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: Plasma‐based CO₂conversion has attracted increasing interest. However, to understand the impact of plasma operation on post‐plasma processes, we studied the effect of adding N₂, N₂/CH₄and N₂/CH₄/H₂O to a CO₂gliding arc plasmatron (GAP) to obtain valuable insights into their impact on exhaust stream composition and temperature, which will serve as feed gas and heat for post‐plasma catalysis (PPC). Adding N₂improves the CO₂conversion from 4 % to 13 %, and CH₄addition further promotes it to 44 %, and even to 61 % at lower gas flow rate (6 L/min), allowing a higher yield of CO and hydrogen for PPC. The addition of H₂O, however, reduces the CO₂conversion from 55 % to 22 %, but it also lowers the energy cost, from 5.8 to 3 kJ/L. Regarding the temperature at 4.9 cm post‐plasma, N₂addition increases the temperature, while the CO₂/CH₄ratio has no significant effect on temperature. We also calculated the temperature distribution with computational fluid dynamics simulations. The obtained temperature profiles (both experimental and calculated) show a decreasing trend with distance to the exhaust and provide insights in where to position a PPC bed.

Abstract: The combination of plasma with catalysis for the synthesis and decomposition of NH3 is an attractive route to the production of carbon-neutral fertiliser and energy carriers and its conversion into H2. Recent years have seen fast developments in the field of plasma-catalytic NH3 life cycle. This work summarises the most recent advances in plasma-catalytic and related NH3-focussed processes, identifies some of the most important discoveries, and addresses plausible strategies for future developments in plasma-based NH3 technology.

Abstract: Molecular dynamics simulations are essential for a better understanding of dissociative chemisorption on metal surfaces, which is often the rate-controlling step in heterogeneous and plasma catalysis. The workhorse quasi-classical trajectory approach ubiquitous in molecular dynamics is able to accurately predict reactivity only for high translational and low vibrational energies. In contrast, catalytically relevant conditions generally involve low translational and elevated vibrational energies. Existing quantum dynamics approaches are intractable or approximate as a result of the large number of degrees of freedom present in molecule−metal surface reactions. Here, we extend a ring polymer molecular dynamics approach to fully include, for the first time, the degrees of freedom of a moving metal surface. With this approach, experimental sticking probabilities for the dissociative chemisorption of methane on Pt(111) are reproduced for a large range of translational and vibrational energies by including nuclear quantum effects and employing full-dimensional simulations.

Abstract: Warm plasma offers a promising route for CO2 splitting into valuable CO, yet recombination reactions of CO with oxygen, forming again CO2, have recently emerged as critical limitation. This study combines experiments and fluid dynamics + chemical kinetics modelling to comprehensively analyse the recombination reactions upon CO2 splitting in an atmospheric plasmatron. We introduce an innovative in-situ gas sampling technique, enabling 2D spatial mapping of gas product compositions and temperatures, experimentally confirming for the first time the substantial limiting effect of CO recombination reactions in the afterglow region. Our results show that the CO mole fraction at a 5 L/min flow rate drops significantly from 11.9 % at a vertical distance of z = 20 mm in the afterglow region to 8.6 % at z = 40 mm. We constructed a comprehensive 2D model that allows for spatial reaction rates analysis incorporating crucial reactions, and we validated it to kinetically elucidate this phenomenon. CO2 +M⇌O+CO+M and CO2 +O⇌CO+O2 are the dominant reactions, with the forward reactions prevailing in the plasma region and the backward reactions becoming prominent in the afterglow region. These results allow us to propose an afterglow quenching strategy for performance enhancement, which is further demonstrated through a meticulously developed plasmatron reactor with two-stage cooling. Our approach substantially increases the CO2 conversion (e.g., from 6.6 % to 19.5 % at 3 L/min flow rate) and energy efficiency (from 13.5 % to 28.5 %, again at 3 L/min) and significantly shortens the startup time (from ~ 150 s to 25 s). Our study underscores the critical role of inhibiting recombination reactions in plasma-based CO2 conversion and offers new avenues for performance enhancement.

Abstract: Solid carbon deposition is a persistent challenge in dry reforming of methane (DRM), affecting both classical and plasma-based processes. In this work, we use a microwave plasma in reverse vortex flow configuration to overcome this issue in CO₂/CH₄plasmas. Indeed, this configuration efficiently mitigates carbon deposition, enabling operation even with pure CH₄feed gas, in contrast to other configurations. At the same time, high reactor performance is achieved, with CO₂and CH₄conversions reaching 33% and 44% respectively, at an energy cost of 14 kJ L⁻¹for a CO₂ : CH₄ratio of 1 : 1. Laser scattering and optical emission imaging demonstrate that the shorter residence time in reverse vortex flow lowers the gas temperature in the discharge, facilitating a shift from full to partial CH₄pyrolysis. This underscores the pivotal role of flow configuration in directing process selectivity, a crucial factor in complex chemistries like CO₂/CH₄mixtures and very important for industrial applications.

Abstract: technologies have been expanding, and one of the most exciting and rapidly growing
applications is in biology and medicine. Most biomedical studies with DBD plasma systems are performed in vitro, which include cells grown on the surface of plastic well plates, or in vivo, which include animal research models (e.g. mice, pigs). Since many DBD systems use the biological target as the secondary electrode for direct plasma generation and treatment, they are sensitive to the surface properties of the target, and thus can be altered based on the in vitro or in vivo system used. This could consequently affect biological response from plasma treatment. Therefore, in this study, we investigated the DBD plasma behavior both in vitro (i.e. 96-well flat bottom plates, 96-well U-bottom plates, and 24-well flat bottom plates), and in vivo (i.e. mouse skin). Intensified charge coupled device (ICCD) imaging was performed and the plasma discharges were visually distinguishable between the different systems. The geometry of the wells did not affect DBD plasma generation for low application distances (≤ 2 mm), but differentially affected plasma uniformity on the bottom of the well at greater distances. Since DBD plasma treatment in vitro is rarely performed in dry wells for plasma medicine experiments, the effect of well wetness was also investigated. In all in vitro cases, the uniformity of the DBD plasma was affected when comparing wet versus dry wells, with the plasma in the wide-bottom wells appearing the most similar to plasma generated on mouse skin. Interestingly, based on quantification of ICCD images, the DBD plasma intensity per surface area demonstrated an exponential one-phase decay with increasing application distance, regardless of the in vitro or in vivo system. This trend is similar to that of the energy per pulse of plasma, which is used to determine the total plasma treatment energy for biological systems. Optical emission spectroscopy performed on the plasma revealed similar trends in radical species generation between the plastic well plates and mouse skin. Therefore, taken together, DBD plasma intensity per surface area may be a valuable parameter to be used as a simple method for in situ monitoring during biological treatment and active plasma treatment control, which can be applied for in vitro and in vivo systems.

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.

Abstract: Chiral ligands are considered a required ingredient during the synthesis of dissymmetric plasmonic metal nanocrystals. The mechanism behind the generation of chiral structures involves the formation of high Miller index chiral facets, induced by the adsorption of such chiral ligands. We found however that, chirality can also evolve spontaneously, without the involvement of any chiral ligands, during the co-deposition of Au and Ag on Au nanorods. When using a specific Au/Ag ratio, phase segregation of the two metals leads to an interface within the obtained AuAg shell, which can be exposed by removing the Ag component via oxidative etching. Although a close-to-racemic mixture of chiral Au nanorods with right and left handedness is found in solution, electron tomography analysis evidences left- and righthanded helicities, both at the Au-Ag interface and at the exposed surface of Au NRs after Ag etching. The helicity profile of the NRs indicates dominating inclination angles in a range from 30° to 60°. Single-particle optical characterization also reveals random handedness in the plasmonic response of individual nanorods. We hypothesize that, the origin of chirality is related with symmetry breaking during the co-deposition of Au and Ag, through an initial perturbation in a small region on the Au-Ag interface that eventually leads to chiral segregation throughout the nanocrystal.

Abstract: This work reports the use of modified screen-printed carbon electrodes (SPCEs) for the identification of three drugs of abuse and two habitual cutting agents, caffeine and paracetamol, combining voltammetric sensing and chemometrics. In order to achieve this goal, codeine, heroin and morphine were subjected to Square Wave Voltammetry (SWV) at pH 7, in order to elucidate their electrochemical fingerprints. The optimized SPCEs electrode array, which have a differentiated response for the three oxidizable compounds, was derived from Carbon, Prussian blue, Cobalt (II) phthalocyanine, Copper (II) oxide, Polypyrrole and Palladium nanoparticles ink-modified carbon electrodes. Finally, Principal Component Analysis (PCA) coupled with Silhouette parameter assessment was used to select the most suitable combination of sensors for identification of drugs of abuse in presence of cutting agents.

Abstract: Duplexed aptamers (DAs) are widespread aptasensor formats that simultaneously recognize and signal the concentration of target molecules. They are composed of an aptamer and aptamer complementary element (ACE) which consists of a short oligonucleotide that partially inhibits the aptamer sequence. Although the design principles to engineer DAs are straightforward, the tailored development of DAs for a particular target is currently based on trial and error due to limited knowledge of how the ACE sequence affects the final performance of DA biosensors. Therefore, we have established a thermodynamic model describing the influence of the ACE on the performance of DAs applied in equilibrium assays and demonstrated that this relationship can be described by the binding strength between the aptamer and ACE. To validate our theoretical findings, the model was applied to the 29-mer anti-thrombin aptamer as a case study, and an experimental relation between the aptamer-ACE binding strength and performance of DAs was established. The obtained results indicated that our proposed model could accurately describe the effect of the ACE sequence on the performance of the established DAs for thrombin detection, applied for equilibrium assays. Furthermore, to characterize the binding strength between the aptamer and ACEs evaluated in this work, a set of fitting equations was derived which enables thermodynamic characterization of DNA-based interactions through thermal denaturation experiments, thereby overcoming the limitations of current predictive software and chemical denaturation experiments. Altogether, this work encourages the development, characterization, and use of DAs in the field of biosensing.

Abstract: Herein, thin-layer potentiometry combined with ion-exchange membranes as barriers for charged interferences is demonstrated for the analytical detection of creatinine (CRE) in undiluted human urine. Briefly, CRE diffuses through an anion-exchange membrane (AEM) from a sample contained in one fluidic compartment to a second reservoir, containing the enzyme CRE deiminase. There, CRE reacts with the enzyme, and the formation of ammonium is dynamically monitored by potentiometric ammonium-selective electrodes. This analytical concept is integrated into a lab-on-a-chip microfluidic cell that allows for a high sample throughput and the operation under stop-flow mode, which allows CRE to passively diffuse across the AEM. Conveniently, positively charged species (i.e., potassium, sodium, and ammonium, among others) are repelled by the AEM and never reach the ammonium-selective electrodes; thus, possible interference in the response can be avoided. As a result, the dynamic potential response of the electrodes is entirely ascribed to the stoichiometric formation of ammonium. The new CRE biosensor exhibits a Nernstian slope, within a linear range of response from 1 to 50 mM CRE concentration. As expected, the response time (15–60 min) primarily depends on the CRE diffusion across the AEM. CRE analysis in urine samples displayed excellent results, without requiring sample pretreatment (before the introduction of the sample in the microfluidic chip) and with high compatibility with development into a potential point-of-care clinical tool. In an attempt to decrease the analysis time, the presented analytical methodology for CRE detection is translated into an all-solid-state platform, in which the enzyme is immobilized on the surface of the ammonium-selective electrode and with the AEM on top. While more work is necessary in this direction, the CRE sensor appears to be promising for CRE analysis in both urine and blood.

Abstract: We summarize herein the literature in the last decade, involving the use of nanomaterials and various (bio)recognition elements, such as antibodies, aptamers and molecularly imprinted polymers, for the development of sensitive and selective (bio)sensors for illicit drugs with a focus on electrochemical transduction systems. The use and abuse of illicit drugs remains an increasing challenge for worldwide authorities and, therefore, it is important to have accurate methods to detect them in seized samples, biological fluids and wastewaters. They are recently classified as the latest group of “emerging pollutants,” as their consumption has increased tremendously in recent years. Nanomaterials, antibodies, aptamers and molecularly imprinted polymers have gained much attention over the last decade in the development of (bio)sensors for a myriad of applications. The applicability of these (nano)materials, functionalized or not, has significantly increased, and are therefore highly suitable for use in the detection of drugs. Lately, such functionalized nanoscale materials have assisted in the detection of illicit drugs fingerprints, providing large surface area, functional groups and unique properties that facilitate sensitive and selective sensing. The review discusses the types of commonly abused drugs and their toxicological implications, classification of functionalized nanomaterials (graphene, carbon nanotubes), their fabrication, and their application on real samples in different fields of forensic science. Biosensors for drugs of abuse from the last decade's literature are then exemplified. It also offers insights into the prospects and challenges of bringing the functionalized nanobased technology to the end user in the laboratories or in-field.

Abstract: We introduce a simple enhanced sampling approach for the calculation of free energy differences and barriers along a one-dimensional reaction coordinate. First, a small number of short nonequilibrium simulations are carried out along the reaction coordinate, and the Jarzynski equality is used to learn an approximate free energy surface from the nonequilibrium work distribution. This free energy estimate is represented in a compact form as an artificial neural network and used as an external bias potential to accelerate rare events in a subsequent molecular dynamics simulation. The final free energy estimate is then obtained by reweighting the equilibrium probability distribution of the reaction coordinate sampled under the influence of the external bias. We apply our reweighted Jarzynski sampling recipe to four processes of varying scales and complexities.spanning chemical reaction in the gas phase, pair association in solution, and droplet nucleation in supersaturated vapor. In all cases, we find reweighted Jarzynski sampling to be a very efficient strategy, resulting in rapid convergence of the free energy to high precision.