OCPMDM 2.0: An intelligent solution for materials data mining

Machine learning methods have played a significant role in materials design. With the rapid development of the Materials Genome Initiative (MGI) and data science, material researchers are confronted with the requirements to conduct sophisticated data analytics in modeling the property of materials. To make it more convenient for material researchers to design new materials using machine learning methods, an intelligent web platform called the second version of online computation platform for material data mining (OCPMDM 2.0) has been updated from the previous computation platform in our lab. Besides the various data mining algorithms developed in OCPMDM 1.0, the new platform tries to provide an intelligent solution for materials datamining, including descriptors filling, virtual screening of candidate materials, connection with materials databases and model sharing. It is convenient for materials researchers to obtain the machine learning model and the result of applying model by only submitting materials data on OCPMDM 2.0. To demonstrate the applications of the platform, two data sets of different kinds of materials were automatically processed to obtain the best models in the platform. The models are applied to screen out candidates with better properties than those in the training dataset. Material data mining process can be implemented via the platform, which provides convenient ways for material researchers in materials design and optimization. The URL of the platform is http://materials-data-mining.com/ocpmdm/.