[HTML][HTML] Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds
This work used a variational quantum circuit (VQC) in conjunction with a quantitative
structure-property relationship (QSPR) model to completely investigate the corrosion …
structure-property relationship (QSPR) model to completely investigate the corrosion …
Implementation of quantum machine learning in predicting corrosion inhibition efficiency of expired drugs
This study explores the potential of quantum machine learning (QML)'s potential in
predicting expired pharmaceutical compounds' corrosion inhibition capacity. This …
predicting expired pharmaceutical compounds' corrosion inhibition capacity. This …
Machine learning for pyrimidine corrosion inhibitor small dataset
Abstract Machine learning (ML) approaches have been developed to predict materials'
corrosion inhibition efficiency, particularly pyrimidine compounds. Notably, the virtual …
corrosion inhibition efficiency, particularly pyrimidine compounds. Notably, the virtual …
Synergism of Computational Simulation Technique and Machine Learning Algorithm for Prediction of Anticorrosion Properties of Some Antipyrine Derivatives
This study aimed to predict the selected antipyrine compounds' inhibitory efficiencies and
anticorrosion properties in a hydrochloric acid (HCl) environment. Molecular descriptors and …
anticorrosion properties in a hydrochloric acid (HCl) environment. Molecular descriptors and …
Comparative Analysis of Linear Regression, Decision Tree, and Gradient Boosting Models for Predicting Drug Corrosion Inhibition Efficiency Using QSAR Descriptors
Corrosion in industrial environments poses significant economic and safety challenges,
necessitating the development of effective inhibitors. Organic compounds, particularly …
necessitating the development of effective inhibitors. Organic compounds, particularly …