In recent years, the field of material science has seen a significant increase in the use of predictive analytics. Predictive analytics is a branch of data analytics that uses statistical algorithms and machine learning techniques to analyze data and make predictions about future events. In material science, predictive analytics is being used to predict the properties of materials before they are even synthesized.
One of the main benefits of using predictive analytics in material science is that it can significantly reduce the time and cost associated with developing new materials. Traditionally, developing new materials involves a lot of trial and error, with researchers synthesizing and testing numerous materials before finding one that meets their requirements.