Machine learning uses X-ray diffraction data from polymers to predict the behavior of new materials

Polymers such as polypropylene are fundamental materials in the modern world, found in everything from computers to cars. Because of their ubiquity, it's vital that materials scientists know exactly how each newly developed polymer will perform under different preparation conditions. As described in a new study, which was published in Science and Technology of Advanced Materials, scientists can now use machine learning to determine what to expect from a new polymer.