Abstract: An extensive CO2 plasmamodel is presented that is relevant for the production of ‘‘solar fuels.’’ It is based on reaction rate coefficients fromrigorously reviewed literature, and is augmented with reactionrate coefficients that are obtained fromscaling laws.The input data set,which is suitable for usage with the plasma simulation software Plasimo (https://plasimo.phys.tue.nl/), is available via the Plasimo and publisher’s websites.1 The correctness of this model implementation has been established by independent ZDPlasKin implementation (http://www.zdplaskin.
laplace.univ-tlse.fr/), to verify that the results agree. Results of these ‘‘global models’’ are presented for a DBD plasma reactor.

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

Abstract: Production of struvite (MgNH4PO4·6H2O) from waste streams is increasingly implemented to recover phosphorus (P), which is listed as a critical raw material in the European Union (EU). To facilitate EU-wide trade of P-containing secondary raw materials such as struvite, the EU issued a revised fertilizer regulation in 2019. A comprehensive overview of the supply of struvite and its quality is presently missing. This study aimed: i) to determine the current EU struvite production volumes, ii) to evaluate all legislated physicochemical characteristics and pathogen content of European struvite against newly set regulatory limits, and iii) to compare not-regulated struvite characteristics. It is estimated that in 2020, between 990 and 1250 ton P are recovered as struvite in the EU. Struvite from 24 European production plants, accounting for 30% of the 80 struvite installations worldwide was sampled. Three samples failed the physicochemical legal limits; one had a P content of <7% and three exceeded the organic carbon content of 3% dry weight (DW). Mineralogical analysis revealed that six samples had a struvite content of 80–90% DW, and 13 samples a content of >90% DW. All samples showed a heavy metal content below the legal limits. Microbiological analyses indicated that struvite may exceed certain legal limits. Differences in morphology and particle size distribution were observed for struvite sourced from digestate (rod shaped; transparent; 82 mass% < 1 mm), dewatering liquor (spherical; opaque; 65 mass% 1–2 mm) and effluent from upflow anaerobic sludge blanket reactor processing potato wastewater (spherical; opaque; 51 mass% < 1 mm and 34 mass% > 2 mm). A uniform soil-plant P-availability pattern of 3.5–6.5 mg P/L soil/d over a 28 days sampling period was observed. No differences for plant biomass yield were observed. In conclusion, the results highlight the suitability of most struvite to enter the EU fertilizer market.

Abstract: Novel indium oxide (In2O3) nanobricks have been prepared by template-less and surfactant-free hydrothermal synthesis method and were characterized by X-ray diffraction (XRD), Raman spectroscopy, photoluminescence (PL) spectroscopy and field emission scanning electronic microscopy (FESEM). The synthesized In2O3 nanobricks were successfully immobilized on the surface of glassy carbon electrode for the detection of Parabens (butylparaben). Owing to the unique structure and intriguing properties of these In2O3 nanobricks, the nanostructured thin-film electrode has shown an obvious electrocatalytic activity for the detection of butylparaben (BP). The detection limit (LOD) was estimated as 3 s/m and the sensitivity (LOQ) was calculated as 10 s/m and were found to be 0.08 μM and 0.26 μA μM−1 cm−2 respectively. This sensor showed high sensitivity compared with the reported electrochemical sensors for the detection of BP. The fabricated sensor was successfully applied for the detection of butyl paraben in real cosmetic samples with good recovery ranging from 96.0 to 100.3%.

Abstract: A crucial property for implants is their biocompatibility. To ensure biocompatibility, thin coatings of hydroxyapatite (HA) are deposited on the actual implant. In this study, we investigate the effects of the addition of silicate anions to the structure of hydroxyapatite coatings on their adhesion strength via a scratch test and ab initio calculations. We find that both the grain size and adhesion strength decrease with the increase in the silicon content in the HA coating (SiHA). The increase in the silicon content to 1.2 % in the HA coating leads to a decrease in the average crystallite size from 28 to 21 nm, and in the case of 4.6 %, it leads to the formation of an amorphous or nanocrystalline film. The decreases in the grain and crystallite sizes lead to peeling and destruction of the coating from the titanium substrate at lower loads. Further, our ab initio simulations demonstrate an increased number of molecular bonds at the amorphous SiHA-TiO2 interface. However, the experimental results revealed that the structure and grain size have more pronounced effects on the adhesion strength of the coatings. In conclusion, based on the results of the ab initio simulations and the experimental results, we suggest that the presence of Si in the form of silicate ions in the HA coating has a significant impact on the structure, grain size, and number of molecular bonds at the interface and on the adhesion strength of the SiHA coating to the titanium substrate.

Abstract: The crystal structure of the newly discovered double-Hg-layer copper oxide superconductor (Hg, Pr)(2)Ba-2(Y, Ca)Cu2O8-delta was studied as a function of chemical doping using neutron and electron diffraction and high-resolution transmission electron microscopy (HREM). Rietveld refinements of the structural parameters from neutron powder diffraction data indicate that the oxygen site O3 on the mercury plane is highly defective, being both partially occupied and displaced from the high-symmetry position. The variable concentration of oxygen vacancies partially compensates for the cation doping and, together with the O3 displacement field, makes some of the Hg atoms acquire an unusual pyramidal coordination. HREM images confirm that the structure is of the '2212' type, with very few defects. In some grains, faint superstructure reflections were evidenced by electron diffraction, suggesting that both the oxygen vacancies and the O3 displacement field may order at least on a local scale.

Abstract: A new tungsten bronze in the SbWO system has been prepared in a solid state reaction from Sb2O3, WO3 and W metal powder. The average structure was determined by single crystal X-ray diffraction. SbxWO3+y (x ∼ 0.11) crystallizes in the orthorhombic space group Pm21n (no. 31), a = 27.8135(9) Å, b = 7.3659(2) Å and c = 3.8672(1) Å. The structure belongs to the (n)-ITB class of intergrowth tungsten bronzes. It contains slabs of hexagonal channels formed by six WO6 octahedra. These slabs are separated by three layers of WO6 octahedra that are arranged in a WO3-type fashion. The WO6 octahedra share all vertices to build up a three-dimensional framework. The hexagonal channels are filled with Sb atoms to ∼80% and additional O atoms. The atoms are shifted out of the center of the channels. Exit-wave reconstruction of focal series of high resolution-transmission-electron-microscope (HRTEM) images combined with statistical paramäeter estimation techniques allowed to study local ordering in the channels. Sb atoms in neighbouring channels tend to be displaced in the same direction, which is in agreement with total energy calculations on ordered structure models, but the ratio of the occupation of the two possible Sb sites varies from channel to channel. The structure of SbxWO3+y exhibits pronounced local modulations.