Author:
Rustad Supriadi,Akrom Muhamad,Sutojo Totok,Dipojono Hermawan Kresno
Reference57 articles.
1. Deep materials informatics: Applications of deep learning in materials science;A Agrawal;MRS Communications,2019
2. Machine learning investigation to predict corrosion inhibition capacity of new amino acid compounds as corrosion inhibitors;M Akrom;Results Chem,2023
3. Development of QSAR-based (MLR/ANN) predictive models for effective design of pyridazine corrosion inhibitors;T W Quadri;Mater Today Commun,2022
4. Predicting protection capacities of pyrimidine-based corrosion inhibitors for mild steel/HCl interface using linear and nonlinear QSPR models;T W Quadri;J Mol Model,2022
5. Multilayer perceptron neural network-based QSAR models for the assessment and prediction of corrosion inhibition performances of ionic liquids;T W Quadri;Comput Mater Sci,2022