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Particle atomic layer deposition (ALD) is an emerging method for engineering 3D materials, such as powders, for energy applications. In our study, we employ a commercially available and scalable particle ALD system to synthesize Pt/C electrocatalysts for fuel cells. Our method yields Pt/C catalysts characterized by highly dispersed platinum nanoparticles with a narrow particle size distribution of 2.2 ± 0.5 nm for 30 wt% Pt and 2.6 ± 0.6 nm for 40 wt% Pt, as verified through transmission electron microscopy and X-ray diffraction analysis. The performance of the ALD-synthesized catalysts is benchmarked against a state-of-the-art catalyst (TEC10V50E), with both catalysts exhibiting similar beginning-of-test performance (1.6 A cm -2 at 0.65 V) under application-relevant operation conditions (80 °C, 50% relative humidity). After 30 000 voltage cycles, conducted in accordance with the U.S. Department of Energy's accelerated catalyst degradation test, the ALD catalysts demonstrate up to 64% greater electrochemical active surface areas and superior retention of cell performance, with a 34% higher current density at 0.65 V, compared to the reference. Given the scalability of the commercial particle ALD system, these promising results encourage the use of particle ALD as a novel synthesis approach for fuel cell catalyst materials in the industry., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Metal Fused Filament Fabrication provides a simple and cost-efficient way to produce dense metal parts with a homogenous microstructure. However, current limitations include the use of hazardous and expensive organic solvents during debinding for flexible filaments the stiffness of filaments made from partly water-soluble binder systems. In this study, the influence of various additives on different partly water-soluble binder systems, with regard to the flexibility and properties of the final parts, was investigated. Furthermore, a method using dynamic mechanical analysis to quantify the flexibility of filaments was introduced and successfully applied. For the first time, it was possible to produce flexible, partly water-soluble filaments with 60 vol.% solid content, which allowed the 3D printing of complex small and large parts with a high level of detail. After sintering, density values of up to 98.9% of theoretical density were achieved, which is significantly higher than those obtained with existing binder systems.

Digital PCR (dPCR) is a powerful method for highly sensitive and precise quantification of nucleic acids. However, designing and optimizing new multiplex dPCR assays using target sequence specific probes remains cumbersome, since fluorescent signals must be optimized for every new target panel. As a solution, we established a generic fluorogenic 6-plex reporter set, based on mediator probe technology, that decouples target detection from signal generation. This generic reporter set is compatible with different target panels and thus provides already optimized fluorescence signals from the start of new assay development. Generic reporters showed high population separability in a colorimetric 6-plex mediator probe dPCR, due to their tailored fluorophore and quencher selection. These reporters were further tested using different KRAS , NRAS and BRAF single-nucleotide polymorphisms (SNP), which are frequent point mutation targets in liquid biopsy. We specifically quantified SNP targets in our multiplex approach down to 0.4 copies per microliter (cp/µL) reaction mix, equaling 10 copies per reaction, on a wild-type background of 400 cp/µL for each, equaling 0.1% variant allele frequencies. We also demonstrated the design of an alternative generic reporter set from scratch in order to give detailed step-by-step guidance on how to systematically establish and optimize novel generic reporter sets. Those generic reporter sets can be customized for various digital PCR platforms or target panels with different degrees of multiplexing.

Integrated reference electrodes allow to deconvolute voltage contributions of anode and cathode and contribute to a better understanding of CO 2 electrolyzers. However, in zero-gap cell configurations, this integration can be challenging and obtaining error-free data with such a setup is a non-trivial task. This study compares five different methods to integrate a reference electrode into an alkaline zero-gap CO 2 electrolysis cell. Sources of error and measures to circumvent them are investigated and finite-element simulation is used to gain a better understanding of observed effects. Placing a reference electrode into the inactive area of the cell is found to be a reliable method, as long as the placement of electrodes is sufficiently controlled. Sandwiching a wire quasi-reference electrode between two membranes is especially useful for electrochemical impedance spectroscopy; however, it can affect the overall cell performance. Contacting the catalyst layer from the backside with a salt-bridge is promising for localized measurements if sufficient reproducibility can be ensured., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Machine learning techniques, particularly deep convolutional neural networks (ConvNets), are increasingly being used to automate clinical EEG analysis, with the potential to reduce the clinical burden and improve patient care. However, further research is required before they can be used in clinical settings, particularly regarding the impact of the number of training samples and model parameters on their testing error. To address this, we present a comprehensive study of the empirical scaling behaviour of ConvNets for EEG pathology classification. We analysed the testing error with increasing the training samples and model size for four different ConvNet architectures. The focus of our experiments is width scaling, and we have increased the number of parameters to up to 1.8 million. Our evaluation was based on two publicly available datasets: the Temple University Hospital (TUH) Abnormal EEG Corpus and the TUH Abnormal Expansion Balanced EEG Corpus, which together contain 10,707 training samples. The results show that the testing error follows a saturating power-law with both model and dataset size. This pattern is consistent across different datasets and ConvNet architectures. Furthermore, empirically observed accuracies saturate at 85%-87%, which may be due to an imperfect inter-rater agreement on the clinical labels. The empirical scaling behaviour of the test performance with dataset and model size has significant implications for deep EEG pathology classification research and practice. Our findings highlight the potential of deep ConvNets for high-performance EEG pathology classification, and the identified scaling relationships provide valuable recommendations for the advancement of automated EEG diagnostics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could appear to have influenced the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Vascular ageing is the deterioration of arterial structure and function which occurs naturally with age, and which can be accelerated with disease. Measurements of vascular ageing are emerging as markers of cardiovascular risk, with potential applications in disease diagnosis and prognosis, and for guiding treatments. However, vascular ageing is not yet routinely assessed in clinical practice. A key step towards this is the development of technologies to assess vascular ageing. In this Roadmap, experts discuss several aspects of this process, including: measurement technologies; the development pipeline; clinical applications; and future research directions. The Roadmap summarises the state of the art, outlines the major challenges to overcome, and identifies potential future research directions to address these challenges., (Creative Commons Attribution license.)

The technology to jet print metal lines with precise shape fidelity on diverse substrates is gaining higher interest across multiple research fields. It finds applications in additively manufactured flexible electronics, environmentally friendly and sustainable electronics, sensor devices for medical applications, and fabricating electrodes for solar cells. This paper provides an experimental investigation to deepen insights into the non-contact printing of solder lines using StarJet technology, eliminating the need for surface activation, substrate heating, curing, or post-processing. Moreover, it employs bulk metal instead of conventional inks or pastes, leading to cost-effective production and enhanced conductivity. The effect of molten metal temperature, substrate temperature, standoff distance, and printing velocity was investigated on polymer foils (i.e., PET sheets). Robust printing parameters were derived to print uniform, bulge-free, bulk metal lines suitable for additive manufacturing applications. The applicability of the derived parameters was extended to 3D-printed PLA, TPU, PA-GF, and PETG substrates having a much higher surface roughness. Additionally, a high aspect ratio of approx. 16:1 wall structure has been demonstrated by printing multiple metal lines on top of each other. While challenges persist, this study contributes to advancing additively manufactured electronic devices, highlighting the capabilities of StarJet metal jet-printing technology.

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

3D cell culture is becoming increasingly important for mimicking physiological tissue structures in areas such as drug discovery and personalized medicine. To enable reproducibility on a large scale, automation technologies for standardized handling are still a challenge. Here, a novel method for fully automated size classification and handling of cell aggregates like spheroids and organoids is presented. Using microfluidic flow generated by a piezoelectric droplet generator, aggregates are aspirated from a reservoir on one side of a thin capillary and deposited on the other side, encapsulated in free-flying nanoliter droplets to a target. The platform has aggregate aspiration and plating efficiencies of 98.1% and 98.4%, respectively, at a processing throughput of up to 21 aggregates per minute. Cytocompatibility of the method is thoroughly assessed with MCF7, LNCaP, A549 spheroids and colon organoids, revealing no adverse effects on cell aggregates as shear stress is reduced compared to manual pipetting. Further, generic size-selective handling of heterogeneous organoid samples, single-aggregate-dispensing efficiencies of up to 100% and the successful embedding of spheroids or organoids in a hydrogel with subsequent proliferation is demonstrated. This platform is a powerful tool for standardized 3D in vitro research., (© 2024 The Authors. Advanced Healthcare Materials published by Wiley‐VCH GmbH.)

Structural epilepsies display complex immune activation signatures. However, it is unclear which neuroinflammatory pathways drive pathobiology. Transcriptome studies of brain resections from mesial temporal lobe epilepsy (mTLE) patients revealed a dysregulation of transforming growth factor β, interferon α/β, and nuclear factor erythroid 2-related factor 2 pathways. Since these pathways are regulated by ubiquitin-specific proteases (USP), in particular USP15, we hypothesized that USP15 blockade may provide therapeutic relief in treatment-resistant epilepsies. For validation, transgenic mice which either constitutively or inducibly lack Usp15 gene expression underwent intrahippocampal kainate injections to induce mTLE. We show that the severity of status epilepticus is unaltered in mice constitutively lacking Usp15 compared to wild types. Cell death, reactive gliosis, and changes in the inflammatory transcriptome were pronounced at 4 days after kainate injection. However, these brain inflammation signatures did not differ between genotypes. Likewise, induced deletion of Usp15 in chronic epilepsy did not affect seizure generation, cell death, gliosis, or the transcriptome. Concordantly, siRNA-mediated knockdown of Usp15 in a microglial cell line did not impact inflammatory responses in the form of cytokine release. Our data show that a lack of USP15 is insufficient to modulate the expression of relevant neuroinflammatory pathways in an mTLE mouse model and do not support targeting USP15 as a therapeutic approach for pharmacoresistant epilepsy., (© 2023. The Author(s).)

We present a novel centrifugal microfluidic approach to rapidly identify animal species in meat products. The workflow requires a centrifugal cartridge for DNA extraction and for preparation of a recombinant polymerase amplification (RPA) reaction, a programmable centrifuge for processing the cartridge and an isothermal reader to perform the RPA. Liquid reagents are pre-stored on the cartridge and the meat sample can be added directly without any pre-treatment. With this system, we are able to identify six different animal species in a single run within one hour. In pork salami containing horse, turkey, sheep, chicken and beef meat, it was possible to identify species levels as low as 0.01%. In beef salami and cooked pork sausages 0.1% of foreign meat could be detected. This novel workflow enables rapid and sensitive species identification in processed meat at the point of need.

Creating model systems that replicate in vivo tissues is crucial for understanding complex biological pathways like drug response and disease progression. Three-dimensional (3D) in vitro models, especially multicellular spheroids (MCSs), offer valuable insights into physiological processes. However, generating MCSs at scale with consistent properties and efficiently recovering them pose challenges. We introduce a workflow that automates large-scale spheroid production and enables parallel harvesting into individual wells of a microtiter plate. Our method, based on the hanging-drop technique, utilizes a non-contact dispenser for dispensing nanoliter droplets of a uniformly mixed-cell suspension. The setup allows for extended processing times of up to 45 min without compromising spheroid quality. As a proof of concept, we achieved a 99.3% spheroid generation efficiency and maintained highly consistent spheroid sizes, with a coefficient of variance below 8% for MCF7 spheroids. Our centrifugation-based drop transfer for spheroid harvesting achieved a sample recovery of 100%. We successfully transferred HT29 spheroids from hanging drops to individual wells preloaded with collagen matrices, where they continued to proliferate. This high-throughput workflow opens new possibilities for prolonged spheroid cultivation, advanced downstream assays, and increased hands-off time in complex 3D cell culture protocols.

Background: RNA-RNA interactions are key to a wide range of cellular functions. The detection of potential interactions helps to understand the underlying processes. However, potential interactions identified via in silico or experimental high-throughput methods can lack precision because of a high false-positive rate., Results: We present CheRRI, the first tool to evaluate the biological relevance of putative RNA-RNA interaction sites. CheRRI filters candidates via a machine learning-based model trained on experimental RNA-RNA interactome data. Its unique setup combines interactome data and an established thermodynamic prediction tool to integrate experimental data with state-of-the-art computational models. Applying these data to an automated machine learning approach provides the opportunity to not only filter data for potential false positives but also tailor the underlying interaction site model to specific needs., Conclusions: CheRRI is a stand-alone postprocessing tool to filter either predicted or experimentally identified potential RNA-RNA interactions on a genomic level to enhance the quality of interaction candidates. It is easy to install (via conda, pip packages), use (via Galaxy), and integrate into existing RNA-RNA interaction pipelines., (© The Author(s) 2024. Published by Oxford University Press GigaScience.)

C-reactive protein is a well-studied host response biomarker, whose diagnostic performance depends on its accurate classification into concentration zones defined by clinical scenario-specific cutoff values. We validated a newly developed, bead-based, bound-free phase detection immunoassay (BFPD-IA) versus a commercial CE-IVD enzyme-linked immunosorbent assay (ELISA) kit and a commercial CE-IVD immunoturbidimetric assay (ITA) kit. The latter was performed on a fully automated DPC Konelab 60i clinical analyzer used in routine diagnosis. We classified 53 samples into concentration zones derived from four different sets of cutoff values that are related to antibiotic prescription scenarios in the case of respiratory tract infections. The agreements between the methods were ELISA/ITA at 87.7%, ELISA/BFPD-IA at 87.3%, and ITA/-BFPD-IA at 93.9%, reaching 98-99% in all cases when considering the calculated relative combined uncertainty of the single measurement of each sample. In a subgroup of 37 samples, which were analyzed for absolute concentration quantification, the scatter plot slopes' correlations were as follows: ELISA/ITA 1.15, R 2 = 0.97; BFPD-IA/ELISA 1.12, R 2 = 0.95; BFPD-IA/ITA 0.95, R 2 = 0.93. These very good performances and the agreement between BFPD-IA and ITA (routine diagnostic), combined with BFPD-IA's functional advantages over ITA (and ELISA)-such as quick time to result (~20 min), reduced consumed reagents (only one assay buffer and no washing), few and easy steps, and compatibility with nucleic-acid-amplification instruments-render it a potential approach for a reliable, cost-efficient, evidence-based point-of-care diagnostic test for guiding antibiotic prescriptions.

Background: Galaxy is a web-based open-source platform for scientific analyses. Researchers use thousands of high-quality tools and workflows for their respective analyses in Galaxy. Tool recommender system predicts a collection of tools that can be used to extend an analysis. In this work, a tool recommender system is developed by training a transformer on workflows available on Galaxy Europe and its performance is compared to other neural networks such as recurrent, convolutional and dense neural networks., Results: The transformer neural network achieves two times faster convergence, has significantly lower model usage (model reconstruction and prediction) time and shows a better generalisation that goes beyond training workflows than the older tool recommender system created using RNN in Galaxy. In addition, the transformer also outperforms CNN and DNN on several key indicators. It achieves a faster convergence time, lower model usage time, and higher quality tool recommendations than CNN. Compared to DNN, it converges faster to a higher precision@k metric (approximately 0.98 by transformer compared to approximately 0.9 by DNN) and shows higher quality tool recommendations., Conclusion: Our work shows a novel usage of transformers to recommend tools for extending scientific workflows. A more robust tool recommendation model, created using a transformer, having significantly lower usage time than RNN and CNN, higher precision@k than DNN, and higher quality tool recommendations than all three neural networks, will benefit researchers in creating scientifically significant workflows and exploratory data analysis in Galaxy. Additionally, the ability to train faster than all three neural networks imparts more scalability for training on larger datasets consisting of millions of tool sequences. Open-source scripts to create the recommendation model are available under MIT licence at https://github.com/anuprulez/galaxy_tool_recommendation_transformers., (© 2023. The Author(s).)

Purpose: The ambition of the research group was to develop a sensor-based system that allowed the transfer of results with strain sensors applied to the knee joint. This system was to be validated in comparison to the current static mechanical measurement system. For this purpose, the internal rotation laxity of the knee joint was measured, as it is relevant for anterolateral knee laxity and anterior cruciate ligament (ACL) injury., Methods: This is a noninvasive measurement method using strain sensors which are applied to the skin in the course of the anterolateral ligament. The subjects were placed in supine position. First the left and then the right leg were clinically examined sequentially and documented by means of an examination form. 11 subjects aged 21 to 45 years, 5 women and 6 men were examined. Internal rotation of the lower leg was performed with a torque of 2 Nm at a knee flexion angle of 30°., Results: Comparison of correlation between length change and internal knee rotation angle showed a strong positive correlation (r = 1, p < 0.01). Whereas females showed a significant higher laxity vs. males (p = 0.003)., Conclusions: The present study showed that the capacitive strain sensors can be used for reproducible measurement of anterolateral knee laxity. In contrast to the previous static systems, a dynamic measurement will be possible by this method in the future., (© 2023. The Author(s).)

A real-time, noninvasive, and clinically applicable aging test in humans has yet to be established. Herein we propose a sweat- and wearable-based test to determine biological age. This test would empower users to monitor their aging process and take an active role in managing their lifestyle and health., Competing Interests: Declaration of interests No interests are declared by the authors., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Thermal noise drives cellular structures, bacteria, and viruses on different temporal and spatial scales. Their weak interactions with their environment can change on subsecond scales. However, particle interactions can be hidden or invisible-even when measured with thermal noise sensitivity, leading to misconceptions about their binding behavior. Here, it is demonstrated how invisible particle interactions at the cell periphery become visible by MHz interferometric thermal noise tracking and frequency decomposition at a spectral update rate of only 0.5 s. The particle fluctuations are analyzed in radial and lateral directions by a viscoelastic modulus G(ω,t ex ) over the experiment time t ex , revealing a surprisingly similar, frequency dependent response for different cell types. This response behavior can be explained by a mathematical model for molecular scale elasticity and damping. The method to reveal hidden interactions is tested at two examples: the stiffening of macrophage filopodia tips within 2 s with particle contact invisible by the fluctuation width. Second, the extent and stiffness of the soft cell glycocalyx is measured, which can be sensed by a particle only on microsecond-timescales, but which remains invisible on time-average. This concept study shows how to uncover hidden cellular interactions, if particle motions are measured at high-speed., (© 2023 The Authors. Small published by Wiley-VCH GmbH.)

High-performance thermoplastics like polyetheretherketone (PEEK), with their outstanding thermal stability, mechanical properties and chemical stability, have great potential for various structural applications. Combining with additive manufacturing methods extends further PEEK usage, e.g., as a mold insert material in polymer melt processing like injection molding. Mold inserts must possess a certain mechanical stability, a low surface roughness as well as a good thermal conductivity for the temperature control during the molding process. With this in mind, the commercially available high-performance thermoplastic PEEK was doped with small amounts of carbon nanotubes (CNT, 6 wt%) and copper particles (10 wt%) targeting enhanced thermomechanical properties and a higher thermal conductivity. The composites were realized by a commercial combined compounder and filament maker for the usage in a material extrusion (MEX)-based 3D-printer following the fused filament fabrication (FFF) principle. Commercial filaments made from PEEK and carbon fiber reinforced PEEK were used as reference systems. The impact of the filler and the MEX printing conditions like printing temperature, printing speed and infill orientation on the PEEK properties were characterized comprehensively by tensile testing, fracture imaging and surface roughness measurements. In addition, the thermal conductivity was determined by the laser-flash method in combination with differential scanning calorimetry and Archimedes density measurement. The addition of fillers did not alter the measured tensile strength in comparison to pure PEEK significantly. The fracture images showed a good printing quality without the MEX-typical voids between and within the deposited layers. Higher printing temperatures caused a reduction of the surface roughness and, in some cases, an enhanced ductile behavior. The thermal conductivity could be increased by the addition of the CNTs. Following the given results, the most critical process step is the compounding procedure, because for a reliable process-parameter-property relationship, a homogeneous particle distribution in the polymer matrix yielding a reliable filament quality is essential.

In this study Ag nanoparticles supported on carbon black (Ag/C) were studied as catalysts for the electrochemical reduction of CO 2 to CO. The nanoparticles were synthesized on three carbon supports, namely Super P, Vulcan and Ketjenblack with surface areas from 50 to 800 m 2 g -1 using cysteamine as a linker as proposed by Kim et al., J. Am. Chem. Soc., 2015, 137 , 13844. Gas diffusion electrodes were fabricated with all three Ag/Cs and then characterized in a zero-gap electrolyzer. All three supported catalysts achieve high voltage efficiencies, mass activities, and faradaic efficiencies above 80% up to 200 mA cm -2 with Ag loadings of ∼0.07 mg cm -2 . Using an IrO 2 anode, a partial CO current density of 196 mA cm -2 at 2.95 V and a mass activity of 3920 mA mg -1 at a cell voltage of 3.2 V was achieved. When changing the electrolyte from 0.1 M KOH to 0.1 M CsOH, it is possible to achieve 90% FE CO at 300 mA cm -2 . This results in a mass activity up to 5400 mA mg -1 . Moreover, long-term tests at 300 mA cm -2 with 0.1 M CsOH resulted in FE CO remaining above 80% over 11 h. The electrochemical performance did not show a dependence on the carbon support, indicating that mass transport is limiting the cathode, rather than catalyst kinetics. It is worth noting that this may only apply to electrodes with PTFE binders as used in this study, and electrodes with ionomer binders may show a dependence on the catalyst support., Competing Interests: The authors declare no competing financial interest., (This journal is © The Royal Society of Chemistry.)

Neocortical interneurons provide inhibition responsible for organizing neuronal activity into brain oscillations that subserve cognitive functions such as memory, attention, or prediction. However, the interneuronal contribution to the entrainment of neocortical oscillations within and across different cortical layers was not described. Here, using layer-specific optogenetic stimulations with micro-Light-Emitting Diode arrays, directed toward parvalbumin-expressing (PV) interneurons in non-anesthetized awake mice, we found that supragranular layer stimulations of PV neurons were most efficient at entraining supragranular local field potential (LFP) oscillations at gamma frequencies (γ: 25-80 Hz), whereas infragranular layer stimulation of PV neurons better entrained the LFP at delta (δ: 2-5 Hz) and theta (θ: 6-10 Hz) frequencies. At the level of neuronal action potential activity, we observed that supragranular neurons better followed the imposed PV stimulation rhythm than their infragranular counterparts at most frequencies when the stimulation was delivered in their respective layer. Moreover, the neuronal entrainment evoked by local stimulation could propagate across layers, though with a lesser impact when the stimulation occurs in deep layers, suggesting a direction-specific laminar propagation. These results establish a layer-based framework for oscillations to entrain the primary somatosensory cortex in awake conditions., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The need for more economical catalysts for various combustion reactions is continuously driving catalyst development. We present Differential Thermal Analysis (DTA) and Differential Scanning Calorimetry (DSC) as suitable techniques for fast examination of catalyst activity for combustion reactions. The heat of reaction ΔH r generated at the catalyst in a combustible atmosphere is the measure for estimating the capability of the catalyst. Present investigations verify the reliability of both methods for the pre-selection of catalysts for further extensive investigations. To simplify the measurements and the result evaluation, a new measurement routine is introduced which is more suitable for rapid catalyst investigation than the conventional approach. For initial investigations, oxidation of 1% methane on a cobalt oxide catalyst was used. First, DTA measurements were performed. The vessel size and the amount of catalyst are considered as factors influencing the thermal signal. Simultaneous mass spectrometry measurements were used to better understand the formation of the DTA response. Comparable DSC investigations were then conducted. Finally, the behavior of catalyst was compared with two commercial palladium/alumina catalysts using DTA and DSC. Our investigations show that DTA and DSC are powerful methods to identify potential catalysts in a fast and reproducible manner, provided that all parameters influencing the thermal signal are kept constant., (© 2023. The Author(s).)

We present a centrifugal microfluidic cartridge for the eight-fold parallel generation of monodisperse water-in-oil droplets using standard laboratory equipment. The key element is interfacing centrifugal microfluidics with its design based on polar coordinates to the linear structures of standard high-throughput laboratory automation. Centrifugal step emulsification is used to simultaneously generate droplets from eight samples directly into standard 200 μl PCR 8-tube strips. To ensure minimal manual liquid handling, the design of the inlets allows the user to load the samples and the oil via a standard multichannel pipette. Simulation-based design of the cartridge ensures that the performance is consistent in each droplet generation unit despite the varying radial positions that originate from the interface to the linear oriented PCR 8-tube strip and from the integration of linear oriented inlet holes for the multichannel pipettes. Within 10 minutes, sample volumes of 50 μl per droplet generation unit are emulsified at a fixed rotation speed of 960 rpm into 1.47 × 10 5 monodisperse droplets with a mean diameter of 86 μm. The overall coefficient of variation (CV) of the droplet diameter was below 4%. Feasibility is demonstrated by an exemplary digital droplet polymerase chain reaction (ddPCR) assay which showed high linearity ( R 2 ≥ 0.999) across all of the eight tubes of the strip.

Electrical Impedance Tomography (EIT) is a low-cost imaging method which reconstructs two-dimensional cross-sectional images, visualising the impedance change within the thorax. However, the reconstruction of an EIT image is an ill-posed inverse problem. In addition, blurring, anatomical alignment, and reconstruction artefacts can hinder the interpretation of EIT images. In this contribution, we introduce a patient-specific structural prior mask into the EIT reconstruction process, with the aim of improving image interpretability. Such a prior mask ensures that only conductivity changes within the lung regions are reconstructed. To evaluate the influence of the introduced structural prior mask, we conducted numerical simulations with two scopes in terms of their different ventilation statuses and varying atelectasis scales. Quantitative analysis, including the reconstruction error and figures of merit, was applied in the evaluation procedure. The results show that the morphological structures of the lungs introduced by the mask are preserved in the EIT reconstructions and the reconstruction artefacts are decreased, reducing the reconstruction error by 25.9% and 17.7%, respectively, in the two EIT algorithms included in this contribution. The use of the structural prior mask conclusively improves the interpretability of the EIT images, which could facilitate better diagnosis and decision-making in clinical settings.

A rapid, precise, and viability-retaining method for cytoplasmic molecule delivery is highly desired for cell engineering. Routine methods suffer from low throughput, lack of selectivity, requirement of helper compounds, predominant endosomal delivery, and/or are restricted to specific molecule classes. Photonic cell manipulation bears the potential to overcome these drawbacks. Here we investigated mammalian cell manipulation by single sub-nanosecond laser pulses. Axial beam waist positioning close to a cell monolayer induced culture vessel damage and zones of cell ablation. Cells at margins of ablation zones exhibited uptake of membrane-impermeant fluorophores and GFP expression plasmids. Increasing Rayleigh-length and beam waist diameter reduced the sensitivity to axial defocusing and resulted in robust molecule transfer. Serial application of single pulses focused over a moving cell monolayer yielded quantitative molecule transfer to cells at rates up to 40%. Our results could be basic to spatially and temporally controlled single laser pulse-mediated marker-free high throughput cell manipulation., (© 2023 Wiley-VCH GmbH.)

In this work, a process chain for the realization of dense Ti6Al4V parts via different material extrusion methods will be introduced applying eco-friendly partially water-soluble binder systems. In continuation of earlier research, polyethylene glycol (PEG) as a low molecular weight binder component was combined either with poly(vinylbutyral) (PVB) or with poly(methylmethacrylat) (PMMA) as a high molecular weight polymer and investigated with respect to their usability in FFF and FFD. The additional investigation of different surfactants' impact on the rheological behaviour applying shear and oscillation rheology allowed for a final solid Ti6Al4V content of 60 vol%, which is sufficient to achieve after printing, debinding and thermal densification parts with densities better than 99% of the theoretical value. The requirements for usage in medical applications according to ASTM F2885-17 can be fulfilled depending on the processing conditions.

Photoacoustic gas sensing is a method suited for the detection of radiation absorbing molecular species in the gas phase. Due to the backgroand-free detection, it has considerable benefits in the measurement of very low concentrations down to the parts-per-trillion range. Yet in resonant systems, the resonance frequency depends on several parameters like temperature or gas composition and therefore must be continuously determined. In the present work, we propose a new method of tracking the resonance frequency using a photoacoustic signal generated at the walls of the resonant cell. The method has been evaluated with two different photoacoustic setups intended for the detection of NO 2 . We further propose an algorithm for finding the resonance frequency and evaluated the performance thereof. With this method, it is possible to detect the resonance frequency of a cylindrical and a dumbbell-shaped cell in less than two seconds and with an accuracy < 0.06% and < 0.2%, respectively., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Infection with the necrotrophic fungus Diplodia sapinea (Fr.) Fuckel is among the economically and ecologically most devastating diseases of conifers in the northern hemisphere and is accelerated by global climate change. This study aims to characterize the changes mediated by D. sapinea infection on its pine host (Pinus sylvestris L.) that lead to the death of its needles. For this purpose, we performed an indoor infection experiment and inoculated shoot tips of pine seedlings with virulent D. sapinea. The consequences for foliar traits, including the phytohormone profile, were characterized at both the metabolite and transcriptome level. Our results showed that D. sapinea infection strongly affected foliar levels of most phytohormones and impaired a multitude of other metabolic and structural foliar traits, such as reactive oxygen species scavenging. Transcriptome analysis revealed that these changes are partially mediated via modified gene expression by fungal exposure. Diplodia sapinea appears to overcome the defense reactions of its pine host by reprogramming gene expression and post-transcriptional controls that determine essential foliar metabolic traits such as the phytohormone profile, cell wall composition and antioxidative system., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background and Aims: Atherosclerosis is a systemic and chronic inflammatory disease propagated by monocytes and macrophages. Yet, our knowledge on how transcriptome of these cells evolves in time and space is limited. We aimed at characterizing gene expression changes in site-specific macrophages and in circulating monocytes during the course of atherosclerosis., Methods: We utilized apolipoprotein E-deficient mice undergoing one- and six-month high cholesterol diet to model early and advanced atherosclerosis. Aortic macrophages, peritoneal macrophages, and circulating monocytes from each mouse were subjected to bulk RNA-sequencing (RNA-seq). We constructed a comparative directory that profiles lesion- and disease stage-specific transcriptomic regulation of the three cell types in atherosclerosis. Lastly, the regulation of one gene, Gpnmb, whose expression positively correlated with atheroma growth, was validated using single-cell RNA-seq (scRNA-seq) of atheroma plaque from murine and human., Results: The convergence of gene regulation between the three investigated cell types was surprisingly low. Overall 3245 differentially expressed genes were involved in the biological modulation of aortic macrophages, among which less than 1% were commonly regulated by the remote monocytes/macrophages. Aortic macrophages regulated gene expression most actively during atheroma initiation. Through complementary interrogation of murine and human scRNA-seq datasets, we showcased the practicality of our directory, using the selected gene, Gpnmb, whose expression in aortic macrophages, and a subset of foamy macrophages in particular, strongly correlated with disease advancement during atherosclerosis initiation and progression., Conclusions: Our study provides a unique toolset to explore gene regulation of macrophage-related biological processes in and outside the atheromatous plaque at early and advanced disease stages., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

In this work, self-lubricating and electrically conductive polymers on a polypropylene (PP) matrix were prepared and investigated. These properties were obtained by additivating PP with carbon black (CB) and multi-walled carbon nanotubes (MWCNTs), in combination with a surface active ionic liquid (IL, trihexyltetradecylphosphonium docusate [P 66614 ][DOC]). These polymeric composites are expected to achieve coefficients of friction (COFs) comparable to lubricated systems. Combined with electrical conductivity, these materials could be applied in electrically loaded tribosystems. The COF was reduced by up to 25% compared to that of plain PP, and high electrical conductivity and self-lubrication were achieved. Fundamental differences between the carbon-based fillers in their interaction with IL were investigated with high-resolution surface analysis (TEM, AFM) and Raman and ATR-FTIR spectroscopy. By varying the tribological test parameters, the application limits of self-lubrication were identified. It was demonstrated that the contact pressure has a strong influence on the COF. Therefore, this work points to potential applications in ( e.g. 3D-printed) bearings and electrically loaded bearings where electrical conductivity and relatively low COFs are required., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Spheroids, organoids, or cell-laden droplets are often used as building blocks for bioprinting, but so far little is known about the spatio-temporal cellular interactions subsequent to printing. We used a drop-on-demand bioprinting approach to study the biological interactions of such building blocks in dimensions of micrometers. Highly-density droplets (approximately 700 cells in 10 nL) of multiple cell types were patterned in a 3D hydrogel matrix with a precision of up to 70 μm. The patterns were used to investigate interactions of endothelial cells (HUVECs) and adipose-derived mesenchymal stem cells (ASCs), which are related to vascularization. We demonstrated that a gap of 200 μm between HUVEC and ASC aggregates led to decreased sprouting of HUVECs towards ASCs and increased growth from ASCs towards HUVECs. For mixed aggregates containing both cell types, cellular interconnections of ASCs with lengths of up to approximately 800 µm and inhibition of HUVEC sprouting were observed. When ASCs were differentiated into smooth muscle cells (dASCs), separate HUVEC aggregates displayed decreased sprouting towards dASCs, whereas no cellular interconnections nor inhibition of HUVEC sprouting were detected for mixed dASCs/HUVEC aggregates. These findings demonstrate that our approach could be applied to investigate cell-cell interactions of different cell types in 3D co-cultures.

cfDNA is an emerging biomarker with promising uses for the monitoring of cancer or infectious disease diagnostics. This work demonstrates a new concept for an automated cfDNA extraction with nanobeads as the solid phase in a centrifugal microfluidic LabDisk. By using a combination of centrifugal and magnetic forces, we retain the nanobeads in one incubation chamber while sequentially adding, incubating and removing the sample and pre-stored buffers for extraction. As the recovery rate of the typically low concentration of cfDNA is of high importance to attain sufficient amounts for analysis, optimal beadhandling is paramount. The goal is that the cfDNA in the sample adsorbs to the solid phase completely during the binding step, is retained during washing and completely removed during elution. In this work, we improved beadhandling by optimizing the incubation chamber geometry and both frequency and temperature protocols, to maximize recovery rates. For characterization of the extraction performance, synthetic mutant DNA was spiked into human plasma samples. The LabDisk showed better reproducibility in DNA recovery rates with a standard deviation of ±13% compared to a manual approach using spin-columns (±17%) or nanobeads (±26%). The extraction of colorectal cancer samples with both the developed LabDisk and a robotic automation instrument resulted in comparable allele frequencies. Consequently, we present a highly attractive solution for an automated liquid biopsy cfDNA extraction in a small benchtop device.

The design of catalysts with stable and finely dispersed platinum or platinum alloy nanoparticles on the carbon support is key in controlling the performance of proton exchange membrane (PEM) fuel cells. In the present work, an intermetallic PtCo/C catalyst is synthesized via double-passivation galvanic displacement. TEM and XRD confirm a significantly narrowed particle size distribution for the catalyst particles compared to commercial benchmark catalysts (Umicore PtCo/C). Only about 10% of the mass fraction of PtCo particles show a diameter larger than 8 nm, whereas this is up to or even more than 35% for the reference systems. This directly results in a considerable increase in electrochemically active surface area (96 m 2 g -1 vs. >70 m 2 g -1 ), which confirms the more efficient usage of precious catalyst metal in the novel catalyst. Single-cell tests validate this finding by improved PEM fuel cell performance. Reducing the cathode catalyst loading from 0.4 mg cm -2 to 0.25 mg cm -2 resulted in a power density drop at an application-relevant 0.7 V of only 4% for the novel catalyst, compared to the 10% and 20% for the commercial benchmarks reference catalysts., Competing Interests: The authors declare no competing financial interest., (This journal is © The Royal Society of Chemistry.)

In contrast to extensively studied prokaryotic 'small' transcriptomes (encompassing all small noncoding RNAs), small proteomes (here defined as including proteins ≤70 aa) are only now entering the limelight. The absence of a complete small protein catalogue in most prokaryotes precludes our understanding of how these molecules affect physiology. So far, archaeal genomes have not yet been analyzed broadly with a dedicated focus on small proteins. Here, we present a combinatorial approach, integrating experimental data from small protein-optimized mass spectrometry (MS) and ribosome profiling (Ribo-seq), to generate a high confidence inventory of small proteins in the model archaeon Haloferax volcanii . We demonstrate by MS and Ribo-seq that 67% of the 317 annotated small open reading frames (sORFs) are translated under standard growth conditions. Furthermore, annotation-independent analysis of Ribo-seq data showed ribosomal engagement for 47 novel sORFs in intergenic regions. A total of seven of these were also detected by proteomics, in addition to an eighth novel small protein solely identified by MS. We also provide independent experimental evidence in vivo for the translation of 12 sORFs (annotated and novel) using epitope tagging and western blotting, underlining the validity of our identification scheme. Several novel sORFs are conserved in Haloferax species and might have important functions. Based on our findings, we conclude that the small proteome of H. volcanii is larger than previously appreciated, and that combining MS with Ribo-seq is a powerful approach for the discovery of novel small protein coding genes in archaea., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.)

The development of enhanced processes for filtration is one solution for stopping the increasing freshwater and sea pollution caused by microplastic and microfibers. Major contributors to micro-X pollution are domestic devices such as washing machines, which also hold a high technical potential for separating problematic soils from waste water during cleaning cycles. The focus of the present paper are the biomimetic development of a novel concept for filtration and removal of particles such as microfibers in conventional washing machines. To this goal, a TRIZ analysis yielded viable solutions for the major key issues. In a next step, measurements were made with various filters with and without ribbed structures. The results are promising for the incorporation in a filter concept that is easy to operate and cost-effective., (© 2022 IOP Publishing Ltd.)

Background: Artificial intelligence (AI) programs that train on large datasets require powerful compute infrastructure consisting of several CPU cores and GPUs. JupyterLab provides an excellent framework for developing AI programs, but it needs to be hosted on such an infrastructure to enable faster training of AI programs using parallel computing., Findings: An open-source, docker-based, and GPU-enabled JupyterLab infrastructure is developed that runs on the public compute infrastructure of Galaxy Europe consisting of thousands of CPU cores, many GPUs, and several petabytes of storage to rapidly prototype and develop end-to-end AI projects. Using a JupyterLab notebook, long-running AI model training programs can also be executed remotely to create trained models, represented in open neural network exchange (ONNX) format, and other output datasets in Galaxy. Other features include Git integration for version control, the option of creating and executing pipelines of notebooks, and multiple dashboards and packages for monitoring compute resources and visualization, respectively., Conclusions: These features make JupyterLab in Galaxy Europe highly suitable for creating and managing AI projects. A recent scientific publication that predicts infected regions in COVID-19 computed tomography scan images is reproduced using various features of JupyterLab on Galaxy Europe. In addition, ColabFold, a faster implementation of AlphaFold2, is accessed in JupyterLab to predict the 3-dimensional structure of protein sequences. JupyterLab is accessible in 2 ways-one as an interactive Galaxy tool and the other by running the underlying Docker container. In both ways, long-running training can be executed on Galaxy's compute infrastructure. Scripts to create the Docker container are available under MIT license at https://github.com/usegalaxy-eu/gpu-jupyterlab-docker., (© The Author(s) 2023. Published by Oxford University Press GigaScience.)

Centrifugal microfluidics enables fully automated molecular diagnostics at the point-of-need. However, the integration of solid-phase nucleic acid extraction remains a challenge. Under this scope, we developed the magnetophoresis under continuous rotation for magnetic bead-based nucleic acid extraction. Four stationary permanent magnets are arranged above a cartridge, creating a magnetic field that enables the beads to be transported between the chambers of the extraction module under continuous rotation. The centrifugal force is maintained to avoid uncontrolled spreading of liquids. We concluded that below a frequency of 5 Hz, magnetic beads move radially inwards. In support of magnetophoresis, bead inertia and passive geometrical design features allow to control the azimuthal bead movement between chambers. We then demonstrated ferrimagnetic bead transfer in liquids with broad range of surface tension and density values. Furthermore, we extracted nucleic acids from lysed Anopheles gambiae mosquitoes reaching comparable results of eluate purity (LabDisk: A260/A280 = 1.6 ± 0.04; Reference: 1.8 ± 0.17), and RT-PCR of extracted RNA (LabDisk: Ct = 17.9 ± 1.6; Reference: Ct = 19.3 ± 1.7). Conclusively, magnetophoresis at continuous rotation enables easy cartridge integration and nucleic acid extraction at the point-of-need with high yield and purity.

In this project, different calcification methods for collagen and collagen coatings were compared in terms of their applicability for 3D printing and production of collagen-coated scaffolds. For this purpose, scaffolds were printed from polycaprolactone PCL using the EnvisionTec 3D Bioplotter and then coated with collagen. Four different coating methods were then applied: hydroxyapatite (HA) powder directly in the collagen coating, incubation in 10× SBF, coating with alkaline phosphatase (ALP), and coating with poly-L-aspartic acid. The results were compared by ESEM, µCT, TEM, and EDX. HA directly in the collagen solution resulted in a pH change and thus an increase in viscosity, leading to clumping on the scaffolds. As a function of incubation time in 10× SBF as well as in ALP, HA layer thickness increased, while no coating on the collagen layer was apparently observed with poly-L-aspartic acid. Only ultrathin sections and TEM with SuperEDX detected nano crystalline HA in the collagen layer. Exclusively the incubation in poly-L-aspartic acid led to HA crystals within the collagen coating compared to all other methods where the HA layers formed in different forms only at the collagen layer.

Accurately measuring flow rates is a key requirement in many medical applications such as infusion and drug delivery systems. A major drawback of current systems is the low resolution of the sensors in the low flow rate regime. In this article, we present a method based on Holographic PIV/PTV that has been used for the first time to measure flow rates in the range of a few nL/min. Our method requires a very simple setup that combines lensless holography with particle velocimetry. For flow rates in the 70 to 200 nL/min range, the highest uncertainty was 5.6% (coverage factor k =2). This is an open-source project; the CAD designs and software source code are available at https://github.com/gui-miotto/holovel., (© 2022 the author(s), published by De Gruyter, Berlin/Boston.)

The electrochemical reduction of CO 2 is a pivotal technology for the defossilization of the chemical industry. Although pilot-scale electrolyzers exist, water management and salt precipitation remain a major hurdle to long-term operation. In this work, we present high-resolution neutron imaging (6 μm) of a zero-gap CO 2 electrolyzer to uncover water distribution and salt precipitation under application-relevant operating conditions (200 mA cm -2 at a cell voltage of 2.8 V with a Faraday efficiency for CO of 99%). Precipitated salts penetrating the cathode gas diffusion layer can be observed, which are believed to block the CO 2 gas transport and are therefore the major cause for the commonly observed decay in Faraday efficiency. Neutron imaging further shows higher salt accumulation under the cathode channel of the flow field compared to the land., (© 2022. The Author(s).)

Two approaches of an automatic control were studied through mathematical fitting obtained from color mixing saturation curves in polydimethylsiloxane microfluidic devices: The integrative control with variable integral gain and integrative control with constant integral gain. The aim of this work is to control the color percentage decrement when dye is injected. The results indicate that microfluidic systems are very sensitive to changes in flow and the control variable needs to change slowly; that is, it must be small (at least 100 times less than the theoretically calculated values). The control and stabilization of the microfluidic system were achieved for dye percentages above 60%. The controlling color percentage could provide a tool to regulate other parameters' concentration applied to cell culture and alkalinity control (pH) of solutions in microfluidic devices., (© 2022 Author(s).)

Cell cultures aiming at tissue regeneration benefit from scaffolds with physiologically relevant elastic moduli to optimally trigger cell attachment, proliferation and promote differentiation, guidance and tissue maturation. Complex scaffolds designed with guiding cues can mimic the anisotropic nature of neural tissues, such as spinal cord or brain, and recall the ability of human neural progenitor cells to differentiate and align. This work introduces a cost-efficient gelatin-based submicron patterned hydrogel-fiber composite with tuned stiffness, able to support cell attachment, differentiation and alignment of neurons derived from human progenitor cells. The enzymatically crosslinked gelatin-based hydrogels were generated with stiffnesses from 8 to 80 kPa, onto which poly(ε-caprolactone) (PCL) alignment cues were electrospun such that the fibers had a preferential alignment. The fiber-hydrogel composites with a modulus of about 20 kPa showed the strongest cell attachment and highest cell proliferation, rendering them an ideal differentiation support. Differentiated neurons aligned and bundled their neurites along the aligned PCL filaments, which is unique to this cell type on a fiber-hydrogel composite. This novel scaffold relies on robust and inexpensive technology and is suitable for neural tissue engineering where directional neuron alignment is required, such as in the spinal cord.

In this work, a holistic approach for the fabrication of dense Ti6Al4V parts via material extrusion methods (MEX), such as fused filament fabrication (FFF) or fused feedstock deposition (FFD), will be presented. With respect to the requirements of the printing process, a comprehensive investigation of the feedstock development will be described. This covers mainly the amount ratio variation of the main binder components LDPE (low-density polyethylene), HDPE (high-density polyethylene), and wax, characterized by shear and oscillation rheology. Solid content of 60 vol% allowed the 3D printing of even more complex small parts in a reproducible manner. In some cases, the pellet-based FFD seems to be superior to the established FFF. After sintering, a density of 96.6% of theory could be achieved, an additional hot isostatic pressing delivered density values better than 99% of theory. The requirements (mechanical properties, carbon, and oxygen content) for the usage of medical implants (following ASTM F2885-17) were partially fulfilled or shortly missed.

Background: The allocation of non-structural carbohydrates (NSCs) plays a critical role in the physiology and metabolism of tree growth and survival defense. However, little is known about the allocation of NSC after continuous mechanical wounding of pine by resin tapping during tree growth., Results: Here, we examine the NSC allocation in plant tissues after 3 year lasting resin tapping, and also investigate the use of near-infrared reflectance (NIR) spectroscopy to quantify the NSC, starch and free sugar (e.g., sucrose, glucose, and fructose) concentrations in different plant tissues of slash pine. Spectral measurements on pine needle, branch, trunk phloem, and root were obtained before starch and free sugar concentrations were measured in the laboratory. The variation of NSC, starch and free sugars in different plant tissues after resin tapping was analyzed. Partial least squares regression was applied to calibrate prediction models, models were simulated 100 times for model performance and error estimation. More NSC, starch and free sugars were stored in winter than summer both in tapped and control trees. The position of resin tapping significantly influenced the NSCs allocation in plant tissues: more NSCs were transformed into free sugars for defensive resin synthesis close to the tapping wound rather than induced distal systemic responses. Models for predicting NSC and free sugars of plant tissues showed promising results for the whole tree for fructose (R 2 CV  = 0.72), glucose (R 2 CV  = 0.67), NSCs (R 2 CV  = 0.66) and starch (R 2 CV  = 0.58) estimates based on NIR models. Models for individual plant tissues also showed reasonable predictive ability: the best model for NSCs and starch prediction was found in root. The significance multivariate correlation algorithm for variable selection significantly reduced the number of variables. Important variables were identified, including features at 1021-1290 nm, 1480, 1748, 1941, 2020, 2123 and 2355 nm, which are highly related to NSC, starch, fructose, glucose and sucrose., Conclusions: NIR spectroscopy provided a rapid and cost-effective method to monitor NSC, starch and free sugar concentrations after continuous resin tapping. It can be used for studying the trade-off between growth and production of defensive metabolites., (© 2022. The Author(s).)

In microfluidic step emulsification, the size of droplets generated in the dripping regime is predominantly determined by the nozzle's height and only weakly depends on the applied flow rates or liquid properties. While the generation of monodisperse emulsions at high throughput using step emulsifiers has been well established, the generation of double emulsions, i.e. , liquid core-shell structures, is still challenging. Here, we demonstrate a novel double-step emulsification method for the direct generation of multi-core double-emulsions and provide a predictive model for the number of cores. While the mechanism of the formation of the core droplets or empty shell droplets follows the well-established scenario of simple step emulsification, the formation of double-emulsion droplets is strongly affected by the presence of the cores. Passing of the cores through the narrowing neck of the shell postpones shell pinch-off. In particular, we demonstrate that our system can be used for the generation of arbitrary large, tightly packed droplet clusters consisting of a controllable number of droplets. Finally, we discuss the options of upscaling the system for high-throughput generation of tailored double emulsions.

Dry cathode operation is a desired operation mode in anion-exchange membrane water electrolyzers to minimize contamination of the generated hydrogen. However, water management under such operation conditions makes it challenging to maintain reliable performance and durability. Here, we utilize high-resolution in situ neutron imaging (∼6 μm effective resolution) to analyze the water content inside the membrane-electrode-assembly of an anion-exchange membrane water electrolyzer. The ion-exchange capacity (IEC) and thus hydrophilicity of the polymer binder in the cathode catalyst layer is varied to study the influence on water content in the anode (mid IEC, 1.8-2.2 meq. g -1 and high IEC, 2.3-2.6 meq. g -1 ). The neutron radiographies show that a higher ion-exchange capacity binder allows improved water retention, which reduces the drying-out of the cathode at high current densities. Electrochemical measurements confirm a generally better efficiency for a high IEC cell above 600 mA cm -2 . At 1.5 A cm -2 the high IEC has a 100 mV lower overpotential (2.1 V vs. 2.2 V) and a lower high frequency resistance (210 mΩ cm -2 vs. 255 mΩ cm -2 ), which is believed to be linked to the improved cathode water retention and membrane humidification. As a consequence, the performance stability of the high IEC cell at 1 A cm -2 is also significantly better than that of the mid IEC cell (45 mV h -1 vs. 75 mV h -1 )., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)