Abstract: This work aims to enhance the efficiency of integrated poultry waste management in bio-circular-green economy by maximizing the co-digestion of chicken manure and its digestate-grown biomass. In a series of batch assays, Napier grass (NG) was mixed with chicken manure (CM) at various proportions (100:0, 80:20, 60:40, 50:50, 40:60, 20:80 and 0:100) to identify co-substrate synergism, followed by physiochemical conditioning (size reduction and ultrasonication) of NG before co-digestion. Results indicated that NG mix of at least 80% was required to gain a full methanation potential of the individual substrates; no synergistic ratio above unity was found. However, the combined effect of size reduction and sonication was found to markedly improve the cosubstrate's biodegradability by 88.7%. The findings were then used to run continuous co-digestion at various operating regimes. In optimal continuous co-digestion condition, NG particle size of 0.6-2.4 mm combined with sonication intensity at 1111 kJ/kgTS improved biomethanation yield as high as 106.3%. Sub-thermophilic digestion at 45 degrees C was shown to give a higher and more stable CH4 yield than at 55 degrees C. Finally, it was also found that recycling liquid effluent at 40% to replace freshwater in feed, although showed no significant difference in CH4 yield (& alpha; = 0.05), noticeably increased system buffer capacity. This optimized biodegradation regime could give co-digestion waste management a higher overall plant efficiency and economic return.

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: We assessed the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal-plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance.

Abstract: Gallium oxide nanorods with unprecedented small dimensions (20-80nm length and 3-5nm width) were prepared using a novel, template-free synthesis method. This nanomaterial is an excellent heterogeneous catalyst for the sustainable epoxidation of alkenes with H2O2, rivaling the industrial benchmark microporous titanosilicate TS-1 with linear alkenes and being much superior with bulkier substrates. A thorough characterization study elucidated the correlation between the physicochemical properties of the gallium oxide nanorods and their catalytic performance, and underlined the importance of the nanorod morphology for generating a material with high specific surface area and a high number of accessible acid sites.

Abstract: The motivation for the present study is to be found in the recent experiments of Fuchizaki and Hamaya on GeI4. They observed a rapid increase in the melting temperature Tm in going from atmospheric pressure to p
~ 2.6 GPa. Tm was found to be largely independent of pressure above this value. In this paper, heuristic arguments are presented to support the idea that until some critical pressure, a crystalline phase of SnI4, CCl4 and GeI4 molecular solids melts into a low density liquid. However, at this critical pressure, a phase boundary intersects Tm(p), separating a low density liquid phase from a high density liquid. The new phase boundary is between the crystal and an amorphous molecular solid with increasing polymerisation as the pressure is increased.

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: The substitution of vanadium in vanadium dioxide VO2 influences the critical temperatures of structural and metal-to-insulator transitions in different ways depending on the valence of the dopant. Rhenium adopts valence states between + 4 and + 7 in an octahedral oxygen surrounding and is particularly interesting in this context. Structural investigation of V1-xRexO2 solid solutions (0.01 <= x <= 0.30) between 80 and 1200 K using synchrotron X-ray powder diffraction revealed only two polymorphs that resemble VO2: the low-temperature monoclinic MoO2-type form (space group P2(1)/c), and the tetragonal rutile-like form (space group P4(2)/mnm). However, for compositions with 0.03 < x <= 0.15 a phase separation in the solid solution was observed below 1000 K upon cooling down from 1200 K, giving rise to two isostructural phases with slightly different lattice parameters. This is reflected in the appearance of two metal-toinsulator transition temperatures detected by magnetization and specific heat measurements. Comprehensive X-ray photoelectron spectroscopy studies showed that an increased amount of Re leads to a change in the Re valence state from solely Re6+ at a low doping level (<= 3 at% Re) via mixed-valence states Re4+/Re6+ for at least 0.03 < x <= 0.10, up to nearly pure Re4+ in V0.70Re0.30O2. Thus, compositions V1-xRexO2 with only one valence state of Re in the material (Re6+ or Re4+) can be obtained as a single phase, while intermediate compositions are subjected to a phase separation, presumably due to different valence states of Re.

Abstract: Monolayers of graphene and hexagonal boron nitride (hBN) are highly permeable to thermal protons1,2. For thicker two-dimensional (2D) materials, proton conductivity diminishes exponentially, so that, for example, monolayer MoS2 that is just three atoms thick is completely impermeable to protons1. This seemed to suggest that only one-atom-thick crystals could be used as proton-conducting membranes. Here, we show that few-layer micas that are rather thick on the atomic scale become excellent proton conductors if native cations are ion-exchanged for protons. Their areal conductivity exceeds that of graphene and hBN by one to two orders of magnitude. Importantly, ion-exchanged 2D micas exhibit this high conductivity inside the infamous gap for proton-conducting materials3, which extends from ∼100 °C to 500 °C. Areal conductivity of proton-exchanged monolayer micas can reach above 100 S cm−2 at 500 °C, well above the current requirements for the industry roadmap4. We attribute the fast proton permeation to ~5-Å-wide tubular channels that perforate micas’ crystal structure, which, after ion exchange, contain only hydroxyl groups inside. Our work indicates that there could be other 2D crystals5 with similar nanometre-scale channels, which could help close the materials gap in proton-conducting applications.