Abstract: Purpose Natural deep eutectic solvents (NADES) represent a green alternative to conventional organic solvents as reaction medium, offering more benign properties. To efficiently design NADES for biocatalysis, a better understanding of their effect on these reactions is needed. We hypothesize that this effect can be described by separately considering (1) the solvent interactions with the substrates, (2) the solvent viscosities and (3) the enzyme stability in NADES. Methods We investigated the effect of substrate solvation and viscosity on the reaction rate; and the stability of the enzyme in NADES. To this end, we monitored the conversion over time of the transesterification of vinyl laurate with 1- butanol by the lipase enzyme Candida antarctica B in NADES of different compounds and molar ratios. Results The initial reaction rate is higher in most NADES ( varying between 1.14 and 15.07 mu mol min(-1) mg(-1)) than in the reference n-hexane (4.0 mu mol min(-1) mg(-1))), but no clear relationship between viscosity and initial reaction rate was found. The increased reaction rate is most likely related to the solvation of the substrate due to a change in the activation energy of the reaction or a change in the conformation of the substrate. The enzyme retained part of its activity after the first 2 h of reaction (on average 20 % of the substrate reacted in the 2-24 h period). Enzyme incubation in ethylene glycol-based NADES resulted in a reduced reaction rate ( 15.07 vs. 3.34 mu mol min(-1) mg(-1)), but this may also be due to slow dissolution of the substrate. Conclusions The effect of viscosity seems to be marginal next to the effect of solvation and possible enzyme-NADES interaction. The enzyme retains some of its activity during the 24-hour measurements, but the enzyme incubation experiments did not yield accurate, comparable values. [GRAPHICS] .

Abstract: New & beta;-stabilizedTi-based alloys are highly promising forbone implants, thanks in part to their low elasticity. The natureof this elasticity, however, is as yet unknown. We here present combinedfirst-principles DFT calculations and experiments on the microstructure,structural stability, mechanical characteristics, and electronic structureto elucidate this origin. Our results suggest that the studied & beta;Ti-35Nb-7Zr-5Ta wt % (TNZT) alloy manufacturedby the electron-beam powder bed fusion (E-PBF) method has homogeneousmechanical properties (H = 2.01 & PLUSMN; 0.22 GPa and E = 69.48 & PLUSMN; 0.03 GPa) along the building direction,which is dictated by the crystallographic texture and microstructuremorphologies. The analysis of the structural and electronic properties,as the main factors dominating the chemical bonding mechanism, indicatesthat TNZT has a mixture of strong metallic and weak covalent bonding.Our calculations demonstrate that the softening in the Cauchy pressure(C & PRIME; = 98.00 GPa) and elastic constant C ̅ ( 44 ) = 23.84 GPa is the originof the low elasticity of TNZT. Moreover, the nature of this softeningphenomenon can be related to the weakness of the second and thirdneighbor bonds in comparison with the first neighbor bonds in theTNZT. Thus, the obtained results indicate that a carefully designedTNZT alloy can be an excellent candidate for the manufacturing oforthopedic internal fixation devices. In addition, the current findingscan be used as guidance not only for predicting the mechanical propertiesbut also the nature of elastic characteristics of the newly developedalloys with yet unknown properties.

Abstract: Carbon nanotubes (CNTs) have been successfully used in biomedicine, including cancer therapy, due to their unique physico-chemical properties. Because pristine CNTs exhibit hydrophobic behaviour, they can have a cytotoxic effect on cells, which limits their practical use in biomedicine. The toxicity of CNTs can be reduced by adding water-soluble functional radicals to their surface, i.e. by increasing their hydrophilicity. Another possibility for increasing the hydrophilicity of CNTs is probably filling them with endohedral metal atoms, which has not yet been studied. Thus, in this study, we use computer simulations to investigate the combined effect of endohedral nickel atoms and functional groups on the hydrophilicity of CNTs. Our simulation results show that the introduction of endohedral nickel atoms into CNTs increases their binding energy with functional groups. We also find that the addition of functional groups to the surface of CNT, along with filling it with endohedral nickel atoms, leads to an increase in the dipole moment of the CNT as well as its interaction energy with water, thereby increasing the hydrophilicity of the CNT and, consequently, its solubility in water. This, in turn, can lead to a decrease in CNT toxicity.

Abstract: The overexpression of voltage dependent anion channels (VDACs), particularly VDAC1, in cancer cells compared to normal cells, plays a crucial role in cancer cell metabolism, apoptosis regulation, and energy homeostasis. In this study, we used molecular dynamics (MD) simulations to investigate the effect of a low level of VDAC1 oxidation (induced e.g., by cold atmospheric plasma (CAP)) on the pyruvate (Pyr) uptake by VDAC1. Inhibiting Pyr uptake through VDAC1 can suppress cancer cell proliferation. Our primary target was to study the translocation of Pyr across the native and oxidized forms of hVDAC1, the human VDAC1. Specifically, we employed MD simulations to analyze the hVDAC1 structure by modifying certain cysteine residues to cysteic acids and methionine residues to methionine sulfoxides, which allowed us to investigate the effect of oxidation. Our results showed that the free energy barrier for Pyr translocation through the native and oxidized channel was approximately 4.3 +/- 0.7 kJ mol-1 and 10.8 +/- 1.8 kJ mol-1, respectively. An increase in barrier results in a decrease in rate of Pyr permeation through the oxidized channel. Thus, our results indicate that low levels of CAP oxidation reduce Pyr translocation, resulting in decreased cancer cell proliferation. Therefore, low levels of oxidation are likely sufficient to treat cancer cells given the inhibition of Pyr uptake.

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: In this letter, a dipole sheet method is proposed to theoretically study the adsorption and decomposition of C5F10O over-discharged Cu (111) and Al (111) surfaces. A synergistic effect of external electric fields and surface excess charges shows up for jointly promoting the adsorption of C5F10O, accompanied by the enhancement of C-F bond elongation and charge transfer process. The decomposition of C5F10O is facilitated in the discharged region and the initial decomposition is found most likely to occur via the cleavage of the C-F single bond. The results indicate that the decomposition of C5F10O over the metal electrode surfaces is much accelerated when discharge faults occur and free F atoms could be generated from C5F10O before its carbon chain breakage. These findings help to elucidate the underlying decomposition tendency of C5F10O in discharged systems and provide a practical method for evaluating and designing new insulation gases.

Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases, characterized by a treatment-resistant and invasive nature. In line with these inherent aggressive characteristics, only a subset of patients shows a clinical response to the standard of care therapies, thereby highlighting the need for a more personalized treatment approach. In this study, we comprehensively unraveled the intra-patient response heterogeneity and intrinsic aggressive nature of PDAC on bulk and single-organoid resolution. We leveraged a fully characterized PDAC organoid panel ( N  = 8) and matched our artificial intelligence-driven, live-cell organoid image analysis with retrospective clinical patient response. In line with the clinical outcomes, we identified patient-specific sensitivities to the standard of care therapies (gemcitabine-paclitaxel and FOLFIRINOX) using a growth rate-based and normalized drug response metric. Moreover, the single-organoid analysis was able to detect resistant as well as invasive PDAC organoid clones, which was orchestrates on a patient, therapy, drug, concentration and time-specific level. Furthermore, our in vitro organoid analysis indicated a correlation with the matched patient progression-free survival (PFS) compared to the current, conventional drug response readouts. This work not only provides valuable insights on the response complexity in PDAC, but it also highlights the potential applications (extendable to other tumor types) and clinical translatability of our approach in drug discovery and the emerging era of personalized medicine.

Abstract: Ceramics and composites, many of whose physicochemical properties significantly exceed similar properties of metals and their alloys, are processed qualitatively mainly by the electroerosion method. Despite the existing works, the mechanism of the initial stage of the removal of materials has not yet been identified. For a comprehensive understanding of the mechanism of the removal of dielectrics, a new model is proposed based on the experimental results obtained on an improved electroerosion installation. It was revealed that the initial stage of the removal of a dielectric material consists of three successive stages that are associated with the synergistic effect on the process of the anionic group of electrolytes, plasma flare, and the cavitation shock. This makes it possible to better understand the mechanism of the removal of composite and ceramic materials, which should contribute to ensuring the machinability of those materials and their wide use in promising technologies.

Abstract: Herein, the efficacy of WOx-promoted CeO2-SiO2 and CeO2-ZrO2 mixed oxide catalysts in the solvent-free selective oxidation of benzyl alcohol to benzaldehyde using molecular oxygen as an oxidant is reported. We evaluated the effects of the oxidant and catalyst concentration, reaction duration, and temperature on the reaction with an aim to optimize the reaction conditions. The as-prepared CeO2, CeO2-ZrO2, CeO2-SiO2, WOx/CeO2, WOx/CeO2-ZrO2, and WOx/CeO2-SiO2 catalysts were characterized by X-ray diffraction (XRD), N-2 adsorption-desorption, Raman spectroscopy, temperature-programmed desorption of ammonia (TPD-NH3), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). These characterisation results indicated that the WOx/CeO2-SiO2 catalyst possessed improved physicochemical (i.e., structural, textural, and acidic) properties owing to the strong interactivity between WOx and CeO2-SiO2. A higher number of Ce3+ ions (I-u '''/I-Total) were created with the WOx/CeO2-SiO2 catalyst than those with the other catalysts in this work, indicating the generation of a high number of oxygen vacancies. The WOx/CeO2-SiO2 catalyst exhibited a high conversion of benzyl alcohol (>99%) and a high selectivity (100%) toward benzaldehyde compared to the other promoted catalysts (i.e., WOx/CeO2 and WOx/CeO2-ZrO2), which is attributed to the smaller particle size of the WOx and CeO2 and their high specific surface area, more significant number of acidic sites, and superior number of oxygen vacancies. The WOx/CeO2-SiO2 catalyst could be quickly recovered and utilized at least five times without suffering any appreciable activity loss.

Abstract: Background This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF. Methods Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy. Results The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids. Conclusion Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.

Abstract: Humanity feels the urge of shifting to a sustainable society more than at any other time in its history. Electrification of chemical industry plays a key role in this transition. The possibility of producing fertilizers from air using renewable electricity, and simultaneously, no greenhouse gas emission, resulted in an increasing interest toward plasma technology as a solution for electrification of a part of the chemical industry in the past few years. Additionally, the activation of nitrogen molecules by vibrational and electronic excitation reactions in plasma can lead to an energy-efficient process. Last but not least, the modularity (fast on/off characteristic) of plasma technology makes it capable of using intermittent renewable electricity on site for the production of fertilizers using air. All these advantages offered by plasma technology make it a potential solution for the on-site production of fertilizers in small and decentralized plants using air and renewable electricity, which leads to a considerable reduction in fertilizer production and transportation costs. However, industrialization of plasma-based NF suffers from several challenges, including challenges of plasma catalysis for the selective production of desired species, the high energy cost of plasma-based NF compared to current industrial processes, and the design and development of scaled up and energy-efficient plasma reactors for industrial purposes. In the framework of this thesis we have tried to add to the state-of-the-art (SOTA) in plasma-based NOx production and deal with its limitations using a combination of experimental and modelling work.

Abstract: Nowadays, the burning of fossil fuels, particularly petroleum, natural gas, and coal, meets the rising need for power and fuels for automobiles and industries. This has given rise to ecological and climate challenges. This thesis explores these issues from three distinct perspectives: (i) experimental, (ii) computational, and (iii) process simulation, with a focus on studying CO2 as an alternative and economically viable raw material. Firstly, the experimental study is focused on the synthesis, characterization, and testing of novel catalysts for electroreduction of CO2 and oxalic acid, an intermediate product of CO2. Electrocatalysts based on Cu supported by citrus (orange and lemon) peel biomass are prepared. These catalysts exhibit activity in the electrochemical reduction of CO2, emphasizing the effectiveness of biomasses, particularly orange peels, as environmentally friendly precursors for sustainable and efficient electrocatalysts. In addition, graphitic carbon nitrides/TiO2 nanotubes (g-C3N4/TiNT) composites are prepared for the electrocatalytic reduction of oxalic acid to glycolic acid, revealing superior electrocatalytic properties compared to pristine TiNT. Characterization by X-ray diffraction, X-ray photoelectron spectroscopy, and scanning electronic microscopy were performed for all the prepared electrocatalysts. Delving into the reduction of CO2 on Cu catalysts, a computational study about the synthesis of methanol on Cu(111) surface is performed by using the Vienna Ab initio Simulation Package. A systematic study is carried out to define the activation energies of the elementary reactions by using mGGA DF. Consequently, it is shown that the rate-controlling step is CH3O* hydrogenation and the formate pathway on Cu(111) proceeds through the HCOOH* intermediate. Finally, the process simulation, performed by using the software Aspen Plus 11 from AspenTech Inc., is based on the comparison of a catalytic (oxidation of ethylene glycol) and an electrocatalytic process (CO2 electroreduction chain) to synthesize glycolic acid. An economic analysis of the operational and investment costs reveals that the catalytic process is more cost-effective due to the current instability of electrocatalysts and proton exchange membranes, resulting in increased maintenance costs and, consequently, higher prices for the product.

Abstract: The development of compact, low power, charge-neutral propulsion sources is of significant recent interest due to the rising application of micro-scale satellite platforms. Among such sources, radio frequency (rf) electrothermal microthrusters present an attractive option due to their scalability, reliability, and tunable control of power coupling to the propellant. For micropropulsion applications, where available power is limited, it is of particular importance to understand how electrical power can be transferred to the propellant efficiently, a process that is underpinned by the plasma sheath dynamics. In this work, two-dimensional fluid/Monte Carlo simulations are employed to investigate the effects of applied voltage frequency on the electron, ion, and neutral heating in an rf capacitively coupled plasma microthruster operating in argon. Variations in the electron and argon ion densities and power deposition, and their consequent effect on neutral-gas heating, are investigated with relation to the phase-averaged and phase-resolved sheath dynamics for rf voltage frequencies of 6-108 MHz at 450 V. Driving voltage frequencies above 40.68 MHz exhibit enhanced volumetric ionization from bulk electrons at the expense of the ion heating efficiency. Lower driving voltage frequencies below 13.56 MHz exhibit more efficient ionization due to secondary electrons and an increasing fraction of rf power deposition into ions. Thermal efficiencies are improved by a factor of 2.5 at 6 MHz as compared to the more traditional 13.56 MHz, indicating a favorable operating regime for low power satellite applications.

Abstract: We propose a plasma chemical looping CO2 splitting (PCLCS) approach that enables highly efficient CO2 conversion into O-2-free CO at mild temperatures. PCLCS achieves an impressive 84% CO2 conversion and a 1.3 mmol g(-1) CO yield, with no O-2 detected. Crucially, this strategy significantly lowers the temperature required for conventional chemical looping processes from 650 to 1000 degrees C to only 320 degrees C, demonstrating a robust synergy between plasma and the Ce0.7Zr0.3O2 oxygen carrier (OC). Systematic experiments and density functional theory (DFT) calculations unveil the pivotal role of plasma in activating and partially decomposing CO2, yielding a mixture of CO, O-2/O, and electronically/vibrationally excited CO2*. Notably, these excited CO2* species then efficiently decompose over the oxygen vacancies of the OCs, with a substantially reduced activation barrier (0.86 eV) compared to ground-state CO2 (1.63 eV), contributing to the synergy. This work offers a promising and energy-efficient pathway for producing O-2-free CO from inert CO2 through the tailored interplay of plasma and OCs.

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image