Modelling mechanisms for measurable and detection based on artificial intelligence

Abstract

One of the trendiest areas in the field of materials science is Artificial Intelligence (AI) based physical applications. Typically, more time and resources are needed for traditional experiments and statistical methods. Thus, there is a growing need for applications of AI in the simulation and investigation of novel materials. Usually, there are significant restrictions because there are not any benchmark datasets, sophisticated pre-processing mechanisms, prediction modelling mechanisms, or simulation tools in the literature on materials. This work aims to attempt for examining computational and experimental data-based AI processes. In addition, the state of research into developing new materials and utilizing AI in material modelling tools is implemented. As long as, AI can be used in materials to improve efficiency and prediction accuracy. Also, it is very difficult to determine great learning models, involving data preparation, model architecture, data management, and simulation techniques. Finally, it has been discussed the challenges in realizing AI-based applications in the field of materials science.