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Serial femtosecond X‐ray crystallography (SFX) captures the structure and dynamics of biological macromolecules at high spatial and temporal resolutions. The ultrashort pulse produced by an X‐ray free‐electron laser (XFEL) `outruns' much of the radiation damage that impairs conventional crystallography. However, the rapid onset of `electronic damage' due to ionization limits this benefit. Here, we distinguish the influence of different atomic species on the ionization of protein crystals by employing a plasma code that tracks the unbound electrons as a continuous energy distribution. The simulations show that trace quantities of heavy atoms (Z > 10) contribute a substantial proportion of global radiation damage by rapidly seeding electron ionization cascades. In a typical protein crystal, sulfur atoms and solvated salts induce a substantial fraction of light‐atom ionization. In further modeling of various targets, global ionization peaks at photon energies roughly 2 keV above inner‐shell absorption edges, where sub‐2 keV photoelectrons ejected from these shells initiate ionization cascades that are briefer than the XFEL pulse. These results indicate that relatively small quantities of heavy elements can substantially affect global radiation damage in XFEL experiments. Plasma simulations with detailed modeling of unbound electron dynamics predict that heavy elements contribute significantly to radiation damage suffered by proteins in serial femtosecond crystallography. New methods to mitigate radiation damage in this regime are highlighted.

We demonstrate an advanced scattering method for accessing the 3D reciprocal space of crystalline structures forming in a rapidly supercooled noble-gas liquid using a combination of femtosecond X-ray diffraction and X-ray cross-correlation analysis. The preservation of angular information from the scattering signal allows probing the structure factor along selected directions in reciprocal space and identifying signatures undetectable in azimuthally integrated scattering curves. Therefore, more information from serial diffraction experiments on stochastic crystallization processes can be retrieved despite the inherent variation of the crystal orientation and morphology for each single probe. We also demonstrate how different features in the correlation maps can be associated with certain forms of stacking faults, which enables studying such defects in situ and disentangling them from simultaneous changes in crystal size and temperature.

We used a soft X-ray free-electron laser and the Bragg coherent diffraction imaging method to characterize the defect structure of colloidal crystals. The single-shot X-ray pulse allowed us to reach four powder rings and measured all six reflections of the hexagonal lattice. We reproduced the static shape of the 2D crystal and mapped out the 2D strain tensors inside the crystal. The observed defect structures agreed with electron microscope images of similar colloidal samples.

SPIND (sparse-pattern indexing) is an auto-indexing algorithm for sparse snapshot diffraction patterns (`stills') that requires the positions of only five Bragg peaks in a single pattern, when provided with unit-cell parameters. The capability of SPIND is demonstrated for the orientation determination of sparse diffraction patterns using simulated data from microcrystals of a small inorganic molecule containing three iodines, 5-amino-2,4,6-triiodoisophthalic acid monohydrate (I3C) [Beck & Sheldrick (2008), Acta Cryst. E 64 , o1286], which is challenging for commonly used indexing algorithms. SPIND , integrated with CrystFEL [White et al. (2012), J. Appl. Cryst. 45 , 335–341], is then shown to improve the indexing rate and quality of merged serial femtosecond crystallography data from two membrane proteins, the human δ-opioid receptor in complex with a bi-functional peptide ligand DIPP-NH 2 and the NTQ chloride-pumping rhodopsin (CIR). The study demonstrates the suitability of SPIND for indexing sparse inorganic crystal data with smaller unit cells, and for improving the quality of serial femtosecond protein crystallography data, significantly reducing the amount of sample and beam time required by making better use of limited data sets. SPIND is written in Python and is publicly available under the GNU General Public License from https://github.com/LiuLab-CSRC/SPIND.