Material Characterization

With increasingly growing advances in computational material science, large databases of information about the processing, material properties and performance attributes are made available. The aggressive growth in the computer speeds enables the designers to search tons of material schemes in the processing-properties-performance envelop and identify those that hold the most promise for target functionalities. We use statistical and machine learning algorithms to analyze the material database and gain insights into chemical, physical and mechanical trends of materials that was unseen through state-of-the-art material design methods.