Abstract: The rate, selectivity and efficiency of plasma-based conversion processes is strongly affected by nonequilibrium phenomena. High concentrations of vibrationally excited molecules are such a plasma-induced effect. It is frequently assumed that vibrationally excited molecules are important in plasma catalysis because their presence lowers the apparent activation energy of dissociative chemisorption reactions and thus increases the conversion rate. A detailed atomic-level understanding of vibrationally stimulated catalytic reactions in the context of plasma catalysis is however lacking. Here, we couple a recently developed statistical model of a plasma-induced vibrational nonequilibrium to molecular dynamics simulations, enhanced sampling methods, and machine learning techniques. We quantify the impact of a vibrational nonequilibrium on the dissociative chemisorption barrier of H2 and CH4 on nickel catalysts over a wide range of vibrational temperatures. We investigate the effect of surface structure and compare the role of different vibrational modes of methane in the dissociation process. For low vibrational temperatures, very high vibrational efficacies are found, and energy in bend vibrations appears to dominate the dissociation of methane. The relative impact of vibrational nonequilibrium is much higher on terrace sites than on surface steps. We then show how our simulations can help to interpret recent experimental results, and suggest new paths to a better understanding of plasma catalysis.

Abstract: A pulsed microwave surfaguide discharge operating at 2.45 GHz was used for the conversion of molecular nitrogen into valuable compounds in several gas mixtures: N2 :O2 , N2 :O2 :CO2 and N2 :CO2 . The ro-vibrational absorption bands of the molecular species were monitored by a Fourier transform infrared apparatus in the post-discharge region in order to evaluate the relative number density of species, specifically NO production. The effects of specific energy input, pulse frequency, gas flow fraction, gas admixture and gas flow rate were studied for better understanding and optimization of the NO production yield and the corresponding energy cost (EC). By both the experiment and modelling, a highest NO yield is obtained at N2 :O2 (1:1) gas ratio in N2 :O2 mixture. The NO yield reveals a small growth followed by saturation when pulse repetition frequency increases. The energy efficiency start decreasing after the energy input reaches about 5 eV/molec, whereas the NO yield rises steadily at the same time. The lowest EC of about 8 MJ mol−1 corresponding to the yield and the energy efficiency of about 7% and 1% are found, respectively, in an optimum discharge condition in our case.

Abstract: Dielectric barrier discharges (DBDs) typically operate in the filamentary regime and thus exhibit great spatial and temporal non-uniformity. In order to optimize DBDs for various applications, such as in plasma catalysis, more fundamental insight is needed. Here, we consider how the millions of microdischarges, characteristic for a DBD, influence individual gas molecules. We use a Monte Carlo approach to determine the number of microdischarges to which a single molecule would be exposed, by means of particle tracing simulations through a full-scale packed bed DBD reactor, as well as an empty DBD reactor. We find that the fraction of microdischarges to which the molecules are exposed can be approximated as the microdischarge volume over the entire reactor gas volume. The use of this concept provides good agreement between a plasma-catalytic kinetics model and experiments for plasma-catalytic NH3 synthesis. We also show that the concept of the fraction of microdischarges indicates the efficiency by which the plasma power is transferred to the gas molecules. This generalised concept is also applicable for other spatially and temporally non-uniform plasmas.

Abstract: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.

Abstract: In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity.

Abstract: This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale.

Abstract: In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities.

Abstract: A growing body of literature has recognized the non-thermal effect of pulsed microwave radiation (PMR) on bacterial systems. However, its mode of action in deactivating bacteria has not yet been extensively investigated. Nevertheless, it is highly important to advance the applications of PMR from simple to complex biological systems. In this study, we first optimized the conditions of the PMR device and we assessed the results by simulations, using ANSYS HFSS (High Frequency Structure Simulator) and a 3D particle-in-cell code for the electron behavior, to provide a better overview of the bacterial cell exposure to microwave radiation. To determine the sensitivity of PMR,<italic>Escherichia coli</italic> and<italic>Staphylococcus aureus</italic>cultures were exposed to PMR (pulse duration: 60 ns, peak frequency: 3.5 GHz) with power density of 17 kW/cm²at the free space of sample position, which would induce electric field of 8.0 kV/cm inside the PBS solution of falcon tube in this experiment at 25 °C. At various discharges (D) of microwaves, the colony forming unit curves were analyzed. The highest ratios of viable count reductions were observed when the doses were increased from 20D to 80D, which resulted in an approximate 6 log reduction in <italic>E. coli</italic>and 4 log reduction in<italic>S. aureus.</italic>Moreover, scanning electron microscopy also revealed surface damage in both bacterial strains after PMR exposure. The bacterial inactivation was attributed to the deactivation of oxidation-regulating genes and DNA damage.

Abstract: The spatiotemporal dynamics of volume and surface positive and negative streamers in a pintoplate volume dielectric barrier discharge is investigated in this study. The discharge characteristics are found to be completely different for positive and negative streamers. First, the spatial propagation of a positive streamer is found to rely on electron avalanches caused by photo-electrons in front of the streamer head, whereas this is not the case for negative streamers. Second, our simulations reveal an interesting phenomenon of floating positive surface discharges, which develop when a positive streamer reaches a dielectric wall and which explain the experimentally observed branching characteristics. Third, we report for the first time, the interactions between a positive streamer and dielectric pores, in which both the pore diameter and depth affect the evolution of a positive streamer.

Abstract: The (photo)catalytic properties of metal–organic frameworks (MOFs) can be enhanced by post-synthetic inclusion of metallic species in their porosity. Due to their extraordinarily high surface area and well defined porous structure, MOFs can be used for the stabilization of metal nanoparticles with adjustable size within their porosity. Originally, we present here an optimized ultrafast photoreduction protocol for the<italic>in situ</italic>synthesis of tiny and monodisperse silver nanoclusters (AgNCs) homogeneously supported on a photoactive porous titanium carboxylate MIL-125-NH₂MOF. The strong metal–framework interaction between –NH₂and Ag atoms influences the AgNC growth, leading to the surfactant-free efficient catalyst AgNC@MIL-125-NH₂with improved visible light absorption. The potential use of AgNC@MIL-125-NH₂was further tested in challenging applications: (i) the photodegradation of the emerging organic contaminants (EOCs) methylene blue (MB-dye) and sulfamethazine (SMT-antibiotic) in water treatment, and (ii) the catalytic hydrogenation of<italic>p</italic>-nitroaniline (4-NA) to<italic>p</italic>-phenylenediamine (PPD) with industrial interest. It is noteworthy that compared with the pristine MIL-125-NH₂, the composite presents an improved catalytic activity and stability, being able to photodegrade 92% of MB in 60 min and 96% of SMT in 30 min, and transform 100% of 4-NA to PPD in 30 min. Aside from these very good results, this study describes for the first time the use of a MOF in a visible light continuous flow reactor for wastewater treatment. With only 10 mg of AgNC@MIL-125-NH₂, high SMT removal efficiency over 70% is maintained after >2 h under water flow conditions found in real wastewater treatment plants, signaling a future real application of MOFs in water remediation.

Abstract: N2 fixation into NH3 is one of the main processes in the chemical industry. Plasma catalysis is among the environmentally friendly alternatives to the industrial energy-intensive Haber-Bosch process. However, many questions remain open, such as the applicability of the conventional catalytic knowledge to plasma. In this work, we studied the performance of Al2O3-supported Fe, Ru, Co and Cu catalysts in plasma-catalytic NH3 synthesis in a DBD reactor. We investigated the effects of different active metals, and different ratios of the feed gas components, on the concentration and production rate of NH3, and the energy consumption of the plasma system. The results show that the trend of the metal activity (common for thermal catalysis) does not appear in the case of plasma catalysis: here, all metals exhibited similar performance. These findings are in good agreement with our recently published microkinetic model. This highlights the virtual independence of NH3 production on the metal catalyst material, thus validating the model and indicating the potential contribution of radical adsorption and Eley-Rideal reactions to the plasma-catalytic mechanism of NH3 synthesis.

Abstract: Plasma catalysis is an emerging new technology for the electrification and downscaling of NH3 synthesis. Increasing attention is being paid to the optimization of plasma catalysis with respect to the plasma conditions, the catalyst material, and their mutual interaction. In this work we use microkinetic models to study how the total conversion process is impacted by the combination of different plasma conditions and transition metal catalysts. We study how plasma-generated radicals and vibrationally excited N2 (present in a dielectric barrier discharge plasma) interact with the catalyst and impact the NH3 turnover frequencies (TOFs). Both filamentary and uniform plasmas are studied, based on plasma chemistry models that provided plasma phase speciation and vibrational distribution functions. The Langmuir−Hinshelwood reaction rate coefficients (i.e., adsorption reactions and subsequent reactions among adsorbates) are determined using conventional scaling relations. An additional set of Eley−Rideal reactions (i.e., direct reactions of plasma radicals with adsorbates) was added and a sensitivity analysis on the assumed reaction rate coefficients was performed. We first show the impact of different vibrational distribution functions on the catalytic dissociation of N2 and subsequent production of NH3, and we gradually include more radical reactions, to illustrate the contribution of these species and their corresponding reaction pathways. Analysis over a large range of catalysts indicates that different transition metals (metals such as Rh, Ni, Pt, and Pd) optimize the NH3TOFs depending on the population of the vibrational levels of N2. At higher concentrations of plasma-generated radicals, the NH3 TOFs become less dependent on the catalyst material, due to radical adsorptions on the more noble catalysts and Eley−Rideal reactions on the less noble catalysts.

Abstract: The physics and chemistry of plasma–surface interaction is a broad domain relevant to various applications and several natural processes, including plasma etching for microelectronics fabrication, plasma deposition, surface functionalization, nanomaterial synthesis, fusion reactors, and some astrophysical and meteorological phenomena. Due to their complex nature, each of these processes is generally investigated in separate subdomains, which are considered to have their own theoretical, modeling, and experimental challenges. In this review, however, we want to emphasize the overarching nature of plasma–surface interaction physics and chemistry, by focusing on the general strategy for its computational simulation. In the first half of the review, we provide a menu card with standard and less standardized computational methods to be used for the multiscale modeling of the underlying processes. In the second half, we illustrate the benefits and potential of the multiscale modeling strategy with a case study of Si and SiO2 etching by fluorocarbon plasmas and identify the gaps in knowledge still present on this intensely investigated plasma–material combination, both on a qualitative and quantitative level. Remarkably, the dominant etching mechanisms remain the least understood. The resulting new insights are of general relevance, for all plasmas and materials, including their various applications. We therefore hope to motivate computational and experimental scientists and engineers to collaborate more intensely on filling the existing gaps in knowledge. In this way, we expect that research will overcome a bottleneck stage in the development and optimization of multiscale models, and thus the fundamental understanding of plasma–surface interaction.

Abstract: Lead halide perovskites have been widely explored
in the field of photovoltaics, light-emitting diodes, and lasers due to
their outstanding linear and nonlinear optical (NLO) properties.
But, the presence of lead toxicity and low chemical stability remain
serious concerns. Lead-free double perovskite with excellent
optical properties and chemical stability could be an alternative.
However, proper examination of the NLO properties of such a
material is crucial to identify their utility for future nonlinear device
applications. Herein, we have made use of femtosecond (fs) Z-scan
technique to explore the NLO properties of Cs2AgIn0.9Bi0.1Cl6
nanocrystals (NCs). Our measurements suggest that under
nonresonant fs excitation, perovskite NCs exhibit strong twophoton
absorption (TPA). The observed saturation of TPA at high
light intensities has been explained by a customized model. Furthermore, we have demonstrated a change in the nonlinear refractive
index of the NCs under varying input intensities. The strong TPA absorption of lead-free double perovskite NCs could be used for
Kerr nonlinearity-based nonlinear applications such as optical shutters for picosecond lasers.