Abstract: Metal halide perovskite (MHP) quantum dots (QDs) offer immense potential for several areas of photonics research due to their easy and low-cost fabrication and excellent optoelectronic properties. However, practical applications of MHP QDs are limited by their poor stability and, in particular, their tendency to aggregate. Here, we develop a two-step double-solvent strategy to grow and confine CsPbBr3 QDs within the three-dimensional (3D) cavities of a mesoporous SBA-16 silica scaffold (CsPbBr3@SBA-16). Strong confinement and separation of the MHP QDs lead to a relatively uniform size distribution, narrow luminescence, and good ambient stability over 2 months. In addition, the CsPbBr3@SBA-16 presents a high activity and stability for visible-light-driven photocatalytic toluene C(sp(3))-H bond activation to produce benzaldehyde with similar to 730 mu mol g(-1) h(-1) yield rate and near-unity selectivity. Similarly, the structural stability of CsPbBr3@SBA-16 QDs is superior to that of both pure CsPbBr3 QDs and those confined in MCM-41 with 1D channels.

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: 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: During the past decades, metallic nanoparticles (NPs) have attracted great attention in materials science due to their specific optical properties based on surface plasmon resonances. Because of these phenomena, plasmonic NPs (or nanoplasmonics) are very promising for application in biosensing, photocatalysts, medicine, data storage, solar energy conversion, etc. Currently, colloidal synthesis techniques enable scientists to routinely produce mono and bimetallic NPs of various shapes, sizes, composition, and elemental distribution, with superior properties for plasmonic applications. Two primary directions for further advancing nanoplasmonic-based technologies include synthesizing novel morphologies, such as highly asymmetric chiral NPs, and gaining deeper insights into the factors affecting the stability of produced nanoplasmonics. With the increasing complexity of nanoplasmonics morphologies and higher stability requirements, there is a pressing need for thorough investigations into their 3D structures and their evolution under different conditions, with high resolution. Electron tomography (ET) emerges as an ideal tool to retrieve shape and element-sensitive information about individual nanoparticles in 3D, achieving resolutions down to the atomic level. Moreover, ET techniques can be combined with in situ holders, enabling detailed studies of processes mimicking real applications of nanoplasmonic-based devices. The first part of this thesis will focus on detailed studies of chiral Au NPs, promising for spectroscopy techniques based on the differential absorption of left- and right-handed circularly polarized light. Specifically, I will discuss the primary strategies for wet-colloidal growth of the various types of intrinsically chiral Au NPs. Advanced ET methods will be demonstrated as powerful tools for characterizing the final helical morphologies of the produced Au NPs and for studying the chiral growth mechanisms by examining intermediate structures obtained during chiral growth. The second part will focus on the heat-induced stability of various Au@Ag core-shell NPs. Operating in real conditions, such as elevated temperatures, may cause particle reshaping and redistribution of metals between the core and shell, gradually altering nanoplasmonics properties. Hence, a thorough understanding of the influence of size, shape, and defects on these processes is crucial for further developments. Recently developed techniques, combining fast ET with in-situ heating holders, have allowed me to evaluate the influence of various parameters (size, shape, defect structure) on heat-induced elemental redistribution in Au@Ag core-shell nanoparticles qualitatively and quantitatively. Additionally, I will discuss the prospects of high-resolution ET for visualizing the diffusion of individual atoms within complex nanostructures.

Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.

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: The safe and efficient use of hydrogen energy, which is in high demand worldwide today, requires efficient hydrogen storage. Despite significant advances in hydrogen storage using carbon-based nanomaterials, including carbon nanotubes (CNTs), efforts to substantially increase the storage capacity remain less effective. In this work, we demonstrate the effect of endohedral transition metal atoms on the hydrogen storage capacity of CNTs using reactive molecular dynamics simulations. We find that an increase in the volume fraction of endohedral nickel atoms leads to an increase in the concentration of physisorbed hydrogen molecules around single-walled CNTs (SWNTs) by approximately 1.6 times compared to pure SWNTs. The obtained results provide insight into the underlying mechanisms of how endohedral transition metal atoms enhance the hydrogen storage ability of SWNTs under nearly ambient conditions.

Abstract: Recent experiments have revealed that the macroscopic Kelvin equation remains surprisingly accurate even for nanoscale capillaries. This phenomenon was so far explained by the oscillatory behavior of the solid−liquid interfacial free energy. We here demonstrate thermodynamic and capillarity inconsistencies with this explanation. After revising the Kelvin equation, we ascribe its validity at nanoscale confinement to the effect of disjoining pressure.
To substantiate our hypothesis, we employed molecular dynamics simulations to evaluate interfacial heat transfer and wetting properties. Our assessments unveil a breakdown in a previously established proportionality between the work of adhesion and the Kapitza conductance at capillary heights below 1.3 nm, where the dominance of the work of adhesion shifts primarily from energy to entropy. Alternatively, the peak density of the initial water layer can effectively probe the work of adhesion. Unlike under bulk conditions, high confinement renders the work of adhesion entropically unfavorable.

Abstract: The interplay between a magnetic field and the Coulomb potential from a charged vacancy on the electron states in graphene is investigated within the tight-binding model. The Coulomb potential removes locally Landau level degeneracy, while the vacancy introduces a satellite level next to the normal Landau level. These satellite levels are found throughout the positive-energy region, but in the negative-energy region, they turn into atomic collapse resonances. Crossings between Landau levels with different angular quantum number m are found. Unlike the point impurity system in which an anticrossing occurs between Landau levels of the same m, in this work anticrossing is found between the normal Landau level and the vacancy-induced level. The atomic collapse resonance hybridizes with the Landau levels. The charge at which the lowest Landau level m = -1, N = 1 crosses E = 0 increases with enhancing magnetic field. A Landau level scaling anomaly occurs when the charge is larger than the critical charge beta 0.6 and this critical charge is independent of the magnetic field.

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: In nature, the two-dimensional (2D) profiles of fruits from many plants often resemble ellipses. However, it remains unclear whether these profiles strictly adhere to the ellipse equation, as many natural shapes resembling ellipses are actually better described as superellipses. The superellipse equation, which includes an additional parameter n compared to the ellipse equation, can generate a broader range of shapes, with the ellipse being just a special case of the superellipse. To investigate whether the 2D profiles of fruits are better described by ellipses or superellipses, we collected a total of 751 mature and undamaged fruits from 31 naturally growing plants of Cucumis melo L. var. agrestis Naud. Our analysis revealed that most adjusted root-mean-square errors (> 92% of the 751 fruits) for fitting the superellipse equation to the fruit profiles were consistently less than 0.0165. Furthermore, there were 638 of the 751 fruits (ca. 85%) with the 95% confidence intervals of the estimated parameter n in the superellipse equation not including 2. These findings suggest that the profiles of C. melo var. agrestis fruits align more closely with the superellipse equation than with the ellipse equation. This study provides evidence for the existence of the superellipse in fruit profiles, which has significant implications for studying fruit geometries and estimating fruit volumes using the solid of revolution formula. Furthermore, this discovery may contribute to a deeper understanding of the mechanisms driving the evolution of fruit shapes.

Abstract: Fine roots mediate plant nutrient acquisition and growth. Depending on soil nutrient availability, plants can regulate fine root biomass and morphological traits to optimise nutrient acquisition. Little is known, however, about the importance of these parameters influencing forest functioning. In this study, we measured root responses to nutrient additions to gain a mechanistic understanding of plant adaptations to nutrient limitation in two tropical forests in French Guiana, differing twofold in their soil nutrient statuses. We analysed the responses of root biomass, mean root diameter (RD), specific root length (SRL), specific root area (SRA), root tissue density (RTD) and carbon (C), nitrogen (N) and phosphorus (P) concentrations in roots down to 15 cm soil depth after three years of N and P additions. At the lower-fertility site Paracou, no changes in root biomass or morphological traits were detected with either N or P addition, although P concentrations in roots increased with P addition. In the higher fertility site, Nouragues, root biomass and P concentrations in roots increased with P addition, with no changes in morphological traits. In contrast, N addition shifted root traits from acquisitive to more conservative by increasing RTD. A significant interaction between N and P in Nouragues pointed to stronger responses to P addition in the absence of N. Our results suggest that the magnitude and direction of root biomass and trait expression were regulated by soil fertility, corroborated by the response to N or P additions. At low fertility sites, we found lower plasticity in root trait expression compared to more fertile conditions, where N and P additions caused stronger and antagonistic responses. Identifying the exact role of mechanisms affecting root nutrient uptake in Amazon forests growing in different soils will be crucial to foresee if and how rapid global changes can affect their carbon allocation.

Abstract: To support experimental research into gas conversion by warm plasmas, models should be developed to explain the experimental observations. These models need to describe all physical and chemical plasma properties in a coupled way. In this paper, we present a modelling approach to solve the complete set of assumed relevant equations, including gas flow, heat balance and species transport, coupled with a rather extensive chemistry set, consisting of 21 species, obtained by reduction of a more detailed chemistry set, consisting of 41 species. We apply this model to study the combined CO2 and CH4 conversion in the presence of O2, in a direct current atmospheric pressure glow discharge. Our model can predict the experimental trends, and can explain why higher O2 fractions result in higher CH4 conversion, namely due to the higher gas temperature, rather than just by additional chemical reactions. Indeed, our model predicts that when more O2 is added, the energy required to reach any set temperature (i.e., the enthalpy) drops, allowing the system to reach higher temperatures with similar amounts of energy. This is in turn related to the higher H2O fraction and lower H2 fraction formed in the plasma, as demonstrated by our model. Altogether, our new self-consistent model can capture the main physics and chemistry occurring in this warm plasma, which is an important step towards predictive modelling for plasma-based gas conversion.

Abstract: The use of microfluidic devices in the field of plasma-liquid interaction can unlock unique possibilities to investigate the effects of plasma-generated reactive species for environmental and biomedical applications. So far, very little simulation work has been performed on microfluidic devices in contact with a plasma source. We report on the modelling and computational simulation of physical and chemical processes taking place in a novel plasma-microfluidic platform. The main production and transport pathways of reactive species both in plasma and liquid are modelled by a novel modelling approach that combines 0D chemical kinetics and 2D transport mechanisms. This combined approach, applicable to systems where the transport of chemical species occurs in unidirectional flows at high Péclet numbers, decreases calculation times considerably compared to regular 2D simulations. It takes advantage of the low computational time of the 0D reaction models while providing spatial information through multiple plug-flow simulations to yield a quasi-2D model. The gas and liquid flow profiles are simulated entirely in 2D, together with the chemical reactions and transport of key chemical species. The model correctly predicts increased transport of hydrogen peroxide into the liquid when the microfluidic opening is placed inside the plasma effluent region, as opposed to inside the plasma region itself. Furthermore, the modelled hydrogen peroxide production and transport in the microfluidic liquid differs by less than 50% compared with experimental results. To explain this discrepancy, the limits of the 0D–2D combined approach are discussed.