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

Abstract

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.

Potential of Time-Resolved Serial Femtosecond Crystallography Using High Repetition Rate XFEL Sources

“…They were first made of glass capillaries and had a manual method, meaning that each nozzle was different, their preparation time consuming and they required specific expertise. Recently, the increasing availability of 3D printing methods and 2-photon polymerization techniques has improved the production of GDVNs with high quality and high reproducibility [16,42,43]. However, even with such a novel nozzle production method, the standard liquid jets still have limitations regarding: their sensitivity to clogging issues, owing to the sample viscosity or crystal preparation; their high sample consumption, as the sample needs to be continuously flowing even when no X-rays are present; and high flow rates are needed for stable jetting.…”

“…In standard liquid jet injection, 300 times more sample is injected than is actually probed by the X-rays. DFFNs, with the use of a focusing liquid, address these limitations, as they allow the use of higher viscosity samples and reduce the minimal sample flow rate for stable injection by a factor of 4 [16,42]. Notwithstanding these improvements, they still do not solve the problem of wasted samples (amounting to more than 99%) and generate additional background due to the sheathing liquid.…”

“…Notwithstanding these improvements, they still do not solve the problem of wasted samples (amounting to more than 99%) and generate additional background due to the sheathing liquid. Very recently, Vakilii et al presented extensive details about all current sample delivery methods available at the EuXFEL, including those used at the SPB/SFX instrument [16]. In the next section, we highlight the current developments that are underway to cope with such limitations.…”

“…However, megahertz repetition rate and sample injection in vacuum come with limitations that need to be overcome, such as the sample needing to be replaced at the same rate and without freezing. Due to these constraints, the most commonly used sample delivery method is within a low viscosity liquid jet [16,17]. Currently, it is the only method available to replenish the sample fast enough to bring a fresh crystal to the interaction point before the subsequent X-ray pulse is delivered while still remaining flexible enough to allow time-resolved studies in the form of mix-and-inject and pump-probe experiments [18][19][20].…”

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

“…The pulses from either type of nanosecond laser can be delivered to both IRU and IRD. These nanosecond lasers, like the PP laser, may also be used as a light source for stroboscopic imaging of samples (Kay & Wheeless Jr, 1976;Schropp et al, 2015;Reich et al, 2018;Vakili et al, 2022), as shown in Fig. 9.…”