Certain Investigations on Machine Learning Models for Material Processing

Machine learning has become a popular area to process all varieties of data, including material sciences. Machine learning approaches are now able to assist in the handling of vast numbers of images in material science projects. In recent days, this is being used in different fields of research like catalysis, super-conductivity, thermoelectric, and photovoltaics. Recent advances reflect major breakthroughs in material knowledge and innovation, demonstrating how machine learning may have a transformational effect at the atomic level by enabling exact property prediction and complex data extraction. In this chapter, various researches and their advancement in the field of material sciences are discussed. In addition, the challenges and opportunities available in the area of machine learning with material engineering are outlined.