State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Quadri, Taiwo W. | - |
dc.contributor.author | Akpan, Ekemini D. | - |
dc.contributor.author | Elugoke, Saheed E. | - |
dc.contributor.author | Olasunkanmi, Lukman O. | - |
dc.contributor.author | Sheetal, Ashish Kumar | - |
dc.contributor.author | Singh, Ashish Kumar | - |
dc.contributor.author | Pani, Balaram | - |
dc.contributor.author | Tuteja, Jaya | - |
dc.contributor.author | Shukla, Sudhish Kumar | - |
dc.contributor.author | Verma, Chandrabhan | - |
dc.contributor.author | Lgaz, Hassane | - |
dc.contributor.author | Anadebe, Valentine Chikaodili | - |
dc.contributor.author | Barik, Rakesh Chandra | - |
dc.contributor.author | Guo, Lei | - |
dc.contributor.author | Alfantazi, Akram | - |
dc.contributor.author | Mothudi, Bakang M. | - |
dc.contributor.author | Ebenso, Eno E. | - |
dc.date.accessioned | 2025-04-24T02:01:18Z | - |
dc.date.available | 2025-04-24T02:01:18Z | - |
dc.date.issued | 2025-03 | - |
dc.identifier.issn | 1931-9401 | - |
dc.identifier.issn | 1931-9401 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/125112 | - |
dc.description.abstract | Artificial intelligence (AI) and machine learning (ML) have attracted the interest of the research community in recent years. ML has found applications in various areas, especially where relevant data that could be used for algorithm training and retraining are available. In this review article, ML has been discussed in relation to its applications in corrosion science, especially corrosion monitoring and control. ML tools and techniques, ML structure and modeling methods, and ML applications in corrosion monitoring were thoroughly discussed. Furthermore, detailed applications of ML in corrosion inhibitor design/modeling coupled with associated limitations and future perspectives were reported. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | AIP Publishing | - |
dc.title | State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1063/5.0228503 | - |
dc.identifier.scopusid | 2-s2.0-85214353958 | - |
dc.identifier.wosid | 001390808000001 | - |
dc.identifier.bibliographicCitation | APPLIED PHYSICS REVIEWS, v.12, no.1 | - |
dc.citation.title | APPLIED PHYSICS REVIEWS | - |
dc.citation.volume | 12 | - |
dc.citation.number | 1 | - |
dc.type.docType | Review | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.subject.keywordPlus | GENETIC FUNCTION APPROXIMATION | - |
dc.subject.keywordPlus | ATMOSPHERIC CORROSION | - |
dc.subject.keywordPlus | FEATURE-SELECTION | - |
dc.subject.keywordPlus | NEURAL-NETWORKS | - |
dc.subject.keywordPlus | QUANTITATIVE STRUCTURE | - |
dc.subject.keywordPlus | PITTING CORROSION | - |
dc.subject.keywordPlus | MILD-STEEL | - |
dc.subject.keywordPlus | ADVANCED STATISTICS | - |
dc.subject.keywordPlus | LINEAR-REGRESSION | - |
dc.subject.keywordPlus | PREDICTIVE MODELS | - |
dc.identifier.url | https://pubs.aip.org/aip/apr/article-abstract/12/1/011302/3329291/State-of-the-art-progress-on-artificial?redirectedFrom=fulltext | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.