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SMILES-based machine learning enables the prediction of corrosion inhibition capacity.

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Title: SMILES-based machine learning enables the prediction of corrosion inhibition capacity.
Authors: Akrom, Muhamad1,2, m.akrom@dsn.dinus.ac.id, Rustad, Supriadi2, srustad@dsn.dinus.ac.id, Dipojono, Hermawan Kresno3, dipojono@itb.ac.id
Source: MRS Communications; Jun2024, Vol. 14 Issue 3, p379-387, 9p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 178234005
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: SMILES-based machine learning enables the prediction of corrosion inhibition capacity.
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  Data: <searchLink fieldCode="AU" term="%22Akrom%2C+Muhamad%22">Akrom, Muhamad</searchLink><relatesTo>1,2</relatesTo>, <i>m.akrom@dsn.dinus.ac.id</i><br /><searchLink fieldCode="AU" term="%22Rustad%2C+Supriadi%22">Rustad, Supriadi</searchLink><relatesTo>2</relatesTo>, <i>srustad@dsn.dinus.ac.id</i><br /><searchLink fieldCode="AU" term="%22Dipojono%2C+Hermawan+Kresno%22">Dipojono, Hermawan Kresno</searchLink><relatesTo>3</relatesTo>, <i>dipojono@itb.ac.id</i>
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  Data: <searchLink fieldCode="JN" term="%22MRS+Communications%22">MRS Communications</searchLink>; Jun2024, Vol. 14 Issue 3, p379-387, 9p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=178234005
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1557/s43579-024-00551-6
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 9
        StartPage: 379
    Titles:
      – TitleFull: SMILES-based machine learning enables the prediction of corrosion inhibition capacity.
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            NameFull: Akrom, Muhamad
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            NameFull: Rustad, Supriadi
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            NameFull: Dipojono, Hermawan Kresno
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            – D: 01
              M: 06
              Text: Jun2024
              Type: published
              Y: 2024
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              Value: 14
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              Value: 3
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            – TitleFull: MRS Communications
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