Prediction of inhibition performance of agro-waste extract in simulated acidizing media via machine learning-Reference-Cited by-同舟云学术

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Prediction of inhibition performance of agro-waste extract in simulated acidizing media via machine learning

Published:2024-01 Issue: Volume:356 Page:129527
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Sanni Omotayo,Adeleke Oluwatobi,Ukoba Kingsley,Ren Jianwei,Jen Tien-Chen

Funder

University of Johannesburg

National Research Foundation

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference35 articles.

1. Effect of pitting corrosion on the mechanical properties of 316 grade stainless steel;Lakkam;Mater Today: Proc,2020

2. Electrochemical, thermodynamic and molecular dynamics studies of some benzoic acid derivatives on the corrosion inhibition of 316 stainless steel in HCl solutions;Alahiane;J Mol Liq,2021

3. Challenges and advantages of using plant extract as inhibitors in modern corrosion inhibition systems: Recent advancements;Alrefaee;J Mol Liq,2021

4. Inhibition of mild steel corrosion in 1 M H2SO4 by a gemini surfactant 1, 6-hexyldiyl-bis-(dimethyldodecylammonium bromide): ANN, RSM predictive modeling, quantum chemical and MD simulation studies;Haladu;J Mol Liq,2022

5. Role of organic and eco-friendly inhibitors on the corrosion mitigation of steel in acidic environments—A state-of-art review;Yang;Molecules,2021

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