Abstract: To support experimental research into gas conversion by warm plasmas, models should be developed to explain the experimental observations. These models need to describe all physical and chemical plasma properties in a coupled way. In this paper, we present a modelling approach to solve the complete set of assumed relevant equations, including gas flow, heat balance and species transport, coupled with a rather extensive chemistry set, consisting of 21 species, obtained by reduction of a more detailed chemistry set, consisting of 41 species. We apply this model to study the combined CO2 and CH4 conversion in the presence of O2, in a direct current atmospheric pressure glow discharge. Our model can predict the experimental trends, and can explain why higher O2 fractions result in higher CH4 conversion, namely due to the higher gas temperature, rather than just by additional chemical reactions. Indeed, our model predicts that when more O2 is added, the energy required to reach any set temperature (i.e., the enthalpy) drops, allowing the system to reach higher temperatures with similar amounts of energy. This is in turn related to the higher H2O fraction and lower H2 fraction formed in the plasma, as demonstrated by our model. Altogether, our new self-consistent model can capture the main physics and chemistry occurring in this warm plasma, which is an important step towards predictive modelling for plasma-based gas conversion.

Abstract: This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of
51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.

Abstract: Dysregulation of miRNA expression occurs in many cancers, making miRNAs useful in cancer diagnosis and therapeutic guidance. In a clinical context using methods such as polymerase chain reaction (PCR), the limited amount of miRNAs in circulation often limits their quantification. Here, we present a PCR-free and sensitive singlet oxygen (1O2)-based strategy for the detection and quantification of miRNAs in untreated human plasma from patients diagnosed with prostate cancer. A target miRNA is specifically captured by functionalised magnetic beads and a detection oligonucleotide probe in a sandwich-like format. The formed complex is concentrated at the sensor surface via magnetic beads, providing an interface for the photoinduced redox signal amplification. The detection oligonucleotide probe bears a molecular photosensitiser, which produces 1O2 upon illumination, oxidising a redox reporter and creating a redox cycling loop, allowing quantification of pM level miRNA in diluted human plasma within minutes after hybridisation and without target amplification.

Abstract: Plasma catalysis is a rapidly growing field, often employing a packed-bed dielectric barrier discharge plasma reactor. Such dielectric barrier discharges are complex, especially when a packing material (e.g., a catalyst) is introduced in the discharge volume. Catalysts are known to affect the plasma discharge, though the underlying mechanisms influencing the plasma physics are not fully understood. Moreover, the effect of the catalysts on the plasma discharge and its subsequent effect on the overall performance is often overlooked. In this work, we deliberately design and synthesize catalysts to affect the plasma discharge in different ways. These Ni or Co alumina-based catalysts are used in plasma-catalytic dry reforming of methane and ammonia synthesis. Our work shows that introducing a metal to the dielectric packing can affect the plasma discharge, and that the distribution of the metal is crucial in this regard. Further, the altered discharge can greatly influence the overall performance. In an atmospheric pressure dielectric barrier discharge reactor, this apparently more uniform plasma yields a significantly better performance for ammonia synthesis compared to the more conventional filamentary discharge, while it underperforms in dry reforming of methane. This study stresses the importance of analyzing the plasma discharge in plasma catalysis experiments. We hope this work encourages a more critical view on the plasma discharge characteristics when studying various catalysts in a plasma reactor.

Abstract: The efficiency of a catalytic process is assessed based on conversion, yield, and time effectiveness. However, these parameters are insufficient for evaluating environmentally sustainable research. As the world is urged to shift towards green catalysis, additional factors such as reaction media, raw material availability, sustainability, waste minimization and catalyst biosafety, need to be considered to accurately determine the efficacy and sustainability of the process. By combining the high porosity and versatility of metal organic frameworks (MOFs) and the activity of gold nanoparticles (AuNPs), efficient, cyclable and biosafe composite catalysts can be achieved. Thus, a composite based on AuNPs and the nanometric flexible porous iron(III) aminoterephthalate MIL-88B-NH2 was successfully synthesized and fully characterized. This nanocomposite was tested as catalyst in the reduction of nitroarenes, which were identified as anthropogenic water pollutants, reaching cyclable high conversion rates at short times for different nitroarenes. Both synthesis and catalytic reactions were performed using green conditions, and even further tested in a time-optimizing one-pot synthesis and catalysis experiment. The sustainability and environmental impact of the catalytic conditions were assessed by green metrics. Thus, this study provides an easily implementable synthesis, and efficient catalysis, while minimizing the environmental and health impact of the process.

Abstract: Nonthermal plasmas are currently being studied as a green alternative to the Haber-Bosch process, which is, today, the dominant industrial process allowing for the fixation of nitrogen and, as such, a fundamental component for the production of nitrogen-based industrial fertilizers. In this context, the gliding arc plasma (GAP) is considered a promising choice among nonthermal plasma options. However, its stability is still a key parameter to ensure industrial transfer of the technology. Nowadays, the conventional approach to stabilize this plasma process is to use external resistors. Although this indeed allows for an enhancement of the plasma stability, very little is reported about how it impacts the process efficiency, both in terms of NOx yield and energy cost. In this work, this question is specifically addressed by studying a DC-powered GAP utilized for nitrogen fixation into NOx at atmospheric pressure stabilized by variable external resistors. Both the performance and the stability of the plasma are reported as a function of the utilization of the resistors. The results confirm that while the use of a resistor indeed allows for a strong stabilization of the plasma without impacting the NOx yield, especially at high plasma current, it dramatically impacts the energy cost of the process, which increases from 2.82 to 7.9 MJ/mol. As an alternative approach, we demonstrate that the replacement of the resistor by an inductor is promising since it allows for decent stabilization of the plasma, while it does not affect either the energy cost of the process or the NOx yield.

Abstract: Graphene oxide (GO) is one of the most promising candidates for next generation of atomically thin membranes. Nevertheless, one of the major issues for real world application of GO membranes is their undesirable swelling in an aqueous environment. Recently, we demonstrated that generation of H3O+ and OH- ions (e.g., with an external electric field) in the interlayer gallery could impart aqueous stability to the layered GO membranes (A. Gogoi, ACS Appl. Mater. Interfaces, 2022, 14, 34946). This, however, compromises the water flux through the membrane. In this study, we report on reducing the GO nanosheets as a solution to this issue. With the reduction of the GO nanosheets, the water flux through the layered GO membrane initially increases and then decreases again beyond a certain degree of reduction. Here, two key factors are at play. Firstly, the instability of the H-bond network between water molecules and the GO nanosheets, which increases the water flux. Secondly, the pore size reduction in the interlayer gallery of the membranes, which decreases the water flux. We also observe a significant improvement in the salt rejection of the membranes, due to the dissociation of water molecules in the interlayer gallery. In particular, for the case of 10% water dissociation, the water flux through the membranes can be enhanced without altering its selectivity. This is an encouraging observation as it breaks the traditional tradeoff between water flux and salt rejection of a membrane.

Abstract: Cable bacteria are filamentous, multicellular microorganisms that display an exceptional form of biological electron transport across centimeter-scale distances. Currents are guided through a network of nickel-containing protein fibers within the cell envelope. Still, the mechanism of long-range conduction remains unresolved. Here, we characterize the conductance of the fiber network under dry and wet, physiologically relevant, conditions. Our data reveal that the fiber conductivity is high (median value: 27 S cm−1; range: 2 to 564 S cm−1), does not show any redox signature, has a low thermal activation energy (Ea = 69 ± 23 meV), and is not affected by humidity or the presence of ions. These features set the nickel-based conduction mechanism in cable bacteria apart from other known forms of biological electron transport. As such, conduction resembles that of an organic semi-metal with a high charge carrier density. Our observation that biochemistry can synthesize an organo-metal-like structure opens the way for novel bio-based electronic technologies.

Abstract: Ruddlesden-Popper La????Sr2−????MnO4−???? materials are interesting symmetric solid oxide
fuel cell electrodes due to their good redox stability, mixed ionic and electronic conducting behavior and thermal expansion that matches well with common electrolytes. In reducing environments – as at a solid oxide fuel cell anode – the x = 0.5 member, i.e. La0.5Sr1.5MnO4−????, has a much higher total conductivity than compounds with a different La/Sr ratio, although all those compositions have the same K2NiF4-type I4/mmm structure. The origin for this conductivity difference is not yet known in literature. Now, a combination of in-situ and ex-situ 3D electron diffraction, high-resolution imaging, energy-dispersive X-ray analysis and electron energy-loss spectroscopy uncovered clear differences between x=0.25 and x=0.5 in the pristine structure, as well as in the transformations upon high-temperature reduction. In La0.5Sr1.5MnO4−????, Ruddlesden-Popper n=2 layer defects and an amorphous surface layer are present, but not in La0.25Sr1.75MnO4−????. After annealing at 700°C in 5% H2/Ar, La0.25Sr1.75MnO4−???? transforms to a tetragonal 2D incommensurately modulated structure with modulation vectors ⃗????1 = 0.2848(1) · (⃗????* +⃗????*) and ⃗????2 =0.2848(1) · (⃗????* – ⃗????*), whereas La0.5Sr1.5MnO4−???? only partially transforms to an orthorhombic 1D incommensurately modulated structure,
with ⃗???? = 0.318(2) · ⃗????*. Perovskite domains grow at the crystal edge at 700°C in 5%
H2 or vacuum, due to the higher La concentration on the surface compared to the bulk, which leads to a different thermodynamic equilibrium. Since it is known that a lower degree of oxygen vacancy ordering and a higher amount of perovskite blocks enhance oxygen mobility, those differences in defect structure and structural transformation upon reduction, might all contribute to the higher conductivity of La0.5Sr1.5MnO4−???? in solid oxide fuel cell anode conditions compared to other La/Sr ratios.

Abstract: Photocathodes play a vital role in photoelectrocatalytic water splitting by acting as catalysts for reducing protons to hydrogen gas when exposed to light. Recent advancements in photocathodes have focused on addressing the limitations of noble metal-based materials. These noble metal-based photocathodes rely on expensive and scarce metals such as platinum and gold as cocatalysts or ohmic back contacts, respectively, rendering the final system less sustainable and costly when applied at scale. This mini-review summarizes the important recent progress in the development of non-noble metal-based photocathodes and their performance in the hydrogen evolution reaction during photoelectrochemical (PEC) water splitting. These advancements bring non-noble metal-based photocathodes closer to their noble metal-based counterparts in terms of performance, thereby paving the way forward toward industrial-scale photoelectrolyzers or PEC cells for green hydrogen production.

Abstract: The European BorderSens project leverages voltammetric sensors, developed with end-users' input, to rapidly and accurately detect illicit drugs. By embracing practicalities and validation, this technology has the potential to combat the illicit drug problem.

Abstract: The interface heat transfer of two layers induced by van der Waals (vdW) contacts is theoretically investigated, based on first-principles calculations at low temperatures. The results suggest that out-of-plane acoustic phonons with low frequencies dominate the interface thermal transport due to the vdW interaction. The interface thermal conductivity is proportional to the cubic of temperature at very low temperatures, but becomes linearly proportional to temperature as temperature increases. We show that manipulating the strain alters vdW coupling, leading to increased interfacial thermal conductivity at the interface. Our findings provide valuable insights into the interface heat transport in vdW heterostructures and support further design and optimization of electronic and optoelectronic nanodevices based on vdW contacts. The heat transfer induced by van der Waals contacts is dominated by ZA phonons. The interface thermal conductivity is proportional to the cubic of temperature, but becomes linearly proportional to temperature as temperature increases.

Abstract: Electrochemical sensors have emerged as a new analytical tool for illicit drug detection to facilitate ultrafast and accurate identification of suspicious compounds on-site. Drugs of abuse can be identified using their unique voltammetric fingerprint at a given pH. Today, the right buffer solution is manually selected based on drug appearance, and in some cases, a consecutive analysis in two different pH solutions is required. In this work, we present a disposable microfluidic multichannel sensor system that automatically records fingerprints in two pH solutions (e.g., pH 5 and pH 12). This system has two advantages. It will overcome the manual selection of a buffer solution at the right pH, decrease analysis time, and minimize the risk of human errors. Second, the combination of two fingerprints, the superfingerprint, contains more detailed information about the samples, which enhances the selectivity of the analytical technique. First, real-time pH measurements proved that the sample can be brought to the desired pH within a minute. Subsequently, an electrochemical study on the microfluidic platform with 1 mM illicit drug standards of MDMA, cocaine, heroin, and methamphetamine showed that the characteristic voltammetric fingerprints and peak potentials are reproducible, also in the presence of common cutting agents. Finally, the microfluidic concept was validated with real confiscated samples, showing promising results for the user-friendly identification of drugs of abuse. In short, this paper presents a successful proof-of-concept study of a multichannel microfluidic sensor system to enrich the fingerprints of illicit drugs at pH 5 and pH 12, thus providing a low-cost, portable, and rapid identification system of illicit drugs with minimal user intervention.

Abstract: Museum staff usually relies on a proven combination of X-ray radiography (XRR) and infrared reflectography (IRR) to study paintings in a non-destructive manner. In the last decades, however, the research toolbox of heritage scientists has expanded considerably, with a prime example being macro X-ray fluorescence (MA-XRF), producing element-specific images. The goal of this article is to illustrate the added value of augmenting MA-XRF with pulse phase thermography (PPT), a variant of active infrared thermographic imaging (IRT), which is an innovative diagnostic method that is able to reveal variations between or in materials, based on a different response to minor fluctuations in temperature when irradiated with optical radiation. By examining three 16thand 17th-century panel paintings we assess the extent in which combined MA-XRF and PPT contributes to a better understanding of two commonly encountered interventions to panel paintings: (a) Anstuckungen (enlargement of the panel) or (b) substitutions (replacement of part of the panel). Yielding information from different depths of the painting, these two techniques proved highly complementary with IRR and XRR, expanding the understanding of the build-up, genesis, and material history of the paintings. While MA-XRF documented the interventions to the wooden substrate indirectly by revealing variations in painting materials, paint handling and/ or layer sequence between the original part and the extended or replaced planks, PPT proved beneficial for the study of the wooden support itself, by providing a clear image of the wood structure quasi-free of distortion by the superimposed paint or cradling. XRR, on the other hand, revealed other features from the wood structure, not visible with PPT, and allowed looking through the wooden panels, revealing e.g. the dowels used for joining the planks. Additionally, IRR visualised dissimilarities in the underdrawings. In this way, the results indicate that PPT has the potential to become an acknowledged add-on to the expanding set of imaging methods for paintings, especially when used in combination with MA-XRF, IRR and XRR.

Abstract: Plasma catalysis has emerged as a promising approach for driving thermodynamically unfavorable chemical
reactions. Nevertheless, comprehending the mechanisms involved remains a challenge, leading to uncertainty
about whether the optimal catalyst in plasma catalysis aligns with that in thermal catalysis. In this research, we
explore this question by studying monometallic catalysts (Fe, Co, Ni and Mo) and bimetallic catalysts (Fe-Co, Mo-
Co, Fe-Ni and Mo-Ni) in both thermal catalytic and plasma catalytic NH3 decomposition. Our findings reveal that
the Fe-Co bimetallic catalyst exhibits the highest activity in thermal catalysis, the Fe-Ni bimetallic catalyst
outperforms others in plasma catalysis, indicating a discrepancy between the optimal catalysts for the two
catalytic modes in NH3 decomposition. Comprehensive catalyst characterization, kinetic analysis, temperature
program surface reaction experiments and plasma diagnosis are employed to discuss the key factors influencing
NH3 decomposition performance.