Abstract: Utilizing ammonia as a storage medium for hydrogen is currently receiving increased attention. A possible method to retrieve the hydrogen is by plasma-catalytic decomposition. In this work, we combined an experimental study, using a dielectric barrier discharge plasma reactor, with a plasma kinetic model, to get insights into the decomposition mechanism. The experimental results revealed a similar effect on the ammonia conversion when changing the flow rate and power, where increasing the specific energy input (higher power or lower flow rate) gave an increased conversion. A conversion as high as 82 % was achieved at a specific energy input of 18 kJ/Nl. Furthermore, when changing the discharge volume from 31 to 10 cm3, a change in the plasma distribution factor from 0.2 to 0.1 was needed in the model to best describe the conversions of the experiments. This means that a smaller plasma volume caused a higher transfer of energy through micro-discharges (non-uniform plasma), which was found to promote the decomposition of ammonia. These results indicate that it is the collisions between NH3 and the high-energy electrons that initiate the decomposition. Moreover, the rate of ammonia destruction was found by the model to be in the order of 1022 molecules/(cm3 s) during the micro-discharges, which is 5 to 6 orders of magnitude higher than in the afterglows. A considerable re-formation of ammonia was found to take place in the afterglows, limiting the overall conversion. In addition, the model revealed that implementation of packing material in the plasma introduced high concentrations of surface-bound hydrogen atoms, which introduced an additional ammonia re-formation pathway through an Eley-Rideal reaction with gas phase NH2. Furthermore, a more uniform plasma is predicted in the presence of MgAl2O4, which leads to a lower average electron energy during micro-discharges and a lower conversion (37 %) at a comparable residence time for the plasma alone (51 %).

Abstract: To gain insights into the underlying mechanisms of NTP therapy sensitivity and resistance, using the firstever
NTP-resistant cell line derived from sensitive melanoma cells (A375).
Methods: Melanoma cells were exposed to NTP and re-cultured for 12 consecutive weeks before evaluation
against the parental control cells. Whole transcriptome sequencing analysis was performed to identify differentially
expressed genes and enriched molecular pathways. Glucose uptake, extracellular lactate, media acidification,
and mitochondrial respiration was analyzed to determine metabolic changes. Cell death inhibitors were
used to assess the NTP-induced cell death mechanisms, and apoptosis and ferroptosis was further validated via
Annexin V, Caspase 3/7, and lipid peroxidation analysis.
Results: Cells continuously exposed to NTP became 10 times more resistant to NTP compared to the parental cell
line of the same passage, based on their half-maximal inhibitory concentration (IC50). Sequencing and metabolic
analysis indicated that NTP-resistant cells had a preference towards aerobic glycolysis, while cell death analysis
revealed that NTP-resistant cells exhibited less apoptosis but were more vulnerable to lipid peroxidation and
ferroptosis.
Conclusions: A preference towards aerobic glycolysis and ferroptotic cell death are key physiological changes in
NTP-resistance cells, which opens new avenues for further, in-depth research into other cancer types.

Abstract: We present a zero-dimensional kinetic model to characterise specifically the gas-phase dynamics of methane
conversion in a nanosecond pulsed discharge (NPD) plasma reactor. The model includes a systematic approach to
capture the nanoscale power discharges and the rapid ensuing changes in electric field, gas and electron temperature,
as well as species densities. The effects of gas temperature and reactor pressure on gas conversion and
product selectivity are extensively investigated and validated against experimental work. We discuss the
important reaction pathways and provide an analysis of the dynamics of the heating and cooling mechanisms. H
radicals are found to be the most populous plasma species and they participate in hydrogenation and dehydrogenation
reactions, which are the dominant recombination reactions leading to C2H4 and C2H2 as main
products (depending on the pressure).

Abstract: Although most state-of-the-art Sn-based electrocatalysts yield promising results in terms of selectivity and catalyst activity, their stability remains insufficient to date. Here, we demonstrate the successful application of the recently developed pomegranate-structured SnO2 (Pom. SnO2) and SnO2@C (Pom. SnO2@C) nanocomposite electrocatalysts for the efficient electrochemical conversion of CO2 to formate. With an initial selectivity of 83 and 86% towards formate and an operating potential of -0.72 V and -0.64 V vs. RHE, respectively, these pomegranate SnO2 electrocatalysts are able to compete with most of the current state-of-the-art Sn-based electrocatalysts in terms of activity and selectivity. Given the importance of electrocatalyst stability, long-term experiments (24 h) were performed and a temporary loss in selectivity for the Pom. SnO2@C electrocatalyst was largely restored to its initial selectivity upon drying and exposure to air. Of all the used (24 h) electrocatalysts, the pomegranate SnO2@C had the highest selectivity over a time period of one hour, reaching an average recovered FE of 85%, while the commercial SnO2 and bare pomegranate SnO2 electrocatalysts reached an average of 79 and 80% FE towards formate, respectively. Furthermore, the pomegranate structure of Pom. SnO2@C was largely preserved due to the presence of the heterogeneous carbon shell, which acts as a protective layer, physically inhibiting particle segregation/pulverisation and agglomeration.

Abstract: Advanced materials often consist of multiple elements which are arranged in a complicated structure. Quantitative scanning transmission electron microscopy is useful to determine the composition and thickness of nanostructures at the atomic scale. However, significant difficulties remain to quantify mixed columns by comparing the resulting atomic resolution images and spectroscopy data with multislice simulations where dynamic scattering needs to be taken into account. The combination of the computationally intensive nature of these simulations and the enormous amount of possible mixed column configurations for a given composition indeed severely hamper the quantification process. To overcome these challenges, we here report the development of an incoherent non-linear method for the fast prediction of ADF-EDX scattering cross-sections of mixed columns under channelling conditions. We first explain the origin of the ADF and EDX incoherence from scattering physics suggesting a linear dependence between those two signals in the case of a high-angle ADF detector. Taking EDX as a perfect incoherent reference mode, we quantitatively examine the ADF longitudinal incoherence under different microscope conditions using multislice simulations. Based on incoherent imaging, the atomic lensing model previously developed for ADF is now expanded to EDX, which yields ADF-EDX scattering cross-section predictions in good agreement with multislice simulations for mixed columns in a core–shell nanoparticle and a high entropy alloy. The fast and accurate prediction of ADF-EDX scattering cross-sections opens up new opportunities to explore the wide range of ordering possibilities of heterogeneous materials with multiple elements.

Abstract: By combining dielectric barrier discharge plasma and external heating, we exploit a two-stage hybrid plasmathermal
system (HPTS), i.e., a plasma stage followed by a thermal stage, for direct non-oxidative coupling of
CH4 to C2H4 and H2, yielding a CH4 conversion of ca. 17 %. In the two-stage HPTS, the plasma first converts CH4
into C2H6 and C3H8, which in the thermal stage leads to a high C2H4 selectivity of ca. 63 % by pyrolysis, with H2
selectivity of ca. 64 %.

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: The ever-increasing energy demand from the world population has made the intensive use of fossil fuels an overarching threat to global environment and human health. An appealing alternative is offered by sunlight-assisted photoelectrochemical water splitting to yield carbon-free hydrogen fuel, but kinetic limitations associated to the oxygen evolution reaction (OER) render the development of cost-effective, eco-friendly and stable electrocatalysts an imperative issue. In the present work, OER catalysts based on graphitic carbon nitride (g-C3N4) were deposited on conducting glass substrates by a simple decantation procedure, followed by functionalization with low amounts of nanostructured CoO and CoFe2O4 by radio frequency (RF)-sputtering, and final annealing under inert atmosphere. A combination of advanced characterization tools was used to investigate the interplay between material features and electrochemical performances. The obtained results highlighted the formation of a p-n junction for the g-C3N4-CoO system, whereas a Z-scheme junction accounted for the remarkable performance enhancement yielded by g-C3N4-CoFe2O4. The intimate contact between the system components also afforded an improved electrocatalyst stability in comparison to various bare and functionalized g-C3N4-based systems. These findings emphasize the importance of tailoring g-C3N4 chemico-physical properties through the dispersion of complementary catalysts to fully exploit its applicative potential.

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: Electron tomography (ET) is a powerful tool to determine the three-dimensional (3D) structure of nanomaterials in a transmission electron microscope. However, the acquisition of a conventional tilt series for ET is a time-consuming process and can therefore not provide 3D structural information in a time-efficient manner. Here, we propose surface-sensitive secondary electron (SE) imaging as an alternative to ET for the investigation of the morphology of nanomaterials. We use the SE electron beam induced current (SEEBIC) technique that maps the electrical current arising from holes generated by the emission of SEs from the sample. SEEBIC imaging can provide valuable information on the sample morphology with high spatial resolution and significantly shorter throughput times compared with ET. In addition, we discuss the contrast formation mechanisms that aid in the interpretation of SEEBIC data.

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: Herein, we describe for the first time the synthesis of the highly porous Hf-tetracarboxylate porphyrin-based metal-organic framework (MOF) (Hf)PCN-224(M) (M = H2, Co2+). (Hf)PCN-224(H2) was easily and efficiently prepared following a simple microwave-assisted procedure with good yields (56–67%; space-time yields: 1100–1270 kg m−3·day−1), high crystallinity and phase purity by using trifluoromethanesulfonic acid and benzoic acid as modulators in less than 30 min. By simply introducing a preliminary step (10 min), 5,10,15,20-(tetra-4-carboxyphenyl)porphyrin linker (TCPP) was quantitatively metalated with Co2+ without additional purification and/or time consuming protection/deprotection steps to further obtain (Hf)PCN-224(Co). (Hf)PCN-224(Co) was then tested as catalyst in CO2 cycloaddition reaction with different epoxides to yield cyclic carbonates, showing the best catalytic performance described to date compared to other PCNs, under mild conditions (1 bar CO2, room temperature, 18–24 h). Twelve epoxides were tested, obtaining from moderate to excellent conversions (35–96%). Moreover, this reaction was gram scaled-up (x50) without significant loss of yield to cyclic carbonates. (Hf)PCN-224(Co) maintained its integrity and crystallinity even after 8 consecutive runs, and poisoning was efficiently reverted by a simple thermal treatment (175 °C, 6 h), fully recovering the initial catalytic activity.

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: 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.