A novel cerium organic network modified graphene oxide prepared multifunctional waterborne epoxy-based coating with excellent mechanical and passive/active anti-corrosion properties

Chemical Engineering Journal, Год журнала: 2023, Номер 465, С. 142997 - 142997

Опубликована: Апрель 17, 2023

Язык: Английский

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Machine learning accelerates the investigation of targeted MOFs: Performance prediction, rational design and intelligent synthesis

Nano Today, Год журнала: 2023, Номер 49, С. 101802 - 101802

Опубликована: Март 10, 2023

Язык: Английский

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Combined electrochemical, DFT/MD-simulation and hybrid machine learning based on ANN-ANFIS models for prediction of doxorubicin drug as corrosion inhibitor for mild steel in 0.5 M H2SO4 solution

Computational and Theoretical Chemistry, Год журнала: 2023, Номер 1229, С. 114334 - 114334

Опубликована: Сен. 17, 2023

Язык: Английский

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In-depth experimental assessment of two new aminocoumarin derivatives as corrosion inhibitors for carbon steel in HCl media combined with AFM, SEM/EDX, contact angle, and DFT/MDs simulations

Journal of Molecular Structure, Год журнала: 2024, Номер 1304, С. 137638 - 137638

Опубликована: Янв. 30, 2024

Язык: Английский

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Prediction of Anti-Corrosion performance of new triazole derivatives via Machine learning

Computational and Theoretical Chemistry, Год журнала: 2024, Номер 1236, С. 114599 - 114599

Опубликована: Апрель 8, 2024

Язык: Английский

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Corrosion Inhibitor of API Pipeline Steels: A Review

Journal of Bio- and Tribo-Corrosion, Год журнала: 2025, Номер 11(2)

Опубликована: Фев. 25, 2025

Язык: Английский

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

Results in Chemistry, Год журнала: 2023, Номер 6, С. 101126 - 101126

Опубликована: Сен. 18, 2023

This scientific paper aims to investigate the best machine learning (ML) for predicting corrosion inhibition efficiency (CIE) value of amino acid compounds. The study applied a quantitative structure–property relationship (QSPR) model based on an ML approach predict CIE values three new compounds, namely L-asparagine (LA), L-isoleucine (LI), and L-proline (LP). result is that Gradient Boosting Regressor (GBR) proven be predictive coefficient determination (R2) root mean square error (RMSE) metrics used. found compounds LA, LI, LP tested had high values, ranging from 90.49% 93.67%. These results are also relevant resulting experimental studies show trend by adsorption energy trend. engineering breakthrough can used properties before synthesis.

Язык: Английский

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Facile synthesis of FeNi alloy-supported N-doped Mo2C hollow nanospheres for the oxygen evolution reaction

Journal of Colloid and Interface Science, Год журнала: 2023, Номер 658, С. 267 - 275

Опубликована: Дек. 14, 2023

Язык: Английский

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Synergistic experimental and computational approaches for evaluating pyrazole Schiff bases as corrosion inhibitor for mild steel in acidic medium

Journal of Molecular Structure, Год журнала: 2023, Номер 1297, С. 136845 - 136845

Опубликована: Окт. 14, 2023

Язык: Английский

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Efficient inhibition of mild steel corrosion in acidic medium by novel pyrimidine derivatives: Inhibitive effect evaluation and interface adsorption mechanism

Journal of Molecular Structure, Год журнала: 2023, Номер 1291, С. 136005 - 136005

Опубликована: Июнь 13, 2023

Язык: Английский

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