Cited by Robust Machine Learning for Predicting Thermal Stability of Metal-Organic Framework

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

Taiwo W. Quadri, Ekemini D. Akpan, Saheed E. Elugoke

et al.

Applied Physics Reviews, Journal Year: 2025, Volume and Issue: 12(1)

Published: Jan. 6, 2025

Artificial intelligence (AI) and machine learning (ML) have attracted the interest of research community in recent years. ML has found applications various areas, especially where relevant data that could be used for algorithm training retraining are available. In this review article, been discussed relation to its corrosion science, monitoring control. tools techniques, structure modeling methods, were thoroughly discussed. Furthermore, detailed inhibitor design/modeling coupled with associated limitations future perspectives reported.

Language: Английский

Citations

Machine Learning-Based Prediction of Corrosion Inhibition Efficiency of Expired Pharmaceuticals: Model Development and Application DOI

Dzaki Asari Surya Putra,

Nibras Bahy Ardyansyah,

Nicholaus Verdhy Putranto

et al.

Journal of Bio- and Tribo-Corrosion, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 21, 2025

Language: Английский

Citations

Stacking Classical-Quantum Hybrid Learner Approach for Corrosion Inhibition Efficiency of N-Heterocyclic Compounds DOI

Muhamad Akrom, Supriadi Rustad,

T. Sutojo

et al.

Results in Surfaces and Interfaces, Journal Year: 2025, Volume and Issue: unknown, P. 100462 - 100462

Published: Feb. 1, 2025

Language: Английский

Citations

Robust Machine Learning for Predicting Thermal Stability of Metal-Organic Framework DOI

Harun Al Azies, Muhamad Akrom, Supriadi Rustad

et al.

Chemistry Africa, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 30, 2024

Language: Английский

Citations