ABSTRACT
Materials science includes the design and discovery of new materials for manufacturing products with desired properties and functionality. The time frame for discovering new materials from initial research to first use is remarkably long. Materials design by using computer simulation and analysis leads to reduction in time and cost of materials development. One of the most exciting computational tools that has entered the materials science toolbox in recent years is machine learning, which is being applied to address various problems, such as new materials discovery, material property prediction, corrosion behavior prediction, etc. In this chapter, a review of applications of machine learning in materials science reported in the literature in recent years is presented.
