Figure Schematic of a ML-driven adaptive scanning workflow for the purpose of optimizing the scanning in a 4D-STEM experiment in real-time. The employed ML methods consist of a convolutional neural network for the atomic structure extraction and a recurrent neural network for the sequential prediction of scan positions. Training of the networks is performed through RL. Reproduced with permission from Springer Nature .