IISc said that the lack of data on material properties-which is needed to train models - is a hindrance.Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties with limited data. The research shows that this approach can aid in the discovery of semiconductors.
It can also predict how quickly ions can move within electrodes in a battery, helping to build better energy storage devices. The research team, led by Sai Gautam Gopalakrishnan, Assistant Professor at the Department of Materials Engineering, developed a model based on Graph Neural Networks for the study.
IISc said that the lack of data on material properties-which is needed to train models - is a hindrance. This is due to expensive and time-consuming methods currently in use.
