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: 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: 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: 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: To get better performance from inductively coupled plasma (ICP)-based methods, it is informative to study the properties of the ICP under different conditions. Annemie Bogaerts and Maryam Aghaei at the University of Antwerp, Belgium, are using computational modeling to examine how various properties of the ICP, such as gas flow path lines and velocity, temperature changes, and ionization effects, are affected by numerous factors, such as the gas flow rates of injector and auxiliary gas, applied power, and even the very presence of a mass spectrometry (MS) sampler. They have also applied their models to study particle transport through the ICP. Using their developed model, it is now possible to predict optimum conditions for specific analyses. Bogaerts and Aghaei spoke to us about this work.