Speaker
Description
TEM-based Electron Diffraction (ED) has progressed from sample orientation or phase analysis to a reliable method for ab initio crystal structure determination at the nanoscale. Owing to the high interaction strength, the practical limits of ED applicability continue to be explored, but its limitations are apparent: only a finite dose budget can be spent on collecting diffraction patterns from a crystal before affecting its structure.
The last few years have seen the development of many approaches that can be used to mitigate radiation damage. Simply merging short 3D experiments alleviates the issue, but for highly sensitive samples, limiting exposure to the absolute minimum is crucial. Here, Serial ED provides a solution. It does bring its own drawback of diffraction-pattern sparsity and partiality, but these can in turn be addressed using beam precession.
Serial Precession Electron Diffraction (Serial PED) is a simple method that can be used to strongly mitigate beam-damage contributions while offering enough data for structure solution. As demonstrated in 2025 by Plana-Ruiz et al. (J. Appl. Crystallogr., 58, 1249), supplementing serial ED with rocking illumination largely averages out orientation-dependent dynamical effects while increasing reciprocal space coverage. This not only facilitates indexing but ultimately lowers the required number of patterns and thus both the length and complexity of the diffraction experiment.
During my contribution, I will demonstrate the first fully automated acquisition algorithm for Serial PED. Rather than relying on image recognition or human input, the approach skips the imaging altogether and systematically scans the entire accessible area for diffraction. Optimized for handling up to kHz frame rates, the implementation determines grid geometry and then performs long sweeps across it, evaluating incoming frames live using a multiprocessing dispatcher.
The presented algorithm is implemented entirely in the open-source Python package Instamatic. Experiment progress can be saved, reloaded, monitored, and adjusted via an intuitive graphical interface while enabling easy customization of the back-end. Notably, the implementation utilizes only simple stage motions and thus can work for any TEM that provides beam precession, a fast camera, and programmable sliding stage control.