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Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability.

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Title: Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability.
Authors: Allec, Sarah I.1, Lu, Xiaonan2, Cassar, Daniel R.3,4, Nguyen, Xuan T.5, Hegde, Vinay I.1, Mahadevan, Thiruvillamalai5, Peterson, Miroslava2, Du, Jincheng5, Riley, Brian J.2, Vienna, John D.2, Saal, James E.1, jsaal@citrine.io
Source: Journal of the American Ceramic Society; Dec2024, Vol. 107 Issue 12, p7784-7799, 16p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 180048199
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+the+American+Ceramic+Society%22">Journal of the American Ceramic Society</searchLink>; Dec2024, Vol. 107 Issue 12, p7784-7799, 16p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=180048199
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        Value: 10.1111/jace.19937
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              Text: Dec2024
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              Y: 2024
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