Nanocrystalline materials are the basis of many novel engineered systems, including batteries, nanocomposites, and glass ceramics. Three-dimensional electron diffraction (3D ED) has become a key technique for structural analysis of such materials, offering clear advantages over conventional X-ray diffraction. Commercial routine 3D ED acquisition allowing for measurements of crystals down to ∼750 nm is now standard, but pushing the measurable size towards a few tens of nanometers introduces new challenges, requiring robust crystal-tracking methods. At this scale, TEM automation, reliable object detection, and high mechanical precision of the goniometer are essential. PyFast-ADT is introduced as a modular automation framework for 3D ED data collection, extending the measurable size range through improved crystal tracking routines. Its Python architecture enhances shareability and promotes facility automation within the 3D ED and Cryo-EM communities. The PatchworkCC algorithm combines Cross-Correlation with Kalman Filtering to achieve fully automatic crystal tracking with improved accuracy and minimal user supervision. Characterization of goniometer reproducibility revealed a rapid decrease behaviour degrading precision, addressed by the HiPerGonio procedure, which stabilizes performance and supports optimal TEM/sample holder choices. Together, these developments enable fully automated 3D ED data collection on 25 nm nanocrystals embedded in a glass-ceramic matrix, increasing throughput up to sixfold and advancing reproducible, high-throughput structure determination at the nanometer scale.

There is a growing interest in identifying the origin of single-photon emission in hexagonal boron nitride (hBN), with proposed candidates including boron and nitrogen vacancies as well as carbon substitutional dopants. Because photon emission intensity often increases with sample thickness, hBN flakes used in these studies commonly exceed 30 atomic layers. To identify potential emitters at the atomic scale, annular dark-field scanning transmission electron microscopy (ADF-STEM) is frequently employed. However, due to the intrinsic AA' stacking of hBN with vertically alternating boron and nitrogen atoms, this approach is complicated even in few-layer systems. Here, we demonstrate using STEM image simulations and experiments that, even under idealized conditions, the intensity differences between boron- and nitrogen-dominated columns and carbon substitutions become indistinguishable at thicknesses beyond 17 atomic layers (ca. 6 nm). While vacancy-type defects can remain detectable at somewhat larger thicknesses, also their detection becomes unreliable at thicknesses typically used in photonic studies. We further show that common residual aberrations, particularly threefold astigmatism, can lead to artificial contrast differences between columns, which may result in misidentification of atomic defects. We systematically study the effects of non-radially symmetric aberrations on multilayer hBN and demonstrate that even small residual threefold astigmatism can significantly distort the STEM contrast, leading to misleading interpretations.

This paper explores the topologies of caustics observed in instruments that employ charged particles, such as electron and ion microscopes. These geometrical figures are studied here using catastrophe theory. The application of this geometrical theory to our optical situation has enabled us to analytically reproduce the behaviours of various caustics. The interest lies mainly in the universal nature of these results since our treatment requires no prior knowledge of the optical configuration, but only a smart definition of the control space. This universal approach has finally made it possible to extract mathematical relationships between the aberration coefficients of any optical system, which were hidden by the complexity of optical trajectories but revealed by the set of catastrophes in the control space. These results provide a glimpse for future applications of caustics in the development of new corrected optical systems, especially for ions-based devices.

Reliable sample temperature measurements are essential in environmental transmission electron microscope (ETEM) experiments. In this study, the effect of flowing gases on the temperature distribution at a MEMS microheater in gas phase is investigated. A computational fluid dynamics model is developed and compared with experimental data. The modeling results agree well with experimental measurements based on the melting temperature of Zn nanoparticles, confirming the model's reliability. The results show that the temperature profile across the heating chip in the case with H2 environment is less uniform compared to the case of vacuum and O2. For example, at a set temperature of 900 °C in 3 mbar H2, a temperature difference of 60 °C is observed between the central sample position compared to the surrounding arc-shaped heater which also is the temperature sensor, while the difference in the vacuum case is only 13 °C. Temperature is one of the key parameters in in-situ TEM experiments and, therefore, these findings are important in the design of ETEM experiments, especially when using MEMS microheaters with relatively large distances between TEM sample and microheater/sensor.