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Long-wavelength pulses from the Swiss X-ray free-electron laser (XFEL) have been used for de novo protein structure determination by native single-wavelength anomalous diffraction (native-SAD) phasing of serial femtosecond crystallography (SFX) data. In this work, sensitive anomalous data-quality indicators and model proteins were used to quantify improvements in native-SAD at XFELs such as utilization of longer wavelengths, careful experimental geometry optimization, and better post-refinement and partiality correction. Compared with studies using shorter wavelengths at other XFELs and older software versions, up to one order of magnitude reduction in the required number of indexed images for native-SAD was achieved, hence lowering sample consumption and beam-time requirements significantly. Improved data quality and higher anomalous signal facilitate so-far underutilized de novo structure determination of challenging proteins at XFELs. Improvements presented in this work can be used in other types of SFX experiments that require accurate measurements of weak signals, for example time-resolved studies.

In this paper, we present a data workflow developed to operate the adJUstiNg Gain detector FoR the Aramis User station (JUNGFRAU) adaptive gain charge integrating pixel-array detectors at macromolecular crystallography beamlines. We summarize current achievements for operating at 9 GB/s data-rate a JUNGFRAU with 4 Mpixel at 1.1 kHz frame-rate and preparations to operate at 46 GB/s data-rate a JUNGFRAU with 10 Mpixel at 2.2 kHz in the future. In this context, we highlight the challenges for computer architecture and how these challenges can be addressed with innovative hardware including IBM POWER9 servers and field-programmable gate arrays. We discuss also data science challenges, showing the effect of rounding and lossy compression schemes on the MX JUNGFRAU detector images.

The crystal structure of a chemical compound serves several purposes: its coordinates represent three-dimensional information about the connectivity between the atoms; it is the only technique that determines the absolute configuration of chiral molecules; it enables determining structure–function relations; and crystallographic data at atomic resolution distinguish between element types and serve as a confirmation of synthesis protocols. Here, we collected electron diffraction data from albite and from a Linde Type A (LTA) type zeolite. Both compounds are aluminosilicates with well-defined silicon and aluminum crystallographic sites. Data were recorded with the “adJUstiNg Gain detector FoR the Aramis User station” (JUNGFRAU detector) and we made use of its capability of energy discrimination to suppress noise. For both compounds, crystallographic refinement distinguishes correctly between silicon and aluminum, even though these elements have very similar electron scattering factors. These results highlight the quality of the electron diffraction data and the reliability of the models for chemical interpretation. Further development in this direction will provide enormous opportunities for structure–function studies by diffraction.