Abstract: We explored the potential of plasma-based In-Situ Resource Utilization (ISRU) for Mars through the conversion of Martian atmosphere (~96% CO2, 2% N2, and 2% Ar) into life-sustaining chemicals. As the Martian surface pressure is about 1% of the Earth’s surface pressure, it is an ideal environment for plasma-based gas conversion using microwave reactors. At 1000 W and 10 Ln/min (normal liters per minute), we produced ~76 g/h of O2 and ~3 g/h of NOx using a 2.45 GHz waveguided reactor at 25 mbar, which is ~3.5 times Mars ambient pressure. The energy cost required to produce O2 was ~0.013 kWh/g, which is very promising compared to recently concluded MOXIE experiments on the Mars surface. This marks a crucial step towards realizing the extension of human exploration.

Abstract: The evolution of the uranium chemical state in uranium compounds, principally in the oxides, is of concern in the context of nuclear fuel degradation under storage and repository conditions, and in accident scenarios. The U–O system shows complicated phase relations between single-valence uranium dioxide (UO₂) and different mixed-valence compounds (<italic>e.g.</italic>U₄O₉, U₃O₇and U₃O₈). To try resolving the electronic structure associated with unique atomic positions, a combined application of diffraction and spectroscopic techniques, such as diffraction anomalous fine structure (DAFS), can be considered. Reported here is the application of two newly developed routines for assessing a DAFS data set, with the aim of refining the uranium X-ray dispersion corrections. High-resolution anomalous diffraction data were acquired from polycrystalline powder samples of UO₂(containing tetravalent uranium) and potassium uranate (KUO₃, containing pentavalent uranium) using synchrotron radiation in the vicinity of the U<italic>L</italic>₃edge (17.17 keV). Both routines are based on an iterative refinement of the dispersion corrections, but they differ in either using the intensity of a selection of reflections or doing a full-pattern (Rietveld method) refinement. The uranium dispersion corrections obtained using either method are in excellent agreement with each other, and they show in great detail the chemical shifts and differences in fine structure expected for tetravalent and pentavalent uranium. This approach may open new possibilities for the assessment of other, more complicated, materials such as mixed-valence compounds. Additionally, the DAFS methodology can offer a significant resource optimization because each data set contains both structural (diffraction) and chemical (spectroscopy) information, which can avoid the requirement to use multiple experimental stations at synchrotron sources.

Abstract: Our study compares short-range order parameters refined from the diffuse scattering in single-crystal X-ray and single-crystal electron diffraction data. Nb0.84CoSb was chosen as a reference material. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms were refined from the diffuse scattering using a Monte Carlo refinement in DISCUS. The difference between the Sb and Co displacements refined from the diffuse scattering and the Sb and Co displacements refined from the Bragg reflections in single-crystal X-ray diffraction data is 0.012 (7) angstrom for the refinement on diffuse scattering in single-crystal X-ray diffraction data and 0.03 (2) angstrom for the refinement on the diffuse scattering in single-crystal electron diffraction data. As electron diffraction requires much smaller crystals than X-ray diffraction, this opens up the possibility of refining short-range order parameters in many technologically relevant materials for which no crystals large enough for single-crystal X-ray diffraction are available.

Abstract: In contrast to conventional polycrystalline titanium oxide (TiO), it was found recently that the superconducting transition temperature Tc can be significantly enhanced from about 2 K to 7.4 K in cubic TiO thin films grown epitaxially on alpha-Al2O3 substrates. This kind of TiO film is also expected to have distinctive optoelectronic properties, which are still not very clear up to now. Herein, by using infrared (IR) reflection measurement we investigate the temperature-dependent optoelectronic response of a cubic TiO thin film, in which temperature induced phase transitions are observed. The semiconductor-, metallic- and semiconductor-like electronic phases of this superconducting film are found in the temperature regimes from 10 to 110 K, 110 to 220 K and above 220 K, respectively. The results obtained optically are consistent with those measured by transport experiment. Furthermore, based on an improved reflection model developed here, we extract the complex optical conductivity of the cubic TiO thin film. We are able to approximately determine the characteristic parameters (e.g., effective electron mass, carrier density, scattering time, etc.) for different electronic phases by fitting the optical conductivity with the modified Lorentz formula. These results not only deepen our understanding of the fundamental physics for cubic TiO thin films but also may find applications in optoelectronic devices based on superconductors.

Abstract: Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain. In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspectral sensors have been used to acquire the reflectance spectra of these mixtures in the visible, near, short, mid, and long-wavelength infrared regions (350-15385) nm. Overlaps in wavelength regions due to the operational ranges of each sensor and variations in acquisition conditions resulted in a large amount of spectral variability. Ground truth composition is given by construction, but to verify that the generated samples are sufficiently homogeneous, XRD and XRF elemental analysis is performed. We believe these data will be beneficial for validating advanced methods for nonlinear unmixing and material composition estimation, including studying spectral variability and training supervised unmixing approaches. The datasets can be downloaded from the following link: https://github.com/VisionlabHyperspectral/Multisensor_datasets.

Abstract: In this work we evaluate the chemical kinetics of dry reforming of methane in warm plasmas (1000–4000 K) using modelling with a newly developed chemistry set, for a broad range of parameters (temperature, power density and CO2/CH4 ratio). We compare the model against thermodynamic equilibrium concentrations, serving as validation of the thermal chemical kinetics. Our model reveals that plasma-specific reactions (i.e., electron impact collisions) accelerate the kinetics compared to thermal conversion, rather than altering the overall kinetics pathways and intermediate products, for gas temperatures below 2000 K. For higher temperatures, the kinetics are dominated by heavy species collisions and are strictly thermal, with negligible influence of the electrons and ions on the overall kinetics. When studying the effects of different gas mixtures on the kinetics, we identify important intermediate species, side reactions and side products. The use of excess CO2 leads to H2O formation, at the expense of H2 formation, and the CO2 conversion itself is limited, only approaching full conversion near 4000 K. In contrast, full conversion of both reactants is only kinetically limited for mixtures with excess CH4, which also gives rise to the formation of C2H2, alongside syngas. Within the given parameter space, our model predicts the 30/70 ratio of CO2/CH4 to be the most optimal for syngas formation with a H2/CO ratio of 2.

Abstract: Climate change impact, food security concerns, and greenhouse gas emissions are pressuring agricultural production systems in developing countries. There is a need for a shift toward sustainable food systems. One of the concepts introduced to drive this shift is climate-smart agriculture (CSA), endorsed by international organizations to address multifaceted challenges. Despite widespread attention and support, the adoption of CSA among African farmers remains low. This systematic literature review aims to shed light on the factors influencing CSA adoption amongst African farmers. Within the articles identified as relevant, over 50 CSA practices and more than 40 factors influencing CSA adoption were distinguished. These influencing factors can be categorized as personal, farm- related, financial, environmental, and informational. The focus of this review is to identify and explain the overall impact (positive, negative, or mixed) of these factors on CSA adoption. Overall, many factors result in mixed effects, only some factors have an unambiguous positive or negative effect on CSA adoption. For instance, educational level emerges as a key personal factor, positively impacting CSA adoption, along with positive influences from farmers’ experience and farm size among farm-related factors. Financial factors reveal distinct patterns, with income from farming and access to credit positively influencing adoption, while off-farm income exhibits a negative effect. Environmental factors, though less researched, indicate positive impacts related to changes in rainfall patterns, temperature, and droughts. Lastly, informational factors consistently exhibit a positive effect on CSA adoption, with training, access to extension, group memberships, climate information, and CSA awareness playing crucial roles. These findings provide valuable insights for policymakers seeking to enhance CSA adoption in Africa, offering a nuanced understanding of the multifaceted dynamics at play.

Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.

Abstract: The structure-property relationship at interfaces is difficult to probe for thermoelectric materials with a complex interfacial microstructure. Designing thermoelectric materials with a simple, structurally-uniform interface provides a facile way to understand how these interfaces influence the transport properties. Here, we synthesized Bi2-xSbxTe3 (x = 0, 0.1, 0.2, 0.4) nanoflakes using a hydrothermal method, and prepared Bi2-xSbxTe3 thin films with predominantly (0001) interfaces by stacking the nanoflakes through spin coating. The influence of the annealing temperature and Sb content on the (0001) interface structure was systematically investigated at atomic scale using aberration-corrected scanning transmission electron microscopy. Annealing and Sb doping facilitate atom diffusion and migration between adjacent nanoflakes along the (0001) interface. As such it enhances interfacial connectivity and improves the electrical transport properties. Interfac reactions create new interfaces that increase the scattering and the Seebeck coefficient. Due to the simultaneous optimization of electrical conductivity and Seebeck coefficient, the maximum power factor of the Bi1.8Sb0.2Te3 nanoflake films reaches 1.72 mW m(-1) K-2, which is 43% higher than that of a pure Bi2Te3 thin film.

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: Photocathodes play a vital role in photoelectrocatalytic water splitting by acting as catalysts for reducing protons to hydrogen gas when exposed to light. Recent advancements in photocathodes have focused on addressing the limitations of noble metal-based materials. These noble metal-based photocathodes rely on expensive and scarce metals such as platinum and gold as cocatalysts or ohmic back contacts, respectively, rendering the final system less sustainable and costly when applied at scale. This mini-review summarizes the important recent progress in the development of non-noble metal-based photocathodes and their performance in the hydrogen evolution reaction during photoelectrochemical (PEC) water splitting. These advancements bring non-noble metal-based photocathodes closer to their noble metal-based counterparts in terms of performance, thereby paving the way forward toward industrial-scale photoelectrolyzers or PEC cells for green hydrogen production.

Abstract: The influence of decoration with impurities and the composition dependent band gap in 2D materials has been the subject of debate for a long time. Here, by using Density Functional Theory (DFT) calculations, we systematically disclose physical properties of chlorinated phosphorene having the stoichiometry of PmCln. By analyzing the adsorption energy, charge density, migration energy barrier, structural, vibrational, and electronic properties of chlorinated phosphorene, we found that (I) the Cl-P bonds are strong with binding energy Eb =-1.61 eV, decreases with increasing n. (II) Cl atoms on phosphorene have anionic feature, (III) the migration path of Cl on phosphorene is anisotropic with an energy barrier of 0.38 eV, (IV) the phonon band dispersion reveal that chlorinated phosphorenes are stable when r <= 0.25 where r = m/n, (V) chlorinated phosphorenes is found to be a photonic crystal in the frequency range of 280 cm-1 to 325 cm-1, (VI) electronic band structure of chlorinated phosphorenes exhibits quasi-flat bands emerging around the Fermi level with widths in the range of 22 meV to 580 meV, and (VII) Cl adsorption causes a semiconducting to metallic/semi-metallic transition which makes it suitable for application as an electroactive material. To elucidate this application, we investigated the change in binding energy (Eb), specific capacity, and open-circuit voltage as a function of the density of adsorbed Cl. The theoretical storage capacity of the chlorinated phosphorene is found to be 168.19 mA h g-1with a large average voltage (similar to 2.08 V) which is ideal number as a cathode in chloride-ion batteries.

Abstract: Digital disconnection has emerged as a concept describing the actions people take to limit their digital connectivity to enhance their well-being. To date, evidence on its effectiveness is mixed, leading to calls for greater consideration of why, how, when, and for whom digital disconnection works. This article responds to these calls, presenting a framework that differentiates four key harms that contribute to experiences of digital ill-being (time displacement, interference, role blurring, and exposure effects). Using these four harms as a starting point, the framework explains: (1) why people are motivated to digitally disconnect; (2) how specific disconnection strategies (i.e., placing limits on time, access, channels, and contents, interactions and features) may help them; and for whom (3) and under which conditions (when) these strategies can be effective.

Abstract: The efficiency of a catalytic process is assessed based on conversion, yield, and time effectiveness. However, these parameters are insufficient for evaluating environmentally sustainable research. As the world is urged to shift towards green catalysis, additional factors such as reaction media, raw material availability, sustainability, waste minimization and catalyst biosafety, need to be considered to accurately determine the efficacy and sustainability of the process. By combining the high porosity and versatility of metal organic frameworks (MOFs) and the activity of gold nanoparticles (AuNPs), efficient, cyclable and biosafe composite catalysts can be achieved. Thus, a composite based on AuNPs and the nanometric flexible porous iron(III) aminoterephthalate MIL-88B-NH2 was successfully synthesized and fully characterized. This nanocomposite was tested as catalyst in the reduction of nitroarenes, which were identified as anthropogenic water pollutants, reaching cyclable high conversion rates at short times for different nitroarenes. Both synthesis and catalytic reactions were performed using green conditions, and even further tested in a time-optimizing one-pot synthesis and catalysis experiment. The sustainability and environmental impact of the catalytic conditions were assessed by green metrics. Thus, this study provides an easily implementable synthesis, and efficient catalysis, while minimizing the environmental and health impact of the process.

Abstract: Plasma catalysis has emerged as a promising approach for driving thermodynamically unfavorable chemical
reactions. Nevertheless, comprehending the mechanisms involved remains a challenge, leading to uncertainty
about whether the optimal catalyst in plasma catalysis aligns with that in thermal catalysis. In this research, we
explore this question by studying monometallic catalysts (Fe, Co, Ni and Mo) and bimetallic catalysts (Fe-Co, Mo-
Co, Fe-Ni and Mo-Ni) in both thermal catalytic and plasma catalytic NH3 decomposition. Our findings reveal that
the Fe-Co bimetallic catalyst exhibits the highest activity in thermal catalysis, the Fe-Ni bimetallic catalyst
outperforms others in plasma catalysis, indicating a discrepancy between the optimal catalysts for the two
catalytic modes in NH3 decomposition. Comprehensive catalyst characterization, kinetic analysis, temperature
program surface reaction experiments and plasma diagnosis are employed to discuss the key factors influencing
NH3 decomposition performance.