In the roughly two decades since its introduction, 3D electron diffraction (3D ED) has evolved from a niche technique to a widely used, established structure determination method. It has undergone rapid development in all stages of the analysis, from data collection techniques and instrumentation to improvements in data processing and structure-refinement techniques, which now enable the application of the dynamical theory of diffraction in the calculation of model intensities.
At present, the fundamentals of 3D ED are well established, and the technique is routinely used to determine crystal structures of micro- and nanocrystals. The focus of the development is shifting towards specific applications and remaining problems. The presentation will focus on these developments.
One direction is the continuous improvement of the attainable accuracy of the resulting structure models. The refinement R-factors can reach values as low as 3% in exceptionally good cases, and values below 6% are not uncommon. At this level of accuracy, it becomes possible to go beyond simple structure determination, and charge density studies become feasible. Indeed, a few recent publications [1-3] have demonstrated that charge-density studies are feasible with 3D ED. Interestingly, charge-density analysis of structures containing heavy atoms is easier with electron diffraction than with X-ray diffraction, due to the different sensitivity of electron diffraction to charge density effects.
Another direction of development focuses on improving the refinement procedure itself. In particular, the above-mentioned high-quality refinements are possible only on perfect crystals. When the crystal contains imperfections, the quality of the dynamical refinement can quickly deteriorate. To address this problem, models have been developed to account for crystal mosaicity, and models that handle the presence of crystal defects are under development – some of these efforts will be discussed in the contribution by prof Holı at this meeting.
Other efforts are aiming at high-throughput data collection and processing. Systems like AutoLEI [4] aim to automatically collect and process many datasets, with the idea that averaging across datasets can at least partially remove dynamical diffraction effects, and that a high-quality refinement can then be obtained with a simple kinematical theory. A specific application of a high-throughput data collection is the determination of the enantiomeric excess of a chiral, but not enantiomorphically pure material. Such determination requires combining measurements from many crystals with the absolute-structure determination for each by dynamical refinement [5]. It is a challenging method, but the benefit is that it is the only available technique for determining the enantiomeric excess of a material that does not contain chiral constituents, such as some chiral MOFs or zeolites.
Finally, a significant amount of effort is invested in a technique called SerialED. In this technique, analogous to serial X-ray crystallography, a single diffraction pattern is collected from each crystal, and a complete dataset is obtained by combining diffraction patterns from many crystals. Recent work [6] has demonstrated that using precession electron diffraction – a technique many considered out of fashion in recent years – can significantly boost the power of SerialED and yield structure models of comparable quality to those obtained from single crystals.
All these efforts aim to make 3D ED an even more versatile, broadly applicable, and accurate technique than it already is.
1. A. Suresh, E. Yörük, M. K. Cabaj, P. Brázda, K. Vıbornı, O. Sedláèek, C. Müller, H. Chintakindi, V. Eigner, L. Palatinus, Nat. Commun., 15, (2024), 9066
2. E. Yörük, P. Brázda, L. Palatinus, J. Molec. Struct., 1343, (2025), 142798.
3. A. Kumar, A. Suresh, A. Lanza, J. Wojciechowski, D. Trzybiñski, A. Makal, A. J. Edwards, P. Brazda, L. Palatinus, Paulina M. Dominiak, Experimental charge density of organic microcrystals revealed by 3D electron diffraction, (2026), under review
4. L. Wang, Y. Chen, E. S. Hutchinson, P. Stenmark, G. Hofer, H. Xu, X. Zou, IUCrJ, 13, (2026),105-115.
6. S. Plana-Ruiz, P. Lu, G. Ummethala, R. E. Dunin-Borkowski, J. Appl. Cryst., 58, (2025), 1249-1260.