Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on ...

Integrating machine learning techniques, including Bayesian optimization (BO) and artificial neural networks, into materials science has ushered in a new era of research 1,2,3. This paradigm shift ...