XRDMatch: a semi-supervised learning framework to efficiently discover room temperature lithium superionic conductors

We propose XRDMatch, a semi-supervised learning framework that integrates consistency regularization and pseudo-labeling. Using X-ray diffraction patterns as descriptors, it effectively addresses data scarcity by leveraging abundant unlabeled data.