The High Throughput Machine Learning Materials Design Platform
Materials discovery and simulation can be an expensive, slow process. Our machine learning models aim to cut the simulation time of important semiconductor properties dramatically by providing machine learning models that can make accurate predictions quickly and cheaply.
Our band gap prediction model has achieved an R2 value of 0.995 using a handful of materials properties.
Do you need assistance with materials property prediction? Perhaps we can help. Get in touch with us.