A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement
dc.contributor.author | Campari, Alessandro | |
dc.contributor.author | Alikhani Darabi, Maryam | |
dc.contributor.author | Alvaro, Antonio | |
dc.contributor.author | Ustolin, Federico | |
dc.contributor.author | Paltrinieri, Nicola | |
dc.date.accessioned | 2023-11-29T07:49:04Z | |
dc.date.available | 2023-11-29T07:49:04Z | |
dc.date.created | 2023-05-31T10:15:16Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Chemical Engineering Transactions. 2023, 99 193-198. | en_US |
dc.identifier.issn | 1974-9791 | |
dc.identifier.uri | https://hdl.handle.net/11250/3105129 | |
dc.language.iso | eng | en_US |
dc.title | A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement | en_US |
dc.title.alternative | A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.pagenumber | 193-198 | en_US |
dc.source.volume | 99 | en_US |
dc.source.journal | Chemical Engineering Transactions | en_US |
dc.identifier.doi | 10.3303/CET2399033 | |
dc.identifier.cristin | 2150363 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 |