Abstract: Direct conversion of CH4 and CO2 to liquid fuels and chemicals under mild conditions is appealing for biogas conversion and utilization but challenging due to the inert nature of both gases. Herein, we report a promising plasma process for the catalyst-free single-step conversion of CH4 and CO2 into higher value oxygenates (i.e., methanol, acetic acid, ethanol, and acetone) at ambient pressure and room temperature using a water-cooled dielectric barrier discharge (DBD) reactor, with methanol being the main liquid product. The distribution of liquid products could be tailored by tuning the discharge power, reaction temperature and residence time. Lower discharge powers (10–15 W) and reaction temperatures (5–20 ◦ C) were favourable for the production of liquid products, achieving the highest methanol selectivity of 43% at 5 ◦ C and 15 W. A higher discharge power and reaction temperature, on the other hand, produced more gaseous products, particularly H2 (up to 26% selec­tivity) and CO (up to 33% selectivity). In addition, varying these process parameters (discharge power, reaction temperature and residence time) resulted in a simultaneous change in key discharge properties, such as mean electron energy (Ee), electron density (ne) and specific energy input (SEI), all of which are essential determiners of plasma chemical reactions. According to the results of artificial neural network (ANN) models, the relative importance of these process parameters and key discharge indicators on reaction performance follows the order: discharge power > reaction temperature > residence time, and SEI > ne > Ee, respectively. This work provides new insights into the contributions and tuning mechanism of multiple parameters for optimizing the reaction performance (e.g., liquid production) in the plasma gas conversion process.

Abstract: Carbon nanotubes (CNTs) are nowadays routinely grown in a thermal CVD setup. State-of-the-art plasma-enhanced CVD (PECVD) growth, however, offers advantages over thermal CVD. A lower growth temperature and the growth of aligned freestanding single-walled CNTs (SWNTs) makes the technique very attractive. The atomic scale growth mechanisms of PECVD CNT growth, however, remain currently entirely unexplored. In this contribution, we employed molecular dynamics simulations to focus on the effect of applying an electric field on the SWNT growth process, as one of the effects coming into play in PECVD. Using sufficiently strong fields results in (a) alignment of the growing SWNTs, (b) a better ordering of the carbon network, and (c) a higher growth rate relative to thermal growth rate. We suggest that these effects are due to the small charge transfer occurring in the Ni/C system. These simulations constitute the first study of PECVD growth of SWNTs on the atomic level.

Abstract: Discrete electron tomography is a new approach for three-dimensional reconstruction of nanoscale objects. The technique exploits prior knowledge of the object to be reconstructed, which results in an improvement of the quality of the reconstructions. Through the combination of conventional transmission electron microscopy and discrete electron tomography with a model-based approach, quantitative structure determination becomes possible. In the present work, this approach is used to unravel the building scheme of Zeotile-4, a silica material with two levels of structural order. The layer sequence of slab-shaped building units could be identified. Successive layers were found to be related by a rotation of 120°, resulting in a hexagonal space group. The Zeotile-4 material is a demonstration of the concept of successive structuring of silica at two levels. At the first level, the colloid chemical properties of Silicalite-1 precursors are exploited to create building units with a slablike geometry. At the second level, the slablike units are tiled using a triblock copolymer to serve as a mesoscale structuring agent.

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: 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: This paper brings the comparison of performances of CO2 conversion by plasma and plasma-assisted catalysis based on the data collected from literature in this field, organised in an open access online data-base. This tool is open to all users to carry out their own analyses, but also to contributors who wish to add their data to the database in order to improve the relevance of the comparisons made, and ultimately to improve the efficiency of CO2 conversion by plasma-catalysis. The creation of this database and data-base user interface is motivated by the fact that plasma-catalysis is a fast-growing field for all CO2 con-version processes, be it methanation, dry reforming of methane, methanolisation, or others. As a result of this rapid increase, there is a need for a set of standard procedures to rigorously compare performances of different systems. However, this is currently not possible because the fundamental mechanisms of plasma-catalysis are still too poorly understood to define these standard procedures. Fortunately how-ever, the accumulated data within the CO2 plasma-catalysis community has become large enough to war-rant so-called “big data” studies more familiar in the fields of medicine and the social sciences. To enable comparisons between multiple data sets and make future research more effective, this work proposes the first database on CO2 conversion performances by plasma-catalysis open to the whole community. This database has been initiated in the framework of a H2020 European project and is called the “PIONEER DataBase”. The database gathers a large amount of CO2 conversion performance data such as conversion rate, energy efficiency, and selectivity for numerous plasma sources coupled with or without a catalyst. Each data set is associated with metadata describing the gas mixture, the plasma source, the nature of the catalyst, and the form of coupling with the plasma. Beyond the database itself, a data extraction tool with direct visualisation features or advanced filtering functionalities has been developed and is available online to the public. The simple and fast visualisation of the state of the art puts new results into context, identifies literal gaps in data, and consequently points towards promising research routes. More advanced data extraction illustrates the impact that the database can have in the understanding of plasma-catalyst coupling. Lessons learned from the review of a large amount of literature during the setup of the database lead to best practice advice to increase comparability between future CO2 plasma-catalytic studies. Finally, the community is strongly encouraged to contribute to the database not only to increase the visibility of their data but also the relevance of the comparisons allowed by this tool. (c) 2023 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. This is an open access article under the CC BY license (http://creati- vecommons.org/licenses/by/4.0/).

Abstract: Plasma-catalytic CO, hydrogenation for methanol production is gaining increasing interest, but our understanding of its reaction mechanism remains primitive. We present a combined experimental/computational study on plasma-catalytic CO, hydrogenation to CH3OH over a size-selected Cu/gamma-Al2O3 catalyst. Our experiments demonstrate a synergistic effect between the Cu/gamma-Al2O3 catalyst and the CO2/H-2 plasma, achieving a CO2 conversion of 10% at 4 wt % Cu loading and a CH3OH selectivity near 50% further rising to 65% with H2O addition (for a H2O/CO2 ratio of 1). Furthermore, the energy consumption for CH3OH production was more than 20 times lower than with plasma only. We carried out density functional theory calculations over a Cu-13/gamma-Al2O3 model, which reveal that the interfacial sites of the Cu-13 cluster and gamma-Al2O3 support show a bifunctional effect: they not only activate the CO2 molecules but also strongly adsorb key intermediates to promote their hydrogenation further. Reactive plasma species can regulate the catalyst surface reactions via the Eley-Rideal (E-R) mechanism, which accelerates the hydrogenation process and promotes the generation of the key intermediates. H2O can promote the CH3OH desorption by competitive adsorption over the Cu-13/gamma-Al2O3 surface. This study provides new insights into CO2 hydrogenation through plasma catalysis, and it provides inspiration for the conversion of some other small molecules (CH4, N-2, CO, etc.) by plasma catalysis using supported-metal clusters.

Abstract: Atomic scale simulations of the nucleation and growth of carbon nanotubes is essential for understanding their growth mechanism. In spite of over twenty years of simulation efforts in this area, limited progress has so far been made on addressing the role of the hydrocarbon growth precursor. Here we report on atomic scale simulations of cap nucleation of single-walled carbon nanotubes from hydrocarbon precursors. The presented mechanism emphasizes the important role of hydrogen in the nucleation process, and is discussed in relation to previously presented mechanisms. In particular, the role of hydrogen in the appearance of unstable carbon structures during in situ experimental observations as well as the initial stage of multi-walled carbon nanotube growth is discussed. The results are in good agreement with available experimental and quantum-mechanical results, and provide a basic understanding of the incubation and nucleation stages of hydrocarbon-based CNT growth at the atomic level.

Abstract: Gap junctions (GJs), essential structures for cell-cell communication, are made of two hemichannels (commonly called connexons), one on each adjacent cell. Found in almost all cells, GJs play a pivotal role in many physi­ological and cellular processes, and have even been linked to the progression of diseases, such as cancer. Modulation of GJs is under investigation as a therapeutic strategy to kill tumor cells. Furthermore, GJs have also been studied for their key role in activating anti-cancer immunity and propagating radiation- and oxidative stress-induced cell death to neighboring cells, a process known as the bystander effect. While, gap junction (GJ)based therapeutic strategies are being developed, one major challenge has been the paradoxical role of GJs in both tumor progression and suppression, based on GJ composition, cancer factors, and tumoral context. Therefore, understanding the mechanisms of action, regulation, and the dual characteristics of GJs in cancer is critical for developing effective therapeutics. In this review, we provide an overview of the current under­ standing of GJs structure, function, and paradoxical pro- and anti-tumoral role in cancer. We also discuss the treatment strategies to target these GJs properties for anti-cancer responses, via modulation of GJ function.

Abstract: Industrial production of HCN from NH3 and CH4 not only uses precious Pt or Pt−Rh catalysts but also requires extremely high temperatures (∼1600 K). From an energetic, operational, and safety perspective, a drastic decrease in temperature is highly desirable. Here, we report ammonia reforming of methane for the production of HCN and H2 at 673 K by the combination of CH4/NH3 plasma and a supported Cu/silicalite-1 catalyst. 30% CH4 conversion has been achieved with 79% HCN selectivity. Catalyst characterization and plasma diagnostics reveal that the excellent reaction performance is attributed to metallic Cu active sites. In addition, we propose a possible reaction pathway, viz. E-R reactions with N, NH, NH2, and CH radicals produced in the plasma, for the production of HCN, based on density functional theory calculations. Importantly, the Cu/silicalite-1 catalyst costs less than 5% of the commercial Pt mesh catalyst.

Abstract: The Covid era has made us aware of the need for resilient, self-sufficient, and local production. We are likely willing to pay an extra price for that quality. Ammonia (NH3) synthesis accounts for 2 % of global energy production and is an important point of attention for the development of green energy technologies. Therefore, we propose a thermally integrated process for H2 production and NH3 synthesis using plasma technology, and we evaluate its techno-economic performance and CO2 footprint by life cycle assessment (LCA). The key is to integrate energy-wise a high-temperature plasma (HTP) process, with a (low-temperature) non-thermal plasma (NTP) process and to envision their joint economic potential. This particularly means raising the temperature of the NTP process, which is typically below 100 ◦ C, taking advantage of the heat released from the HTP process. For that purpose, we proposed the integrated process and conducted chemical kinetics simulations in the NTP section to determine the thermodynamically feasible operating window of this novel combined plasma process. The results suggest that an NH3 yield of 2.2 mol% can be attained at 302 ◦ C at an energy yield of 1.1 g NH3/kWh. Cost calculations show that the economic performance is far from commercial, mainly because of the too low energy yield of the NTP process. However, when we base our costs on the best literature value and plausible future scenarios for the NTP energy yield, we reach a cost prediction below 452 $/tonne NH3, which is competitive with conventional small-scale Haber-Bosch NH3 synthesis for distributed production. In addition, we demonstrate that biogas can be used as feed, thus allowing the proposed integrated reactor concept to be part of a biogas-to-ammonia circular concept. Moreover, by LCA we demonstrate the environmental benefits of the pro­posed plant, which could cut by half the carbon emissions when supplied by photovoltaic electricity, and even invert the carbon balance when supplied by wind power due to the avoided emissions of the carbon black credits.

Abstract: In this contribution, we present an overview of the various techniques for combining atomistic molecular dynamics with Monte Carlo simulations, mainly in the context of condensed matter systems, as well as a brief summary of the main accelerated dynamics techniques. Special attention is given to the force bias Monte Carlo technique and its combination with molecular dynamics, in view of promising recent developments, including a definable timescale. Various examples of the application of combined molecular dynamics / Monte Carlo simulations are given, in order to demonstrate the enhanced simulation efficiency with respect to either pure molecular dynamics or Monte Carlo.

Abstract: The compositional influence of Cr and Y on the microstructure of Mg―Cr―O, and Mg―Y―O films synthesized by reactive magnetron sputtering has been investigated by transmission electron microscopy, X-ray diffraction and molecular dynamics simulations. A decrease in crystallinity is observed in these films as the M (Cr or Y) content is increased. It is found that M forms a solid solution with MgO for metal ratios up to ~ 70% and ~ 50% for Cr and Y respectively. Above ~ 70% Cr metal ratio the Mg―Cr―O films are found to be completely amorphous. The Mg―Y―O films are composed of Mg(Y)O and Y2O3 nano crystallites, up to ~ 50% Y metal ratio. Above this ratio, only Y2O3 nano crystallites are found. The preferential < 111> MgO grain alignment is strongly affected by the increase in M content. For M metal ratios up to ~ 50%, there is a selective promotion of the < 100> MgO grain alignments and a decline in the < 111> grain alignments.

Abstract: Understanding the fundamental dynamics in carbon nanotube (CNT) catalysts is of primary importance to understand CNT nucleation. This Letter reports on calculated bond switching (BS) rates in pure and carbon containing nickel nanoclusters. The rates are analyzed in terms of their temperature dependent spatial distribution and the mobility of the cluster atoms. The BS mechanism is found to change from vibrational to diffusional at around 900 K, with a corresponding strong increase in activation energy. Furthermore, the BS activation energy is observed to decrease as the carbon content in the cluster increases, resulting in an effective liquification of the cluster.