Artificial intelligence-based model for physical-mechanical surface properties of nanostructured coatings

• DOI: 10.1016/j.rinma.2023.100494
• Publication Date: 2023-11-29T04:19:59Z
• Authors: F.J. Sánchez-Ruiz; M. Bedolla-Hernández; G. Rosano-Ortega; J. Bedolla-Hernández; P.S. Schabes-Retc...; C.A. Vega-Lebrún; E. Vargas-Viveros
• Keywords: Artificial intelligence; Physical-mechanical surface properties; TA401-492; Quantum chemistry; Materials of engineering and construction. Mechanics of materials; 01 natural sciences; Nanostructured metallic coating; 0104 chemical sciences

This article presents a computational numerical model for the simulation and analysis of quantum chemistry Gibbs free energy theory using static (ANNS), dynamic (DANN), chaotic neural networks (CANN). The calculates physical-surface mechanics hardness, adhesion, strength. They resulted in nanostructured metal coatings with electrodeposited chromium nanoparticles on low-carbon steel. ANNS, DANN, CANN simulations showed that model-obtained values analyzed properties presented an approximation 99 % concerning theoretical matters taken as base. Likewise, accuracy was verified by comparison reference data (datasheet). proposed is not limited to case provides consistent results predicting surface physical-mechanical coating-substrate arrangements, minimum error percentage 1–1.5 over learning.