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Gas-dynamic virtual nozzles (GDVNs) play a vital role in delivering biomolecular samples during diffraction measurements at X-ray free-electron laser facilities. Recently, submicrometer resolution capabilities of two-photon polymerization 3D printing techniques opened the possibility to quickly fabricate gas-dynamic virtual nozzles with practically any geometry. In our previous work, we exploited this capability to print asymmetric gas-dynamic virtual nozzles that outperformed conventional symmetric designs, which naturally leads to the question of how to identify the optimal gas-dynamic virtual nozzle geometry. In this work, we develop a 3D computational fluid dynamics pipeline to investigate how the characteristics of microjets are affected by gas-dynamic virtual nozzle geometry, which will allow for further geometry optimizations and explorations. We used open-source software (OpenFOAM) and an efficient geometric volume-of-fluid method ( isoAdvector ) to affordably and accurately predict jet properties for different nozzle geometries. Computational resources were minimized by utilizing adaptive mesh refinement. The numerical simulation results showed acceptable agreement with the experimental data, with a relative error of about 10% for our test cases that compared bell- and cone-shaped sheath-gas cavities. In these test cases, we used a relatively low sheath gas flow rate (6 mg/min), but future work including the implementation of compressible flows will enable the investigation of higher flow rates and the study of asymmetric drip-to-jet transitions. 

Abstract Sample consumption for serial femtosecond crystallography (SFX) with X-ray free electron lasers (XFELs) remains a major limitation preventing broader use of this powerful technology in macromolecular crystallography. This drawback is exacerbated in the case of time-resolved (TR)-SFX experiments, where the amount of sample required per reaction time point is multiplied by the number of time points investigated. Thus, in order to reduce the limitation of sample consumption, here we demonstrate the implementation of segmented droplet generation in conjunction with a mix-and-inject approach for TR studies on NAD(P)H:quinone oxidoreductase 1 (NQO1). We present the design and application of mix-and-inject segmented droplet injectors for the Single Particles, Clusters, and Biomolecules & Serial Femtosecond Crystallography (SPB/SFX) instrument at the European XFEL (EuXFEL) with a synchronized droplet injection approach that allows liquid phase protein crystal injection. We carried out TR-crystallography experiments with this approach for a 305 ms and a 1190 ms time point in the reaction of NQO1 with its coenzyme NADH. With this successful TR-SFX approach, up to 97% of the sample has been conserved compared to continuous crystal suspension injection with a gas dynamic virtual nozzle. Furthermore, the obtained structural information for the reaction of NQO1 with NADH is an important part of the future elucidation of the reaction mechanism of this crucial therapeutic enzyme. 

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility. 

A 3D-printed modular droplet injector successfully delivered microcrystals of human NAD(P)H:quinone oxidoreductase 1 (NQO1) and phycocyanin with electrical stimulation in a serial crystallography experiment at 120 Hz repetition rate. 

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 ofSPINDis 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.E64, o1286], which is challenging for commonly used indexing algorithms.SPIND, integrated withCrystFEL[Whiteet 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-NH₂and the NTQ chloride-pumping rhodopsin (CIR). The study demonstrates the suitability ofSPINDfor 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.SPINDis written in Python and is publicly available under the GNU General Public License from https://github.com/LiuLab-CSRC/SPIND.