State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors

  • Quadri, Taiwo W.
  • Akpan, Ekemini D.
  • Elugoke, Saheed E.
  • Olasunkanmi, Lukman O.
  • Sheetal, Ashish Kumar
  • ... Lgaz, Hassane
  • 외 11명
Citations

WEB OF SCIENCE

13
Citations

SCOPUS

15

초록

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.

키워드

GENETIC FUNCTION APPROXIMATIONATMOSPHERIC CORROSIONFEATURE-SELECTIONNEURAL-NETWORKSQUANTITATIVE STRUCTUREPITTING CORROSIONMILD-STEELADVANCED STATISTICSLINEAR-REGRESSIONPREDICTIVE MODELS
제목
State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors
저자
Quadri, Taiwo W.Akpan, Ekemini D.Elugoke, Saheed E.Olasunkanmi, Lukman O.Sheetal, Ashish KumarSingh, Ashish KumarPani, BalaramTuteja, JayaShukla, Sudhish KumarVerma, ChandrabhanLgaz, HassaneAnadebe, Valentine ChikaodiliBarik, Rakesh ChandraGuo, LeiAlfantazi, AkramMothudi, Bakang M.Ebenso, Eno E.
DOI
10.1063/5.0228503
발행일
2025-03
유형
Review
저널명
Applied Physics Reviews
12
1