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Data-driven and computational insights into borophene: Integrating machine learning with DFT and AI.

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Title: Data-driven and computational insights into borophene: Integrating machine learning with DFT and AI.
Authors: Patel, Rutu1 (AUTHOR) rutupatel114538@gmail.com, Chaudhary, Mayankkumar L.1 (AUTHOR) mayank.chaudhary1807@gmail.com, Gupta, Ram K.1,2 (AUTHOR) ramguptamsu@gmail.com
Source: Coordination Chemistry Reviews. Mar2026, Vol. 550, pN.PAG-N.PAG. 1p.
Database: Academic Search Ultimate
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Header DbId: asn
DbLabel: Academic Search Ultimate
An: 190300219
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Data-driven and computational insights into borophene: Integrating machine learning with DFT and AI.
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  Data: <searchLink fieldCode="JN" term="%22Coordination+Chemistry+Reviews%22">Coordination Chemistry Reviews</searchLink>. Mar2026, Vol. 550, pN.PAG-N.PAG. 1p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=190300219
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.ccr.2025.217385
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      – Code: eng
        Text: English
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      – TitleFull: Data-driven and computational insights into borophene: Integrating machine learning with DFT and AI.
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            NameFull: Patel, Rutu
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            NameFull: Chaudhary, Mayankkumar L.
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              Text: Mar2026
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              Y: 2026
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              Value: 550
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