Development of quantum machine learning to evaluate the corrosion inhibition capability of pyrimidine compounds-Reference-Cited by-同舟云学术

Development of quantum machine learning to evaluate the corrosion inhibition capability of pyrimidine compounds

Published:2024-06 Issue: Volume:39 Page:108758
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Akrom Muhamad,Rustad Supriadi,Dipojono Hermawan Kresno

Publisher

Elsevier BV

Reference86 articles.

1. The inhibition behavior of two pyrimidine-pyrazole derivatives against corrosion in hydrochloric solution: Experimental, surface analysis and in silico approach studies;Arrousse;Arab. J. Chem.,2020

2. Detailed experimental performance of two new pyrimidine-pyrazole derivatives as corrosion inhibitors for mild steel in HCl media combined with DFT/MDs simulations of bond breaking upon adsorption;Lachhab;Colloids Surf. A Physicochem Eng. Asp.,2024

3. Mitigation of corrosion in petroleum oil well/tubing steel using pyrimidines as efficient corrosion inhibitor: Experimental and theoretical investigation;Sarkar;Mater. Today Commun.,2021

4. Experimental and theoretical investigation to the mild steel’s corrosion inhibition using pyrazole pyrimidine derivative;Echihi;Chem. Data Collect.,2023

5. Pyrimidine derivatives as potential corrosion inhibitors for steel in acid medium – An overview;Rasheeda;Int. J. Corros. Scale Inhib.,2018

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A comprehensive approach utilizing quantum machine learning in the study of corrosion inhibition on quinoxaline compounds;Artificial Intelligence Chemistry;2024-12

2. Quantum machine learning for corrosion resistance in stainless steel;Materials Today Quantum;2024-09

3. Machine learning for pyrimidine corrosion inhibitor small dataset;Theoretical Chemistry Accounts;2024-08

4. Implementation of quantum machine learning in predicting corrosion inhibition efficiency of expired drugs;Materials Today Communications;2024-08

5. Prediction of Anti-Corrosion performance of new triazole derivatives via Machine learning;Computational and Theoretical Chemistry;2024-06