Abstract: Cold atmospheric plasma (CAP) is a source of cell‐damaging oxidant molecules that may be used as low‐cost cancer treatment with minimal side effects. Liquids treated with cold plasma and enriched with oxidants are a modality for non‐invasive treatment of internal tumors with cold plasma via injection. However, liquids are easily diluted with body fluids which impedes high and localized delivery of oxidants to the target. As an alternative, plasma‐treated hydrogels (PTH) emerge as vehicles for the precise delivery of oxidants. This study reports an optimal protocol for the preparation of injectable alginate PTH that ensures the preservation of plasma‐generated oxidants. The generation, storage, and release of oxidants from the PTH are assessed. The efficacy of the alginate PTH in cancer treatment is demonstrated in the context of cancer cell cytotoxicity and immunogenicity–release of danger signals and phagocytosis by immature dendritic cells, up to now unexplored for PTH. These are shown in osteosarcoma, a hard‐to‐treat cancer. The study aims to consolidate PTH as a novel cold plasma treatment modality for non‐invasive or postoperative tumor treatment. The results offer a rationale for further exploration of alginate‐based PTHs as a versatile platform in biomedical engineering.

Abstract: Density functional theory simulations are used to identify the structural factors that define the material properties of ovonic threshold switches (OTS). They show that the nature of mobility-gap trap states in amorphous Ge-rich Ge50Se50 is related to Ge-Ge bonds, whereas in Se-rich Ge30Se70 the Ge valence-alternating-pairs and Se lone-pairs dominate. To obtain a faithful description of the electronic structure and delocalization of states, it is required to combine hybrid exchange-correlation functionals with large unit-cell models. The extent of localization of electronic states depends on the applied external electric field. Hence, OTS materials undergo structural changes during electrical cycling of the device, with a decrease in the population of less exothermic Ge-Ge bonds in favor of more exothermic Ge-Se. This reduces the amount of charge traps, which translates into coordination changes, an increase in mobility-gap, and subsequently changes in the selector-device electrical parameters. The threshold voltage drift process can be explained by natural evolution of the nonpreferred Ge-Ge bonds (or “chains”/clusters thereof) in Ge-rich GexSe1-x. The effect of extrinsic doping is shown for Si and N, which introduce strong covalent bonds into the system, increase both mobility-gap and crystallization temperature, and decrease the leakage current.

Abstract: Ammonia is an industrial large-volume chemical, with its main application in fertilizer production. It also attracts increasing attention as a green-energy vector. Over the past century, ammonia production has been dominated by the Haber-Bosch process, in which a mixture of nitrogen and hydrogen gas is converted to ammonia at high temperatures and pressures. Haber-Bosch processes with natural gas as the source of hydrogen are responsible for a significant share of the global CO(2)emissions. Processes involving plasma are currently being investigated as an alternative for decentralized ammonia production powered by renewable energy sources. In this work, we present the PNOCRA process (plasma nitrogen oxidation and catalytic reduction to ammonia), combining plasma-assisted nitrogen oxidation and lean NO(x)trap technology, adopted from diesel-engine exhaust gas aftertreatment technology. PNOCRA achieves an energy requirement of 4.6 MJ mol(-1)NH(3), which is more than four times less than the state-of-the-art plasma-enabled ammonia synthesis from N(2)and H(2)with reasonable yield (>1 %).

Abstract: CO2 dissociation and its subsequent conversion into added-value chemicals is a promising strategy for recycling CO2 gas into reusable products. One of the possible methods is direct plasma-induced dissociation. In this work we study the efficiency of CO2 dissociation in pulsed atmospheric-pressure gas discharge between two conducting electrodes by a 0-D numerical plasma model. The purpose of the study is to provide results on the optimal conditions of CO2 conversion with respect to the energy efficiency and dissociation by varying the maximum power density value and the pulse length. The power density is directly related to the discharge current and the reduced electric field in the discharge. We consider pulse lengths in the range from hundreds of nanosecond up to milliseconds. The results obtained show that the dissociation degree and energy efficiency are sensitive to the pulse length (duration) and the power density, so that a considerable improvement of the discharge performance can be achieved by fine-tuning these parameters. The study is intended to provide guidance in designing an experimental set-up and a power supply with the characteristics necessary to achieve optimal conversion.

Abstract: Upgrading ethane with CO2 as a soft oxidant represents a desirable means of obtaining oxygenated hydrocarbons. This reaction is not thermodynamically feasible under mild conditions and has not been previously achieved as a one-step process. Nonthermal plasma was implemented as an alternative means of supplying energy to overcome activation barriers, leading to the production of alcohols, aldehydes, and acids as well as C1−C5+ hydrocarbons under ambient pressure, with a maximum total oxygenate selectivity of 12%. A plasma chemical kinetic computational model was developed and found to be in good agreement with the experimental trends. Results from this study illustrate the potential to use plasma for the direct synthesis of value-added alcohols, acids, and aldehydes from ethane and CO2 under mild conditions.

Abstract: Melanoma remains a deadly cancer despite significant advances in immune checkpoint blockade and targeted therapies. The incidence of melanoma is also growing worldwide, which highlights the need for novel treatment options and strategic combination of therapies. Here, we investigate non-thermal plasma (NTP), an ionized gas, as a promising, therapeutic option. In a melanoma mouse model, direct treatment of tumors with NTP results in reduced tumor burden and prolonged survival. Physical characterization of NTP treatment in situ reveals the deposited NTP energy and temperature associated with therapy response, and whole transcriptome analysis of the tumor identified several modulated pathways. NTP treatment also enhances the cancer-immunity cycle, as immune cells in both the tumor and tumor-draining lymph nodes appear more stimulated to perform their anti-cancer functions. Thus, our data suggest that local NTP therapy stimulates systemic, anti-cancer immunity. We discuss, in detail, how these fundamental insights will help direct the translation of NTP technology into the clinic and inform rational combination strategies to address the challenges in melanoma therapy.

Abstract: Although recent studies have advanced the understanding of pyrolyzed
Fe−N−C materials as oxygen reduction reaction (ORR) catalysts, the atomic and
electronic structures of the active sites and their detailed reaction mechanisms still remain unknown. Here, based on first-principles density functional theory (DFT) computations, we discuss the electronic structures of three FeN4 catalytic centers with different local topologies of the surrounding C atoms with a focus on unraveling the mechanism of their ORR activity in acidic electrolytes. Our study brings back a forgotten, synthesized pyridinic Fe−N coordinate to the community’s attention, demonstrating that this catalyst can exhibit excellent activity for promoting direct four-electron ORR through the addition of a fifth ligand such as −NH2, −OH, and −SO4. We also identify sites with good stability properties through the combined use of our DFT calculations and Mössbauer spectroscopy data.

Abstract: Biological membranes are under constant attack of reactive oxygen and nitrogen species (RONS), which may lead to a complex mixture of nitro-oxidized lipids that are responsible for structural and dynamic changes on the membrane. Because of that, nitro-oxidized lipids are also associated with several tumors and inflammatory and neurodegenerative diseases. Moreover, lipid oxidation may induce membrane phase-separated domains, which also drastically affect the membrane function. Evidence suggests that domain interfaces are “hot spots” for pore formation, but the underlying mechanisms remain elusive. There is an urgent need for an improved understanding of oxidation-induced phase separation on membrane properties. Likewise, the molecular structure at domain interfaces still needs to be elucidated. To evaluate the effect of lipid nitro-oxidation on the permeability of single-phase (homogeneous) and phase-separated (heterogeneous) phospholipid bilayers (PLBs), we performed atomistic molecular dynamics (MD) simulations using: (1) single-phase PLBs composed of several isomers of nitrated and/or oxidized lipids; (2) phase-separated PLBs composed of coexisting liquid ordered (Lo) and liquid disordered (Ld) domains, where the Ld domain is composed of non-oxidized and/or oxidized lipids. Our results show that nitrated lipids increase the membrane permeability of single-phase PLBs by three-fold compared to oxidized lipids. In addition, we show that oxidized lipids in the presence of nitrated lipids decrease the membrane permeability, suggesting an interaction between nitrated and oxidized lipids. Overall, the permeability of single-phase and phase-separated PLBs was comparable, and the presence of oxidized lipids increases the membrane permeability only in single-phase PLBs. Despite the latter, the presence of only 1.5% of lipid aldehydes at the Lo/Ld domain interfaces of phase-separated PLBs was able to increase the membrane permeability. In consequence of this, we also performed coarse-grained MD simulations to evaluate whether lipid aldehydes have a preference to accumulate at the interface between Lo/Ld domains. Our results show that lipid aldehydes derived from mono-unsaturated lipids accumulate at the interface, but those derived from poly-unsaturated lipids remain in the Ld domain. This study is of interest for photodynamic therapy and plasma medicine for cancer treatment, to understand the effects caused by RONS in cell membranes.

Abstract: Effective abatement of the greenhouse gas sulphur hexafluoride (SF6) waste is of great importance for the environment protection. This work investigates the size effect and the surface properties of gamma-Al2O3 pellets on SF6 degradation in a packed bed dielectric barrier discharge (PB-DBD) system. Experimental results show that decreasing the packing size improves the filamentary discharges and promotes the ignition and the maintenance of plasma, enhancing the degradation performance at low input powers. However, too small packing pellets decrease the gas residence time and reduce the degradation efficiency, especially for the input power beyond 80 W. Besides, lowering the packing size promotes the generation of SO2, while reduces the yields of S-O-F products, corresponding to a better degradation. After the discharge, the pellet surface becomes smoother with the appearance of S and F elements. Density functional theory calculations show that SF6 is likely to be adsorbed at the Al-III site over the gamma-Al2O3(110) surface, and it is much more easily to decompose than in the gas phase. The fluorine gaseous products can decompose and stably adsorb on the pellet surface to change the surface element composition. This work provides a better understanding of SF6 degradation in a PB-DBD system.

Abstract: The application of dielectric barrier discharge (DBD) plasma reactors is promising in various environmental and energy processes, but is limited by their low energy yield. In this study, we put a number of stainless steel rings over the inner electrode rod of the DBD reactor to change the local discharge gap and electric field, and we studied the dry reforming performance. At 50 W supplied power, the metal rings mostly have a negative impact on the performance, which we attribute to the non-uniform spatial distribution of the discharges caused by the rings. However, at 30 W supplied power, the energy yield is higher than at 50 W and the placement of the rings improves the performance of the reactor. More rings and with a larger cross-sectional diameter can further improve the performance. The reactor with 20 rings with a 3.2 mm cross-sectional diameter exhibits the best performance in this study. Compared to the reactor without rings, it increases the CO2 conversion from 7% to 16 %, the CH4 conversion from 12% to 23%, and the energy yield from 0.05 mmol/kJ supplied power to 0.1 mmol/kJ (0.19 mmol/kJ if calculated from the plasma power), respectively. The presence of the rings increases the local electric field, the displaced charge and the discharge fraction, and also makes the discharge more stable and with more uniform intensity. It also slightly improves the selectivity to syngas. The performance improvement observed by placing stainless steel rings in this study may also be applicable to other plasma-based processes.

Abstract: 200 years ago, humanity started the industrial revolution by discovering fossil fuels, which lead to unprecedented technological advancements. However it has become alarmingly clear that the major environmental concerns associated with fossil fuels require a short-term transition from a carbon-based energy economy to a sustainable one based on green electricity. A key step concerning this transition exists in developing electricity-driven alternatives for chemical processes that rely on fossil fuels as a raw material. A technology that is gaining increasing interest to achieve this, is plasma technology. Using plasmas to induce chemical reactions by selectively heating electrons in a gas has already delivered promising results for gas conversion applications like CO2 conversion and N2 fixation, but plasma reactors still require optimization to be considered industrially competitive to existing fossil fuel-based processes and emerging other electricity-based technologies. In this thesis I develop computational models to describe plasma reactors and identify key mechanisms in three different plasma reactors for three different gas conversion applications, i.e. N2 fixation, combined CO2-CH4 conversion and CO2 splitting. I first developed models to describe a new rotating gliding arc (GA) reactor operating in two arc modes, which, as revealed by my model, are characterized by distinct plasma chemistry pathways. Subsequently, my colleague and I study the quenching effect of an effusion nozzle to this rotating GA reactor, reaching the best results to date for N2 fixation into NOx at atmospheric pressure, i.e., NOx concentrations up to 5.9%, at an energy cost down to 2.1 MJ/mol. Afterwards, I investigate the possible improvement of N2 admixtures in plasma-based CO2 and CH4 conversion, as significant amounts of N2 are often found in industrial CO2 waste streams, and gas separations are financially costly. Through combining my models with the experiment from a fellow PhD student, we reveal that moderate amounts of N2 (i.e. around 20%) increase both the electron density and the gas temperature to yield an overall energy cost reduction of 21%. Finally, I model quenching nozzles for plasma-based CO2 conversion in a microwave reactor, to explain the enhancements in CO2 conversion that were demonstrated in experiments. Through computational modelling I reveal that the nozzle introduces fast gas quenching resulting in the suppression of recombination reactions, which have more impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.