Understanding the synergistic inhibition effect of hydrosol extract derivatives as eco-friendly anti-corrosive for copper alloy: GC–MS Identification, An Electrochemical …

A Chraka, I Raissouni, J Kassout, M Ezzaki… - Journal of Molecular …, 2023 - Elsevier
The research on green sources of corrosion inhibitors has gained significant traction in
recent times due to their cost-effectiveness and environmentally friendly nature. In this study …

Examination of the main chemical components of essential oil of Syzygium aromaticum as a corrosion inhibitor on the mild steel in 0.5 M HCl medium

A Acidi, A Sedik, A Rizi, R Bouasla, KO Rachedi… - Journal of Molecular …, 2023 - Elsevier
The study delves into the versatile applications of essential oils, natural aromatic
compounds derived from plants through hydro-distillation or cold extraction, across …

Data-driven investigation to model the corrosion inhibition efficiency of Pyrimidine-Pyrazole hybrid corrosion inhibitors

M Akrom, S Rustad, AG Saputro… - … and Theoretical Chemistry, 2023 - Elsevier
This paper proposes a quantitative structure–property relationship model (QSPR) based on
machine learning (ML) for a pyrimidine-pyrazole hybrid as a corrosion inhibitor. Based on …

A combination of machine learning model and density functional theory method to predict corrosion inhibition performance of new diazine derivative compounds

M Akrom, S Rustad, AG Saputro, A Ramelan… - Materials Today …, 2023 - Elsevier
This study proposes a novel approach that combines machine learning (ML) and density
functional theory (DFT) methods to construct a quantitative structure-properties relationship …

[HTML][HTML] Machine learning investigation to predict corrosion inhibition capacity of new amino acid compounds as corrosion inhibitors

M Akrom, S Rustad, HK Dipojono - Results in Chemistry, 2023 - Elsevier
This scientific paper aims to investigate the best machine learning (ML) for predicting the
corrosion inhibition efficiency (CIE) value of amino acid compounds. The study applied a …

[HTML][HTML] A comprehensive approach utilizing quantum machine learning in the study of corrosion inhibition on quinoxaline compounds

M Akrom, S Rustad, HK Dipojono… - Artificial Intelligence …, 2024 - Elsevier
In this investigation, a quantitative structure-property relationship (QSPR) model coupled
with a quantum neural network (QNN) was used to explore the corrosion inhibition efficiency …

[HTML][HTML] A feature restoration for machine learning on anti-corrosion materials

S Rustad, M Akrom, T Sutojo, HK Dipojono - Case Studies in Chemical and …, 2024 - Elsevier
Materials informatics often struggles with small datasets. Our study introduces the Gaussian
Mixture Model Virtual Sample Generation (GMM-VSG) approach to enhance feature …

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

M Akrom, S Rustad, HK Dipojono - Materials Today Communications, 2024 - Elsevier
This investigation employs a quantum neural network (QNN) synergistically integrated with a
quantitative structure-property relationship (QSPR) model for the comprehensive evaluation …

A machine learning approach to predict the efficiency of corrosion inhibition by natural product-based organic inhibitors

M Akrom, S Rustad, HK Dipojono - Physica Scripta, 2024 - iopscience.iop.org
This paper presents a quantitative structure–property relationship (QSPR)-based machine
learning (ML) framework designed for predicting corrosion inhibition efficiency (CIE) values …

Study on the corrosion inhibitory performance of Pomacea canaliculata extract as a corrosion inhibitor for carbon steel in acidic environments

Q Wang, Q Zhang, C Zhao, R Wang, X Zhou… - Journal of Molecular …, 2024 - Elsevier
Pomacea canaliculata meat extract (PCE) was explored as a multifunctional green corrosion
inhibitor on carbon steel (CS) in 1 M HCl and 0.5 MH 2 SO 4. The results showed that PCE …