Molecular modelling of compounds used for corrosion inhibition studies: a review

EE Ebenso, C Verma, LO Olasunkanmi… - Physical Chemistry …, 2021 - pubs.rsc.org
Molecular modelling of organic compounds using computational software has emerged as a
powerful approach for theoretical determination of the corrosion inhibition potential of …

Molecular modeling applied to corrosion inhibition: a critical review

JM Castillo-Robles, E de Freitas Martins… - npj Materials …, 2024 - nature.com
In the last few years, organic corrosion inhibitors have been used as a green alternative to
toxic inorganic compounds to prevent corrosion in materials. Nonetheless, the fundamental …

Development of QSAR-based (MLR/ANN) predictive models for effective design of pyridazine corrosion inhibitors

TW Quadri, LO Olasunkanmi, ED Akpan… - Materials Today …, 2022 - Elsevier
Twenty pyridazine derivatives with previously reported experimental data were utilized to
develop predictive models for the anticorrosion abilities of pyridazine-based compounds …

Quantitative structure activity relationship and artificial neural network as vital tools in predicting coordination capabilities of organic compounds with metal surface: A …

TW Quadri, LO Olasunkanmi, OE Fayemi… - Coordination Chemistry …, 2021 - Elsevier
It has been well-established that organic corrosion inhibitors often form protective film
through coordinate bonding with the metal. Different computational and experimental …

Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review

UMR Paturi, S Cheruku - Materials Today: Proceedings, 2021 - Elsevier
Advancement in technology has created wide opportunities for the researchers to utilize
artificial intelligence in various fields. Numerous attempts have been made in the use of …

Probing the randomness of the local current distributions of 316 L stainless steel corrosion in NaCl solution

LB Coelho, D Torres, M Bernal, GM Paldino… - Corrosion …, 2023 - Elsevier
This investigation proposes using Scanning Electrochemical Cell Microscopy (SECCM) as a
high throughput tool to collect corrosion activity from randomly probed locations on 316 L …

An optimization method for multi-objective and multi-factor designing of a ceramic slurry: Combining orthogonal experimental design with artificial neural networks

L Deng, B Feng, Y Zhang - Ceramics International, 2018 - Elsevier
Three-dimensional printing (3D printing) technology based on slurry extrusion makes it
possible to realize rapid manufacture of personalized, refined and complex ceramic …

Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models

EJ Schiessler, T Würger, SV Lamaka… - npj computational …, 2021 - nature.com
The degradation behaviour of magnesium and its alloys can be tuned by small organic
molecules. However, an automatic identification of effective organic additives within the vast …

Dynamic failure analysis of process systems using neural networks

SA Adedigba, F Khan, M Yang - Process Safety and Environmental …, 2017 - Elsevier
Complex and non-linear relationships exist among process variables in a process operation.
Owing to these complex and non-linear relationships potential accident modelling using an …

Inhibitor_Mol_VAE: a variational autoencoder approach for generating corrosion inhibitor molecules

H Gong, Z Fu, L Ma, D Zhang - npj Materials Degradation, 2024 - nature.com
Deep learning-based generative modeling demonstrates proven advantages as an effective
approach in molecular discovery. This study introduces a generative-network based method …