phase-Prediction Rules.

Bibliographic Details
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]
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. (Copyright applies to all Abstracts.)
Database: Complementary Index
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edb&genre=article&issn=19961944&ISBN=&volume=19&issue=14&date=20260715&spage=3075&pages=3075-3092&title=Materials (1996-1944)&atitle=HEA-Bench%3A%20An%20AI-Agent-Optimized%20Calculator%20of%20High-Entropy%20Alloy%20and%20Oxide%20Descriptors%20and%20Phase-Prediction%20Rules.&aulast=Fieser%2C%20David&id=DOI:10.3390/ma19143075
    Name: Full Text Finder (for New FTF UI) (ns324271)
    Category: fullText
    Text: Full Text Finder
    MouseOverText: Full Text Finder
Header DbId: edb
DbLabel: Complementary Index
An: 195806514
RelevancyScore: 1082
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1082.42224121094
IllustrationInfo
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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=195806514
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
ResultId 1