Abstract: In present work, we have performed the Grand Canonical Monte Carlo (GCMC) simulations to quantify CO2 capture inside porous silica at high operating temperatures of 673.15 K and 873.15 K; and over a operating pressure range of 500 kPa – 4000 kPa that are methane steam reforming process parameters. Related chemical potential values at these thermodynamic conditions are obtained from the bulk phase simulations in the Canonical ensemble in conjunction with Widom’s insertion technique, where the CO2 has been accurately represented by TraPPE force field. Present structure of the porous silica is a single slit pore geometry of various heights (H = 20 Å, 31.6 Å, 63.2 Å and 126.5 Å), dimensions in which possible vapour-liquid equilibria for generic square well fluids has been reported in literature. Estimation of the pore-fluid interactions show a higher interaction between silica pore and adsorbed CO2 compared to the reported pore-fluid interactions between homogeneous carbon slit pore and adsorbed CO2; thus resulting in an enhancement of adsorption inside silica pores of H = 20 Å and H = 126.5 Å, which are respectively 3.5 times and 1.5 times higher than that in homogeneous carbon slit pores of same dimensions and at 673.15 K and 500 kPa. Estimated local density plots indicate the presence of structured layers due to more molecular packing, which confirms possible liquid-like and vapour-like phase coexistence of the supercritical bulk phase CO2 under confinement.

Abstract: It is standard practice in virtual reality applications to synthesize binaural audio based on a discrete set of directionally-dependent head-related impulse responses (HRIRs). This set of HRIRs is often time-aligned in a pre-processing step, to allow for high-fidelity interpolation between HRIRs corresponding with neighbouring directions. The fidelity of this operation depends on the similarity of neighbouring aligned HRIRs. The pairwise quality of similarity makes it a difficult criterion to optimize globally and consequently one often resorts to alignment methods based on a specific feature that can be extracted for each HRIR separately, e.g., the first-onset of the peak or the group delay. However, such proxies for similarity are very sensitive to noise and therefore require a high signal-to-noise ratio, which makes them less suitable for processing HRIRs acquired outside an anechoic room. In this paper, we advance a novel alignment method, which maximizes the similarity – defined as the correlation between the full-length HRIRs – between neighbouring aligned HRIRs for all directions at once. We show that this correlation-based alignment procedure outperforms the first-onset alignment with regards to the fidelity of the spherical harmonics representation of both the spectral and interaural time difference (ITD) information, when tested on the KEMAR HRIR and six human HRIRs. Finally, we show that the correlation-based alignment is more robust to noise.

Abstract: Transmission electron microscopy (TEM) is a technique that uses an electron beam to analyze materials. This analysis is based on the interaction between the electron beam and the sample, such as photon emission and electron diffraction pattern, to name a few. Sample damage, however, also occurs when such interaction alters the structure of the sample. To ensure information from the undamaged material can be acquired, the electron expense to probe the material is thus limited. In this work, we propose efficient methods for acquiring and processing the information originating from the electron-sample interaction so that the study of the material and the conducting of the TEM experiment can be less hindered by the limited dose usage. In the first part of the work, the relationship between the scattering of the electron and the local physical property of the sample is studied. Based on this relationship, two reconstruction schemes are proposed capable of producing high-resolution images at low-dose conditions. Besides, the proposed reconstructions are not restricted to complete datasets but instead work on pieces of data, therefore allowing live feedback during data acquisition. Such feature of the methods allows the whole TEM experiment to be carried out under low dose conditions and thus further reduces possible beam damage on the studied material. In the second part of the work, we discuss our approach to modulating the electron beam and its benefits. An electrostatic device that can alter the wavefront of the passing electron wave is introduced and characterized. The beam-modulation ability is demonstrated by creating orthogonal beam sets, and applications that exploit the adaptability of the wave modulator are demonstrated with both simulation and experiments.

Abstract: Delve into the diverse aspects of plant morphology, their responses to global climate change, and the spatiotemporal dynamics of forest productivity. Join us on a journey through the intricate web of plant characteristics and their impact on the environment.

Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

Abstract: The EPS Antwerp Young Minds (AYM) invited Prof. Nir Navon (Yale University) to hold a colloquium for the physics department. For an audience of students and researchers, Prof. Navon presented recent advances in ultracold quantum matter and research from his own lab. His experimental work paves the way to make toy models used by theorists a reality. We sat down afterwards to discuss ultracold physics, box traps and setting up a lab from scratch.

Abstract: Supplementary information for the article “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” containing the videos of in-situ SEM imaging (mp4 files), raw data/images, and Jupyter notebooks (ipynb files) for data treatment and plots. Link to the preprint: https://doi.org/10.48550/arXiv.2308.15123 Explanation of the data files can be found in the Information.pdf file. The Videos folder contains the in-situ SEM image series mentioned in the paper. If there are any questions/bugs, feel free to contact me at lukas.grunewaldatuantwerpen.be

Abstract: Plasma-based CO2 conversion is worldwide gaining increasing interest. The aim of this work is to find potential pathways to improve the energy efficiency of plasma-based CO2 conversion beyond what is feasible for thermal chemistry. To do so, we use a combination of modeling and experiments to better understand the underlying mechanisms of CO2 conversion, ranging from non-thermal to thermal equilibrium conditions. Zero-dimensional (0D) chemical kinetics modelling, describing the detailed plasma chemistry, is developed to explore the vibrational kinetics of CO2, as the latter is known to play a crucial role in the energy efficient CO2 conversion. The 0D model is successfully validated against pulsed CO2 glow discharge experiments, enabling the reconstruction of the complex dynamics underlying gas heating in a pure CO2 discharge, paving the way towards the study of gas heating in more complex gas mixtures, such as CO2 plasmas with high dissociation degrees. Energy-efficient, plasma-based CO2 conversion can also be obtained upon the addition of a reactive carbon bed in the post-discharge region. The reaction between solid carbon and O2 to form CO allows to both reduce the separation costs and increase the selectivity towards CO, thus, increasing the energy efficiency of the overall conversion process. In this regard, a novel 0D model to infer the mechanism underlying the performance of the carbon bed over time is developed. The model outcome indicates that gas temperature and oxygen complexes formed at the surface of solid carbon play a fundamental and interdependent role. These findings open the way towards further optimization of the coupling between plasma and carbon bed. Experimentally, it has been demonstrated that “warm” plasmas (e.g. microwave or gliding arc plasmas) can yield very high energy efficiency for CO2 conversion, but typically only at reduced pressure. For industrial application, it will be important to realize such good energy efficiency at atmospheric pressure as well. However, recent experiments illustrate that the microwave plasma at atmospheric pressure is too close to thermal conditions to achieve a high energy efficiency. Hence, we use a comprehensive set of advanced diagnostics to characterize the plasma and the reactor performance, focusing on CO2 and CO2/CH4 microwave discharges. The results lead to a deeper understanding of the mechanism of power concentration with increasing pressure, typical of plasmas in most gases, which is of great importance for model validation and understanding of reactor performance.

Abstract: Farmers should increasingly adopt more water‐efficient irrigation technologies—such as drip irrigation—as a result of climate warming and aggravating water scarcity. We analyze how Italian farmers adapt to climate change by changing their irrigation technology mix. We apply a two‐stage econometric model to data from 5876 Italian farms. We find that farmers' initial reaction to increasing temperatures is reducing their surface‐irrigated fractions. When temperatures increase further, farmers switch toward more sprinkler irrigation. Our results show that farmers are not autonomously moving to drip irrigation in response to climate change, suggesting that government incentives are needed to encourage this transition.

Abstract: Climate models suggest that the persistence of summer precipitation regimes (PRs) is on the rise, characterized by both longer dry and longer wet durations. These PR changes may alter plant biochemical composition and thereby their economic and ecological characteristics. However, impacts of PR persistence have primarily been studied at the community level, largely ignoring the biochemistry of individual species. Here, we analyzed biochemical components of four grassland species with varying sensitivity to PR persistence (Holcus lanatus, Phleum pratense, Lychnis flos-cuculi, Plantago lanceolata) along a range of increasingly persistent PRs (longer consecutive dry and wet periods) in a mesocosm experiment. The more persistent PRs decreased nonstructural sugars, whereas they increased lignin in all species, possibly reducing plant quality. The most sensitive species Lychnis seemed less capable of altering its biochemical composition in response to altered PRs, which may partly explain its higher sensitivity. The more tolerant species may have a more robust and dynamic biochemical network, which buffers the effects of changes in individual biochemical components on biomass. We conclude that the biochemical composition changes are important determinants for plant performance under increasingly persistent precipitation regimes.

Abstract: New Cinema History broadened film studies by emphasising the complexity of cinema as a multifaceted phenomenon that includes the socio-economic context in which films were made, circulated, shown and received. As part of the digital turn, the discipline adopted computational methods and created quantitative research data to research this socio-economic context at scale. However, not all datasets created in this context adhere to FAIR principles, decreasing their reusability. By reconciling 14 cinema-related datasets, Cinema Belgica facilitates research into the history of Belgian cinema. This research paper documents and critically reflects on the choices made when selecting, modelling and reconciling information for the Cinema Belgica database.

Abstract: Land-tenure security is integral to local communities' socioeconomic development. It has been a center of debate in academia and for legislators and advocates to implement reforms to enhance efficient and sustainable development in land management. Yet, knowledge gaps remain in how various contract-farming regimes contribute to land-improvement investment and technical efficiency. This study used a data set of 650 farm households collected through a two-stage stratified sampling to investigate the influence of three contract-farming regimes: long-term, medium-term, and short-term contracts, on the land-improvement investment, productivity, and technical efficiency of contract farmers in Punjab, Pakistan. The study used multivariate probit and ordinary least square regression models to examine the posit relationships. The findings highlight that farmers with long-term land contracts have higher per hectare yield, income and profit than those with medium-term and short-term contracts. The results confirm that farmers with medium- and long-term contracts tend to invest more in land-improvement measures, i.e., organic and green manure. Further, the study findings demonstrate that long-term land tenures are more effective when farmers make decisions regarding the on-farm infrastructure, like tube-well installation, tractor ownership, and holding farm logistics. Last, the study results confirm that long-term contracts are more robust regarding technical efficiency. Moreover, the findings support the Marshallian inefficiency hypothesis and extend the literature on contract farming, land-improvement investment, and land use policy, and offer coherent policy actions for stakeholders to improve farmers' productivity, technical efficiency, and income.