Ultrasound cavitation and exfoliation dynamics of 2D materials re-vealed in operando by X-ray free electron laser megahertz imaging

Ultrasonic liquid phase exfoliation is a promising method for the production of two-dimensional (2D) layered materials. A large number of studies have been made in investigating the underlying ultrasound exfoliation mechanisms. However, due to the experimental challenges for capturing the highly transient and dynamic phenomena in real-time at sub-microsecond time and micrometer length scales simultaneously, most theories reported to date still remain elusive. Here, using the ultra-short X-ray Free Electron Laser pulses (~25ps) with a unique pulse train structure, we applied MHz X-ray Microscopy and machine-learning technique to reveal unambiguously the full cycles of the ultrasound cavitation and graphite layer exfoliation dynamics with sub-microsecond and micrometer resolution. Cyclic fatigue shock wave impacts produced by ultrasound cloud implosion were identified as the dominant mechanism to deflect and exfoliate graphite layers mechanically. For the graphite flakes, exfoliation rate as high as ~5 angstroms per shock wave impact was observed. For the HOPG graphite, the highest exfoliation rate was ~0.15 angstroms per impact. These new findings are scientifically and technologically important for developing industrial upscaling strategies for ultrasonic exfoliation of 2D materials

First operation of the JUNGFRAU detector in 16-memory cell mode at European XFEL

The JUNGFRAU detector is a well-established hybrid pixel detector developed at the Paul Scherrer Institut (PSI) designed for free-electron laser (FEL) applications. JUNGFRAU features a charge-integrating dynamic gain switching architecture, with three different gain stages and 75 μm pixel pitch. It is widely used at the European X-ray Free-Electron Laser (EuXFEL), a facility which produces high brilliance X-ray pulses at MHz repetition rate in the form of bursts repeating at 10 Hz. In nominal configuration, the detector utilizes only a single memory cell and supports data acquisition up to 2 kHz. This constrains the operation of the detector to a 10 Hz frame rate when combined with the pulsed train structure of the EuXFEL. When configured in so-called burst mode, the JUNGFRAU detector can acquire a series of images into sixteen memory cells at a maximum rate of around 150 kHz. This acquisition scheme is better suited for the time structure of the X-rays as well as the pump laser pulses at the EuXFEL. To ensure confidence in the use of the burst mode at EuXFEL, a wide range of measurements have been performed to characterize the detector, especially to validate the detector alibration procedures. In particular, by analyzing the detector response to varying photon intensity (so called ‘intensity scan’), special attention was given to the characterization of the transitions between gain stages. The detector was operated in both dynamic gain switching and fixed gain modes. Results of these measurements indicate difficulties in the characterization of the detector dynamic gain switching response while operated in burst mode, while no major issues have been found with fixed gain operation. Based on this outcome, fixed gain operation mode with all the memory cells was used during two experiments at EuXFEL, namely in serial femtosecond protein crystallography and Kossel lines measurements. The positive outcome of these two experiments validates the good results previously obtained, and opens the possibility for a wider usage of the detector in burst operation mode, although compromises are needed on the dynamic range

Two Piwis with Ago-like functions silence somatic genes at the chromatin level

Most sRNA biogenesis mechanisms involve either RNAseIII cleavage or ping-pong amplification by different Piwi proteins harboring slicer activity. Here, we follow the question why the mechanism of transgene-induced silencing in the ciliate Paramecium needs both Dicer activity and two Ptiwi proteins. This pathway involves primary siRNAs produced from non-translatable transgenes and secondary siRNAs from endogenous remote loci. Our data does not indicate any signatures from ping-pong amplification but Dicer cleavage of long dsRNA. We show that Ptiwi13 and 14 have different preferences for primary and secondary siRNAs but do not load them mutually exclusive. Both Piwis enrich for antisense RNAs and Ptiwi14 loaded siRNAs show a 5′-U signature. Both Ptiwis show in addition a general preference for Uridine-rich sRNAs along the entire sRNA length. Our data indicates both Ptiwis and 2’-O-methylation to contribute to strand selection of Dicer cleaved siRNAs. This unexpected function of two distinct vegetative Piwis extends the increasing knowledge of the diversity of Piwi functions in diverse silencing pathways. As both Ptiwis show differential subcellular localisation, Ptiwi13 in the cytoplasm and Ptiwi14 in the vegetative macronucleus, we conclude that cytosolic and nuclear silencing factors are necessary for efficient chromatin silencing

Automatic bad‐pixel mask maker for X‐ray pixel detectors with application to serial crystallography

X‐ray crystallography has witnessed a massive development over the past decade, driven by large increases in the intensity and brightness of X‐ray sources and enabled by employing high‐frame‐rate X‐ray detectors. The analysis of large data sets is done via automatic algorithms that are vulnerable to imperfections in the detector and noise inherent with the detection process. By improving the model of the behaviour of the detector, data can be analysed more reliably and data storage costs can be significantly reduced. One major requirement is a software mask that identifies defective pixels in diffraction frames. This paper introduces a methodology and program based upon concepts of machine learning, called robust mask maker (RMM), for the generation of bad‐pixel masks for large‐area X‐ray pixel detectors based on modern robust statistics. It is proposed to discriminate normally behaving pixels from abnormal pixels by analysing routine measurements made with and without X‐ray illumination. Analysis software typically uses a Bragg peak finder to detect Bragg peaks and an indexing method to detect crystal lattices among those peaks. Without proper masking of the bad pixels, peak finding methods often confuse the abnormal values of bad pixels in a pattern with true Bragg peaks and flag such patterns as useful regardless, leading to storage of enormous uninformative data sets. Also, it is computationally very expensive for indexing methods to search for crystal lattices among false peaks and the solution may be biased. This paper shows how RMM vastly improves peak finders and prevents them from labelling bad pixels as Bragg peaks, by demonstrating its effectiveness on several serial crystallography data sets.Attention is focused on perhaps the biggest bottleneck in data analysis for serial crystallography at X‐ray free‐electron lasers, which has not received serious enough examination to date. An effective and reliable way is presented to identify anomalies in detectors, using machine learning and recently developed mathematical methods in the field referred to as `robust statistics'. imag

Shot-to-shot two-dimensional photon intensity diagnostics within megahertz pulse-trains at the European XFEL

Characterizing the properties of X-ray free-electron laser (XFEL) sources is a critical step for optimization of performance and experiment planning. The recent availability of MHz XFELs has opened up a range of new opportunities for novel experiments but also highlighted the need for systematic measurements of the source properties. Here, MHz-enabled beam imaging diagnostics developed for the SPB/SFX instrument at the European XFEL are exploited to measure the shot-to-shot intensity statistics of X-ray pulses. The ability to record pulse-integrated two-dimensional transverse intensity measurements at multiple planes along an XFEL beamline at MHz rates yields an improved understanding of the shot-to-shot photon beam intensity variations. These variations can play a critical role, for example, in determining the outcome of single-particle imaging experiments and other experiments that are sensitive to the transverse profile of the incident beam. It is observed that shot-to-shot variations in the statistical properties of a recorded ensemble of radiant intensity distributions are sensitive to changes in electron beam current density. These changes typically occur during pulse-distribution to the instrument and are currently not accounted for by the existing suite of imaging diagnostics. Modulations of the electron beam orbit in the accelerator are observed to induce a time-dependence in the statistics of individual pulses – this is demonstrated by applying radio-frequency trajectory tilts to electron bunch-trains delivered to the instrument. We discuss how these modifications of the beam trajectory might be used to modify the statistical properties of the source and potential future applications

Automatic bad pixel mask maker for X-ray pixel detectors with application to serial crystallography

X-ray crystallography has witnessed a massive development over the past decade, driven by large increases in the intensity and brightness of X-ray sources and enabled by employing high-frame-rate X-ray detectors. The analysis of large data sets is done via automatic algorithms that are vulnerable to imperfections in the detector and noise inherent with the detection process. By improving the model of the behaviour of the detector, data can be analysed more reliably and data storage costs can be significantly reduced. One major requirement is a software mask that identifies defective pixels in diffraction frames. This paper introduces a methodology and program based upon concepts of machine learning, called robust mask maker (RMM), for the generation of bad-pixel masks for large-area X-ray pixel detectors based on modern robust statistics. It is proposed to discriminate normally behaving pixels from abnormal pixels by analysing routine measurements made with and without X-ray illumination. Analysis software typically uses a Bragg peak finder to detect Bragg peaks and an indexing method to detect crystal lattices among those peaks. Without proper masking of the bad pixels, peak finding methods often confuse the abnormal values of bad pixels in a pattern with true Bragg peaks and flag such patterns as useful regardless, leading to storage of enormous uninformative data sets. Also, it is computationally very expensive for indexing methods to search for crystal lattices among false peaks and the solution may be biased. This paper shows how RMM vastly improves peak finders and prevents them from labelling bad pixels as Bragg peaks, by demonstrating its effectiveness on several serial crystallography data sets

Data reduction for serial crystallography using a robust peak finder

A peak-finding algorithm for serial crystallography (SX) data analysis based on the principle of `robust statistics' has been developed. Methods which are statistically robust are generally more insensitive to any departures from model assumptions and are particularly effective when analysing mixtures of probability distributions. For example, these methods enable the discretization of data into a group comprising inliers (i.e. the background noise) and another group comprising outliers (i.e. Bragg peaks). Our robust statistics algorithm has two key advantages, which are demonstrated through testing using multiple SX data sets. First, it is relatively insensitive to the exact value of the input parameters and hence requires minimal optimization. This is critical for the algorithm to be able to run unsupervised, allowing for automated selection or `vetoing' of SX diffraction data. Secondly, the processing of individual diffraction patterns can be easily parallelized. This means that it can analyse data from multiple detector modules simultaneously, making it ideally suited to real-time data processing. These characteristics mean that the robust peak finder (RPF) algorithm will be particularly beneficial for the new class of MHz X-ray free-electron laser sources, which generate large amounts of data in a short period of time

3D printed devices and infrastructure for liquid sample delivery at the European XFEL

The Sample Environment and Characterization (SEC) group of the European X-ray Free-Electron Laser (EuXFEL) develops sample delivery systems for the various scientific instruments, including systems for the injection of liquid samples that enable serial femtosecond X-ray crystallography (SFX) and single-particle imaging (SPI) experiments, among others. For rapid prototyping of various device types and materials, sub-micrometre precision 3D printers are used to address the specific experimental conditions of SFX and SPI by providing a large number of devices with reliable performance. This work presents the current pool of 3D printed liquid sample delivery devices, based on the two-photon polymerization (2PP) technique. These devices encompass gas dynamic virtual nozzles (GDVNs), mixing-GDVNs, high-viscosity extruders (HVEs) and electrospray conical capillary tips (CCTs) with highly reproducible geometric features that are suitable for time-resolved SFX and SPI experiments at XFEL facilities. Liquid sample injection setups and infrastructure on the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument are described, this being the instrument which is designated for biological structure determination at the EuXFEL

Pump–probe capabilities at the SPB/SFX instrument of the European XFEL

Pump–probe experiments at X-ray free-electron laser (XFEL) facilities are a powerful tool for studying dynamics at ultrafast and longer timescales. Observing the dynamics in diverse scientific cases requires optical laser systems with a wide range of wavelength, flexible pulse sequences and different pulse durations, especially in the pump source. Here, the pump–probe instrumentation available for measurements at the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument of the European XFEL is reported. The temporal and spatial stability of this instrumentation is also presented.Keywords: pump–probe experiments; European XFEL; megahertz pump and probe sources; time-resolved experiments

Form factor determination of biological molecules with X-ray free electron laser small-angle scattering (XFEL-SAS)

Free-electron lasers (FEL) are revolutionizing X-ray-based structural biology methods. While protein crystallography is already routinely performed at FELs, Small Angle X-ray Scattering (SAXS) studies of biological macromolecules are not as prevalent. SAXS allows the study of the shape and overall structure of proteins and nucleic acids in solution, in a quasi-native environment. In solution, chemical and biophysical parameters that have an influence on the structure and dynamics of molecules can be varied and their effect on conformational changes can be monitored in time-resolved XFEL and SAXS experiments. We report here the collection of scattering form factors of proteins in solution using FEL X-rays. The form factors correspond to the scattering signal of the protein ensemble alone; the scattering contributions from the solvent and the instrument are separately measured and accurately subtracted. The experiment was done using a liquid jet for sample delivery. These results pave the way for time-resolved studies and measurements from dilute samples, capitalizing on the intense and short FEL X-ray pulses