Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.

Abstract: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

Abstract: Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification. ,

Abstract: Accurate barriers for rate controlling elementary reactions on metal surfaces are key to understanding, controlling, and predicting the rate of heterogeneously catalyzed processes. While barrier heights for gas phase reactions have been extensively benchmarked, dissociative chemisorption barriers for the reactions of molecules on metal surfaces have received much less attention. The first database called SBH10 and containing 10 entries was recently constructed based on the specific reaction parameter approach to density functional theory (SRP-DFT) and experimental results. We have now constructed a new and improved database (SBH17) containing 17 entries based on SRP-DFT and experiments. For this new SBH17 benchmark study, we have tested three algorithms (high, medium, and light) for calculating barrier heights for dissociative chemisorption on metals, which we have named for the amount of computational effort involved in their use. We test the performance of 14 density functionals at the GGA, GGA+vdW-DF, and meta-GGA rungs. Our results show that, in contrast with the previous SBH10 study where the BEEF-vdW-DF2 functional seemed to be most accurate, the workhorse functional PBE and the MS2 density functional are the most accurate of the GGA and meta-GGA functionals tested. Of the GGA+vdW functionals tested, the SRP32-vdW-DF1 functional is the most accurate. Additionally, we found that the medium algorithm is accurate enough for assessing the performance of the density functionals tested, while it avoids geometry optimizations of minimum barrier geometries for each density functional tested. The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. While these are avoided in the light algorithm, this algorithm is found not to give a reliable description of functional performance. The combination of relative ease of use and demonstrated reliability of the medium algorithm will likely pave the way for incorporation of the SBH17 database in larger databases used for testing new density functionals and electronic structure methods.

Abstract: Catalysis science and technology increased efforts recently to progress beyond conventional “thermal” catalysis and face the challenges of net-zero emissions and electrification of production. Nevertheless, a better gaps and opportunities analysis is necessary. This review analyses four emerging areas of unconventional or less- conventional catalysis which share the common aspect of using directly renewable energy sources: (i) plasma catalysis, (ii) catalysis for flow chemistry and process intensification, (iii) application of electromagnetic (EM) fields to modulate catalytic activity and (iv) nanoscale generation at the catalyst interface of a strong local EM by plasmonic effect. Plasma catalysis has demonstrated synergistic effects, where the outcome is higher than the sum of both processes alone. Still, the underlying mechanisms are complex, and synergy is not always obtained. There is a crucial need for a better understanding to (i) design catalysts tailored to the plasma environment, (ii) design plasma reactors with optimal transport of plasma species to the catalyst surface, and (iii) tune the plasma conditions so they work in optimal synergy with the catalyst. Microfluidic reactors (flow chemistry) is another emerging sector leading to the intensification of catalytic syntheses, particularly in organic chemistry. New unconventional catalysts must be designed to exploit in full the novel possibilities. With a focus on (a) continuous-flow photocatalysis, (b) electrochemical flow catalysis, (c) microwave flow catalysis and (d) ultra­ sound flow activation, a series of examples are discussed, with also indications on scale-up and process indus­ trialisation. The third area discussed regards the effect on catalytic performances of applying oriented EM fields spanning several orders of magnitude. Under well-defined conditions, gas breakdown and, in some cases, plasma formation generates activated gas phase species. The EM field-driven chemical conversion processes depend further on structured electric/magnetic catalysts, which shape the EM field in strength and direction. Different effects influencing chemical conversion have been reported, including reduced activation energy, surface charging, hot spot generation, and selective local heating. The last topic discussed is complementary to the third, focusing on the possibility of tuning the photo- and electro-catalytic properties by creating a strong localised electrical field with a plasmonic effect. The novel possibilities of hot carriers generated by the plasmonic effect are also discussed. This review thus aims to stimulate the reader to make new, creative catalysis to address the challenges of reaching a carbon-neutral world.

Abstract: Theoretical studies on molecule-metal surface reactions have so far been limited to small surface unit cells due to computational costs. Here, for the first time molecular dynamics simulations on very large surface unit cells at the level of density functional theory are performed, allowing a direct comparison to experiments performed on a curved crystal. Specifically, the reaction of D-2 on a curved Pt crystal is investigated with a neural network potential (NNP). The developed NNP is also accurate for surface unit cells considerably larger than those that have been included in the training data, allowing dynamical simulations on very large surface unit cells that otherwise would have been intractable. Important and complex aspects of the reaction mechanism are discovered such as diffusion and a shadow effect of the step. Furthermore, conclusions from simulations on smaller surface unit cells cannot always be transfered to larger surface unit cells, limiting the applicability of theoretical studies of smaller surface unit cells to heterogeneous catalysts with small defect densities.

Abstract: Immobilization of single metal atoms on a solid host opens numerous possibilities for catalyst designs. If that host is a two-dimensional sheet, sheet curvature becomes a design parameter potentially complementary to host and metal composition. Here, we use a combination of density functional theory calculations and microkinetic modeling to compare the mechanisms and kinetics of formic acid decomposition and formation, chosen for their relevance as a potential hydrogen storage medium, over single Ru atoms anchored to pyridinic nitrogen in a planar graphene flake (RuN4-G) and curved carbon nanotube (RuN4-CNT). Activation barriers are lowered and the predicted turnover frequencies are increased over RuN4-CNT relative to RuN4-CNT. The results highlight the potential of curvature control as a means to achieve high performance and robust catalysts.

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

Abstract: Packed-bed DBD (PB-DBD) plasmas hold promise for effective degradation of greenhouse gases like SF6. In this work, we conducted a combined experimental and theoretical study to investigate the effect of the packing surface structure and the plasma surface discharge on the SF6 degradation in a gamma-Al2O3 packing DBD system. Experimental results show that both the hydration effect of the surface (upon moisture) and the presence of excessive reactive gases in the plasma can significantly reduce the SF6 degradation, but they hardly change the discharge behavior. DFT results show that the pre-adsorption of species such as H, OH, H2O and O-2 can occupy the active sites (Al-III site) which negatively impacts the SF6 adsorption. H2O molecules pre-adsorbed at neighboring sites can promote the activation of SF6 molecules and lower the reaction barrier for the S-F bond-breaking process. Surface-induced charges and local external electric fields caused by the plasma can both improve the SF6 adsorption and enhance the elongation of the S-F bonds. Our results indicate that both the surface structure of the packing material and the plasma surface discharge are crucial for SF6 degradation performance, and the packing beads should be kept dry during the degradation. This work helps to understand the underlying mechanisms of SF6 degradation in a PB-DBD system.

Abstract: e investigate atmospheric pressure microwave (MW) plasma (2.45 GHz) conversion in CO2 and CH4 mixtures (i.e., dry reforming of methane, DRM) focusing on reaction performance and carbon formation. Promising energy costs of ~2.8–3.0 eV/molecule or ~11.1–11.9 kJ/L are amongst the best performance to date considering the current state-of-the-art for plasma-based DRM for all types of plasma. The conversion is in the range of ~46–49% and ~55–67% for CO2 and CH4, respectively, producing primarily syngas (i.e., H2 and CO) with H2/CO ratios of ~0.6–1 at CH4 fractions ranging from 30% to 45%. Water is the largest byproduct with levels ranging ~7–14% in the exhaust. Carbon particles visibly impact the plasma at higher CH4 fractions (> 30%), where they become heated and incandescent. Particle luminosity increases with increasing CH4 fractions, with the plasma becoming unstable near a 1:1 mixture (i.e., > 45% CH4). Electron microscopy of the carbon material reveals an agglomerated morphology of pure carbon nanoparticles. The mean particle size is determined as ~20 nm, free of any metal contamination, consistent with the electrode-less MW design.

Abstract: We studied the plasma-catalytic production of NH3 from H2 and N2 in a dielectric barrier discharge plasma reactor using five different Co-based catalysts supported on Al2O3, namely Co/Al2O3, CoCe/Al2O3, CoLa/Al2O3, CoCeLa/Al2O3 and CoCeMg/Al2O3. The catalysts were characterized via several techniques, including SEM-EDX, and their performance was compared. The best performing catalyst was found to be CoLa/Al2O3, but the dif-ferences in NH3 concentration, energy consumption and production rate between the different catalysts were limited under the same conditions (i.e. feed gas, flow rate and ratio, and applied power). At the same time, the plasma properties, such as the plasma power and current profile, varied significantly depending on the catalyst. Taken together, these findings suggest that in the production of NH3 by plasma catalysis, our catalysts act as plasma modifiers, i.e., they change the discharge properties and hence the gas phase plasma chemistry. Importantly, this effect dominates over the direct catalytic effect (as e.g. in thermal catalysis) defined by the chemistry on the catalyst surface.

Abstract: A gliding arc plasmatron (GAP), which is very promising for purification and gas conversion,
is characterized in nitrogen using optical emission spectroscopy and high-speed photography,
because the cross sections of electron impact excitation of N 2 are well known. The gas
temperature (of about 5500 K), the electron density (up to 1.5 × 10 15 cm −3 ) and the reduced
electric field (of about 37 Td) are determined using an absolutely calibrated intensified charge-
coupled device (ICCD) camera, equipped with an in-house made optical arrangement for
simultaneous two-wavelength diagnostics, adapted to the transient behavior of a GA channel
in turbulent gas flow. The intensities of nitrogen molecular emission bands, N 2 (C–B,0–0) as
well as N +
2 (B–X,0–0), are measured simultaneously. The electron density and the reduced
electric field are determined at a spatial resolution of 30 µm, using numerical simulation and
measured emission intensities, applying the Abel inversion of the ICCD images. The temporal
behavior of the GA plasma channel and the formation of plasma plumes are studied using a
high-speed camera. Based on the determined plasma parameters, we suggest that the plasma
plume formation is due to the magnetization of electrons in the plasma channel of the GAP by
an axial magnetic field in the plasma vortex.

Abstract: In order to optimize the plasma-synthesis and modification process of carbon nanomaterials for applications such as nanoelectronics and energy storage, a deeper understanding of fundamental hydrogengraphite/graphene interactions is required. Atomistic simulations by Molecular Dynamics have proven to be indispensable to illuminate these phenomena. However, severe time-scale limitations restrict them to very fast processes such as reflection, while slow thermal processes such as surface diffusion and molecular desorption are commonly inaccessible. In this work, we could however reach these thermal processes for the first time at time-scales and surface temperatures (1000 K) similar to high-flux plasma exposure experiments during the simulation of multilayer graphene etching by 5 eV H ions. This was achieved by applying the Collective Variable-Driven Hyperdynamics biasing technique, which extended the inter-impact time over a range of six orders of magnitude, down to a more realistic ion-flux of 1023m
2s
1. The results show that this not only causes a strong shift from predominant ion-to thermally induced interactions, but also significantly affects the hydrogen uptake and surface evolution. This study thus elucidates H ion-graphite/graphene interaction mechanisms and stresses the importance of including long time-scales in atomistic simulations at high surface temperatures to understand the dynamics of the ion-surface system.

Abstract: Plasma is gaining increasing interest for cancer
treatment, but the underlying mechanisms are not yet fully
understood. Using computer simulations at the molecular
level, we try to gain better insight in how plasma-generated
reactive oxygen and nitrogen species (RONS) can
penetrate through the cell membrane. Specifically, we
compare the permeability of various (hydrophilic and
hydrophobic) RONS across both oxidized and nonoxidized cell membranes. We also study pore formation,
and how it is hampered by higher concentrations of
cholesterol in the cell membrane, and we illustrate the
much higher permeability of H2O2 through aquaporin
channels. Both mechanisms may explain the selective
cytotoxic effect of plasma towards cancer cells. Finally, we
also discuss the synergistic effect of plasma-induced
oxidation and electric fields towards pore formation.
Keywords plasma medicine, cancer treatment, computer
modelling, cell membrane, reactive oxygen and nitrogen
species

Abstract: Plasma technology is gaining increasing interest for CO2 conversion, but to maximize the energy efficiency, it is important to track the different energy transfers taking place in the plasma. In this paper, we study these mechanisms by a 0D chemical kinetics model, including the vibrational kinetics, for different conditions of reduced electric field, gas temperature and ionization degree, at a pressure of 100 mbar. Our model predicts a maximum conversion and energy efficiency of 32% and 47%, respectively, at conditions that are particularly beneficial for energy efficient CO2 conversion, i.e. a low reduced electric field (10 Td) and a low gas temperature (300 K). We study the effect of the efficiency by which the vibrational energy is used to dissociate CO2, as well as of the activation energy of the reaction CO2+O→CO+O2, to elucidate the theoretical limitations to the energy
efficiency. Our model reveals that these parameters are mainly responsible for the limitations in the energy efficiency. By varying these parameters, we can reach a maximum conversion and energy efficiency of 86%. Finally, we derive an empirical formula to estimate the maximum possible energy efficiency that can be reached under the assumptions of the model.