Abstract: Experimental evidence in the literature has shown that low-current direct current nitrogen discharges can exist in both glow and arc regimes at atmospheric pressure. However, modelling investigations of the positive column that include the influence of the cathode phenomena are scarce. In this work we developed a 2D axisymmetric model of a plasma discharge in flowing nitrogen gas, studying the influence of the two cathode emission mechanisms—thermionic field emission and secondary electron emission—on the cathode region and the positive column. We show for an inlet gas flow velocity of 1 m s⁻¹in the current range of 80–160 mA, that the electron emission mechanism from the cathode greatly affects the size and temperature of the cathode region, but does not significantly influence the discharge column at atmospheric pressure. We also demonstrate that in the discharge column the electron density balance is local and the electron production and destruction is dominated by volume processes. With increasing flow velocity, the discharge contraction is enhanced due to the increased convective heat loss. The cross sectional area of the conductive region is strongly dependent on the gas velocity and heat conductivity of the gas.

Abstract: Plasma medicine, or the biomedical application of cold atmospheric plasma (CAP), is an expanding field within plasma research. CAP has demonstrated remarkable versatility in diverse biological applications, including cancer treatment, wound healing, microorganism inactivation, and skin disease therapy. However, the precise mechanisms underlying the effects of CAP remain incompletely understood. The therapeutic effects of CAP are largely attributed to the generation of reactive oxygen and nitrogen species (RONS), which play a crucial role in the biological responses induced by CAP. Specifically, RONS produced during CAP treatment have the ability to chemically modify cell membranes and membrane proteins, causing nitro-oxidative stress, thereby leading to changes in membrane permeability and disruption of cellular processes. To gain atomic-level insights into these interactions, non-reactive molecular dynamics (MD) simulations have emerged as a valuable tool. These simulations facilitate the examination of larger-scale system dynamics, including protein-protein and protein-membrane interactions. In this comprehensive review, we focus on the applications of non-reactive MD simulations in studying the effects of CAP on cellular components and interactions at the atomic level, providing a detailed overview of the potential of CAP in medicine. We also review the results of other MD studies that are not related to plasma medicine but explore the effects of nitro-oxidative stress on cellular components and are therefore important for a broader understanding of the underlying processes.

Abstract: With climate change still a pressing issue, there is a great need for carbon capture, utilisation and storage (CCUS)
methods. We propose a novel concept where CO2 conversion is accomplished by O2 splitting followed by the
addition of O atoms to CO2. The latter is studied here by means of kinetic modelling. In the first instance, we
study various CO2/O ratios, and we observe an optimal CO2 conversion of around 30–40% for 50% O addition.
Gas temperature also has a large influence, with a minimum temperature of around 1000 K to a maximum of
2000 K for optimal conversion. In the second instance, we study various CO2/O/O2 ratios, due to O2 being a
starting gas. Also here we define optimal regions for CO2 conversion, which reach maximum conversion for a
CO2 fraction of 50% and an O/O2 ratio bigger than 1. Those can be expanded by heating on one hand, for low
atomic oxygen availability, and by quenching after reaction on the other hand, for cases where the temperatures
are too high. Our model predictions can serve as a guideline for experimental research in this domain.

Abstract: Transforming CO2 into value-added chemicals is crucial to realizing a carbon–neutral economy, and plasma-based conversion, a Power-2-X technology, offers a promising route to realizing an efficient and scalable process. This paper investigates the effects of post-plasma placement of a converging–diverging nozzle in a vortex-stabilized 2.45 GHz CO2 microwave plasma reactor to increase energy efficiency and conversion. The CDN leads to a 21 % relative increase in energy efficiency (31 %) and CO2 conversion (13 %) at high flow rates and near-atmospheric conditions. The most significant performance improvement was seen at low flow rates and sub-atmospheric pressure (300 mbar), where energy efficiency was 23 % and conversion was 28 %, a 71 % relative increase over conditions without the CDN. Using CFD simulations, we found that the CDN produces a change in the flow geometry, leading to a confined temperature profile at the height of the plasma, and forced extraction of CO to the post-CDN region.

Abstract: Given the ecological problems associated to the CO2 emissions of fossil fuels, plasma technology has gained
interest for conversion of CO2 into value-added products. Microwave plasmas operating at atmospheric pressure
have proven to be especially interesting, due to the high gas temperatures inside the reactor (i.e. up to 6000 K)
allowing for efficient thermal dissociation of CO2 into CO and O2. However, the performance of these high
temperature plasmas is limited by recombination of CO back into CO2 once the gas cools down in the afterglow.
In this work, we computationally investigated several quenching nozzles, developed and experimentally tested
by Hecimovic et al., [1] for their ability to quickly cool the gas after the plasma, thereby quenching the CO
recombination reactions. Using a 3D computational fluid dynamics model and a quasi-1D chemical kinetics
model, we reveal that a reactor without nozzle lacks gas mixing between hot gas in the center and cold gas near
the reactor walls. Especially at low flow rates, where there is an inherent lack of convective cooling due to the
low gas flow velocity, the temperature in the afterglow remains high (between 2000 and 3000 K) for a relatively
long time (in the 0.1 s range). As shown by our quasi-1D chemical kinetics model, this results in a important loss
of CO due to recombination reactions. Attaching a nozzle in the effluent of the reactor induces fast gas quenching
right after the plasma. Indeed, it introduces (i) more convective cooling by forcing cool gas near the walls to mix
with hot gas in the center of the reactor, as well as (ii) more conductive cooling through the water-cooled walls of
the nozzle. Our model shows that gas quenching and the suppression of recombination reactions have more
impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: Plasma-catalytic dry reforming of CH4 (DRM) is promising to convert the greenhouse gasses CH4 and CO2 into value-added chemicals, thus simultaneously providing an alternative to fossil resources as feedstock for the chemical industry. However, while many experiments have been dedicated to plasma-catalytic DRM, there is no consensus yet in literature on the optimal choice of catalyst for targeted products, because the underlying mechanisms are far from understood. Indeed, plasma catalysis is very complex, as it encompasses various chemical and physical interactions between plasma and catalyst, which depend on many parameters. This complexity hampers the comparison of experimental results from different studies, which, in our opinion, is an important bottleneck in the further development of this promising research field. Hence, in this perspective paper, we describe the important physical and chemical effects that should be accounted for when designing plasma-catalytic experiments in general, highlighting the need for standardized experimental setups, as well as careful documentation of packing properties and reaction conditions, to further advance this research field. On the other hand, many parameters also create many windows of opportunity for further optimizing plasma-catalytic systems. Finally, various experiments also reveal the lack of improvement in plasma catalysis compared to plasma-only, specifically for DRM, but the underlying mechanisms are unclear. Therefore, we present our newly developed coupled plasma-surface kinetics model for DRM, to provide more insight in the underlying reasons. Our model illustrates that transition metal catalysts can adversely affect plasmacatalytic DRM, if radicals dominate the plasma-catalyst interactions. Thus, we demonstrate that a good understanding of the plasma-catalyst interactions is crucial to avoiding conditions at which these interactions negatively affect the results, and we provide some recommendations for improvement. For instance, we believe that plasma-catalytic DRM may benefit more from higher reaction temperatures, at which vibrational excitation can enhance the surface reactions.

Abstract: Structured waves are ubiquitous for all areas of wave physics, both classical and quantum, where the wavefields are inhomogeneous and cannot be approximated by a single plane wave. Even the interference of two plane waves, or of a single inhomogeneous (evanescent) wave, provides a number of nontrivial phenomena and additional functionalities as compared to a single plane wave. Complex wavefields with inhomogeneities in the amplitude, phase, and polarization, including topological----- structures and singularities, underpin modern nanooptics and photonics, yet they are equally important, e.g. for quantum matter waves, acoustics, water waves, etc. Structured waves are crucial in optical and electron microscopy, wave propagation and scattering, imaging, communications, quantum optics, topological and non-Hermitian wave systems, quantum condensed-matter systems, optomechanics, plasmonics and metamaterials, optical and acoustic manipulation, and so forth. This Roadmap is written collectively by prominent researchers and aims to survey the role of structured waves in various areas of wave physics. Providing background, current research, and anticipating future developments, it will be of interest to a wide cross-disciplinary audience.

Abstract: This study presents new insights on the effect of (sub)micrometer particle sized materials in plasma-based CO2-
CH4 reforming by investigating the performance of SiO2 spheres (with/without supported metal) of varying
particle sizes. (Sub)micron particles synthesized through the St¨ober method were used instead of (sub)millimeter
particles employed in previous studies. Increasing particle size (from 120 nm to 2390 nm) was found to first
increase and then decrease conversion and energy yield, with optimal performance achieved using 740 nm 5 wt%
Ni loaded SiO2, which improved CO2 and CH4 conversion, and energy yield to 44%, 55%, and 0.271 mmol/kJ,
respectively, compared to 20%, 27%, and 0.116 mmol/kJ in an empty reactor at the same flow rate. This is the
first to achieve significant performance improvement in a fully packed reactor, highlighting the importance of
selecting a suitable particle size. The findings can offer guidance towards rational design of catalysts for plasmabased
reactions.

Abstract: Among oxides, bismuthates have been gaining much interest due to their unique features. In addition to their superconducting properties, they show potential for applications as topological insulators and as possible spin-to-charge converters. After being first investigated in their bulk form in the 1980s, bismuthates have been successfully grown as thin films. However, most efforts have focused on BaBiO₃, with SrBiO₃receiving only little attention. Here, we report the growth of epitaxial films of SrBiO₃on both TiO₂-terminated SrTiO₃and NdO-terminated NdScO₃substrates by pulsed laser deposition. SrBiO₃has a pseudocubic lattice constant of ∼4.25 Å and grows relaxed on NdScO₃. Counter-intuitively, it grows with a slight tensile strain on SrTiO₃despite a large lattice mismatch, which should induce compressive strain. High-resolution transmission electron microscopy reveals that this occurs as a consequence of structural domain matching, with blocks of 10 SrBiO₃unit planes matching blocks of 11 SrTiO₃unit planes. This work provides a framework for the synthesis of high quality perovskite bismuthates films and for the understanding of their interface interactions with homostructural substrates.

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: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Abstract: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

Abstract: Electron tomography is essential for investigating the three-dimensional (3D) structure of nanomaterials. However, many of these materials, such as metal-organic frameworks (MOFs), are extremely sensitive to electron radiation, making it difficult to acquire a series of projection images for electron tomography without inducing electron-beam damage. Another significant challenge is the high contrast in high-angle annular dark field scanning transmission electron microscopy that can be expected for nanocomposites composed of a metal nanoparticle and an MOF. This strong contrast leads to so-called metal artifacts in the 3D reconstruction. To overcome these limitations, we here present low-dose electron tomography based on four-dimensional scanning transmission electron microscopy (4D-STEM) data sets, collected using an ultrafast and highly sensitive direct electron detector. As a proof of concept, we demonstrate the applicability of the method for an Au nanostar embedded in a ZIF-8 MOF, which is of great interest for applications in various fields, including drug delivery.

Abstract: Despite the natural abundance and promising properties of Si, there are few examples of crystalline Si-based catalysts. Here, the authors report an epitaxial growth method to construct Co single atoms on Si for light driven CO2 reduction to syngas. Improving the dispersion of active sites simultaneous with the efficient harvest of photons is a key priority for photocatalysis. Crystalline silicon is abundant on Earth and has a suitable bandgap. However, silicon-based photocatalysts combined with metal elements has proved challenging due to silicon's rigid crystal structure and high formation energy. Here we report a solid-state chemistry that produces crystalline silicon with well-dispersed Co atoms. Isolated Co sites in silicon are obtained through the in-situ formation of CoSi2 intermediate nanodomains that function as seeds, leading to the production of Co-incorporating silicon nanocrystals at the CoSi2/Si epitaxial interface. As a result, cobalt-on-silicon single-atom catalysts achieve an external quantum efficiency of 10% for CO2-to-syngas conversion, with CO and H-2 yields of 4.7 mol g((Co))(-1) and 4.4 mol g((Co))(-1), respectively. Moreover, the H-2/CO ratio is tunable between 0.8 and 2. This photocatalyst also achieves a corresponding turnover number of 2 x 10(4) for visible-light-driven CO2 reduction over 6 h, which is over ten times higher than previously reported single-atom photocatalysts.

Abstract: In recent years, quantum dots (QDs) have emerged as bright,color-tunablelight sources for various applications such as light-emitting devices,lasing, and bioimaging. One important next step to advance their applicabilityis to reduce particle-to-particle variations of the emission propertiesas well as fluctuations of a single QD's emission spectrum,also known as spectral diffusion (SD). Characterizing SD is typicallyinefficient as it requires time-consuming measurements at the single-particlelevel. Here, however, we demonstrate multiparticle spectroscopy (MPS)as a high-throughput method to acquire statistically relevant informationabout both fluctuations at the single-particle level and variationsat the level of a synthesis batch. In MPS, we simultaneously measureemission spectra of many (20-100) QDs with a high time resolution.We obtain statistics on single-particle emission line broadening fora batch of traditional CdSe-based core-shell QDs and a batchof the less toxic InP-based core-shell QDs. The CdSe-basedQDs show significantly narrower homogeneous line widths, less SD,and less inhomogeneous broadening than the InP-based QDs. The timescales of SD are longer in the InP-based QDs than in the CdSe-basedQDs. Based on the distributions and correlations in single-particleproperties, we discuss the possible origins of line-width broadeningof the two types of QDs. Our experiments pave the way to large-scale,high-throughput characterization of single-QD emission propertiesand will ultimately contribute to facilitating rational design offuture QD structures.