Abstract: The superconducting properties of two recently synthesized ternary silicides with unit formula X₄CoSi (X = Nb, Ta) are investigated through ab initio calculations combined with Eliashberg theory. Interestingly, their crystal structure comprises interlocking honeycomb networks of Nb/Ta atoms. Nb₄CoSi is found to harbor better conditions for phonon-mediated superconductivity, as it possesses a higher density of states at the Fermi level, fostering stronger electron-phonon coupling. The superconducting critical temperatures (T_c) follow the same trend, with Nb₄CoSi having a twice higher value than Ta₄CoSi. Furthermore, the calculated T_c values (5.9 K vs 3.1 K) agree excellently with the experimentally obtained ones, establishing superconductivity in this new materials class as mediated by the electron-phonon coupling. Furthermore, my calculations show that the superconducting properties of these compounds do not simply correlate with the parameters of their honeycomb networks, contrary to proposals raised in the literature. Rather, their complete fermiology and phonon spectrum should be taken into account in order to explain their respective superconducting properties.

Abstract: Plasma is considered one of the promising technologies to solve greenhouse gas problems, as it can activate CO2 and CH4 at relatively low temperatures. Among the various types of plasmas, the gliding arc plasmatron (GAP) is promising, as it has a high level of non-equilibrium and high electron density. Nevertheless, the conversion of CO2 and CH4 in the GAP reactor is limited. Therefore, combining the GAP reactor with catalysts and making use of the heat produced by the plasma to provide thermal energy to the catalyst, forming a post-plasma catalytic (PPC) system, is hypothesized to improve its performance. Therefore, in this PhD research, we investigate important aspects of the PPC concept towards the use of the heat produced by GAP plasma to heat the plasma bed, without additional energy input. Aiming at this, based on a literature study (chapter 1), Ni-loaded layered double hydroxide (LDH) derived catalyst with good thermal catalytic DRM performance were chosen as the catalyst material. Before applying the LDH as a support material, the rehydration property of calcined LDH in moist and liquid environment was studied as part of chapter 2. The data indicated that after high temperatures calcination (600-900 C), the obtained layered double oxides (LDOs) can rehydrate into LDH, although, the rehydrated LDH were different from the original LDH. In chapter 3, different operating conditions, such as gas flow rate, gas compositions (e.g. CH4/CO2 ratio and nitrogen dilution), and addition of H2O were studied to investigate optimal conditions for PPC DRM, identifying possible differences in temperature profiles and exhaust gas compositions that might influence the catalytic performance. Subsequently, the impact of different PPC configurations, making use of the heat and exhaust gas composition produced by the GAP plasma, is shown in Chapter 4. Experiments studying the impact of adjusting the catalyst bed distance to the post-plasma, the catalyst amount, the influence of external heating (below 250 C) and the addition of H2O are discussed. As only limited improvement in the performance was achieved, a new type of catalyst bed was designed and utilized, as described in chapter 5. This improved configuration can realize better heat and mass transfer by directly connecting to the GAP device. The performance was improved and became comparable to the traditional thermal catalytic DRM results obtained at 800 C, although obtained by a fully electrically driven plasma.

Abstract: 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 hyperspectral dataset of intimate mineral powder mixtures by homogeneously mixing five different clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide). In total 325 samples were prepared. Among the 325 samples, 60 mixtures were binary, 150 were ternary, 100 were quaternary, and 15 were quinary. For each mixture (and pure clay powder), reflectance spectra are acquired by 13 different sensors, with a broad wavelength range between the visible and the long-wavelength infrared regions (i.e., between 350 nm and 15385 nm) and with a large variation in sensor types, platforms, and acquisition conditions. We will make this dataset public, to be used by the community for the validation of nonlinear unmixing methodologies (https://github.com/VisionlabUA/Multisensor_datasets)

Abstract: Matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has become a powerful method to extract spatially resolved chemical information in complex materials. This study provides the first use of MALDI-MSI to define spatial–temporal changes in oil paints. Due to the highly heterogeneous nature of oil paints, the sample preparation had to be optimized to prevent molecules from delocalizing. Here, we present a new protocol for the layer-specific analysis of oil paint cross sections achieving a lateral resolution of 10 μm and without losing ionization efficiency due to topographic effects. The efficacy of this method was investigated in oil paint samples containing a mixture of two historic organic pigments, geranium lake and lead white, a mixture often employed in the work of painter Vincent Van Gogh. This methodology not only allows for spatial visualization of the molecules responsible for the pink hue of the paint but also helps to elucidate the chemical changes behind the discoloration of paintings with this composition. The results demonstrate that this approach provides valuable molecular compositional information about the degradation pathways of pigments in specific paint layers and their interaction with the binding medium and other paint components and with light over time. Since a spatial correlation between molecular species and the visual pattern of the discoloration pattern can be made, we expect that mass spectrometry imaging will become highly relevant in future degradation studies of many more historical pigments and paints.

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: Dry deposition is an important process determining pollutant concentrations, especially when studying the influence of urban green infrastructure on particulate matter (PM) levels in cities. Computational fluid dynamics (CFD) models of PM capture by vegetation are useful tools to increase their applicability. The meso-scale models of Zhang et al. (Atmos Environ 35:549-560, 2001) and Petroff and Zhang (Geosci Model Dev 3(2):753-769, 2010) have often been adopted in CFD models, however a comparison of these models with measurements including all PM particle sizes detrimental to health has been rarely reported and certainly not for green wall species. This study presents dry deposition experiments on real grown Hedera helix in a wind tunnel setup with wind speeds from 1 to 4 m s(-1) and PM consisting of a mixture of soot (0.02 – 0.2 mu mu m) and dust particles (0.3 – 10 mu mu m). Significant factors determining the collection efficiency (%) were particle diameter and wind speed, but relative air humidity and the type of PM (soot or dust) did not have a significant influence. Zhang's model outperformed Petroff's model for particles < 0.3 mu mu m, however the inclusion of turbulent impaction in Petroff's model resulted in better agreement with the measurements for particles > 2 – 3 mu mu m. The optimised model had an overall root-mean-square-error of similar to 4% for collection efficiency (CE) and 0.4 cm s-1 for deposition velocity (nu d), which was shown to be highly competitive against previously described models. It can thus be used to model PM deposition on other plant species, provided the correct parameterisation of the drag by this species. A detailed description of the spatial distribution of the vegetation could solve the underestimation for particle sizes of 0.3 – 2 mu mu m.

Abstract: Cold atmospheric plasma (CAP) is a source of cell‐damaging oxidant molecules that may be used as low‐cost cancer treatment with minimal side effects. Liquids treated with cold plasma and enriched with oxidants are a modality for non‐invasive treatment of internal tumors with cold plasma via injection. However, liquids are easily diluted with body fluids which impedes high and localized delivery of oxidants to the target. As an alternative, plasma‐treated hydrogels (PTH) emerge as vehicles for the precise delivery of oxidants. This study reports an optimal protocol for the preparation of injectable alginate PTH that ensures the preservation of plasma‐generated oxidants. The generation, storage, and release of oxidants from the PTH are assessed. The efficacy of the alginate PTH in cancer treatment is demonstrated in the context of cancer cell cytotoxicity and immunogenicity–release of danger signals and phagocytosis by immature dendritic cells, up to now unexplored for PTH. These are shown in osteosarcoma, a hard‐to‐treat cancer. The study aims to consolidate PTH as a novel cold plasma treatment modality for non‐invasive or postoperative tumor treatment. The results offer a rationale for further exploration of alginate‐based PTHs as a versatile platform in biomedical engineering.

Abstract: We present a 48-element programmable phase plate for coherent electron waves produced by a combination of photolithography and focused ion beam. This brings the highly successful concept of wavefront shaping from light optics into the realm of electron optics and provides an important new degree of freedom to prepare electron quantum states. The phase plate chip is mounted on an aperture rod placed in the C2 plane of a transmission electron microscope operating in the 100-300 kV range. The phase plate's behavior is characterized by a Gerchberg-Saxton algorithm, showing a phase sensitivity of 0.075 rad/mV at 300 kV, with a phase resolution of approximately 3x10e−3π. In addition, we provide a brief overview of possible use cases and support it with both simulated and experimental results.

Abstract: A portable and highly sensitive sensor was designed for the specific detection of 3,4-methyl-enedioxy-methamphetamine (MDMA), in a range of field-testing situations. The sensor can detect MDMA in street samples, even when other controlled substances drugs, or adulterants are present. In this work, we report for the first time a sensor using electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA and then produced using solid phase synthesis. A composite comprising chitosan, reduced graphene oxide, and molecularly imprinted polymer nanoparticles synthesized for MDMA for the first time was immobilized on screen-printed carbon electrodes. The sensors displayed a satisfactory sensitivity (106.8 nA x mu M-1), limit of detection (1.6 nM; 0.31 ng/mL), and recoveries (92-99%). The accuracy of the results was confirmed through validation using Ultra-High Performance Liquid Chromatography coupled with tandem Mass Spectrometry (UPLC-MS/MS). This technology could be used in forensic analysis and make it possible to selectively detect MDMA in street samples. A highly sensitive and portable sensor has been developed to detect MDMA in street samples. It uses electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA, which were immobilized on screen-printed carbon electrodes with chitosan and graphene. The sensor showed good sensitivity and satisfactory recoveries (92-99%), confirmed with UPLC-MS/MS validation. This technology has the potential to be used in forensic analysis.image

Abstract: LNMO (LiNi0.5Mn1.5O4-delta) is a high-energy density positive electrode material for lithium ion batteries. Unfortunately, it suffers from capacity loss and impedance rise during cycling due to electrolyte oxidation and electrode/electrolyte interface instabilities at high operating voltages. Here, a solution-gel synthesis route was used to coat 0.5-2.5 mu m LNMO particles with amorphous Li-Ti-O (LTO) for improved Li conduction, surface structural stability and cyclability. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) analysis coupled with energy dispersive X-ray (EDX) showed Ti-rich amorphous coatings/islands or Ti-rich spinel layers on many of the LTO-modified LNMO facets, with a thickness varying from about 1 to 10 nm. The surface modification in the form of amorphous islands was mostly possible on high-energy crystal facets. Physicochemical observations were used to propose a molecular mechanism for the surface modification, combining insights from metalorganic chemistry with the crystallographic properties of LNMO. The improvements in functional properties were investigated in half cells. The cell impedance increased faster for the bare LNMO compared to amorphous LTO modified LNMO, resulting in R-ct values as high as 1247 Omega (after 1000 cycles) for bare LNMO, against 216 Omega for the modified material. At 10C, the modified material boosted a 15% increase in average discharge capacity. The improvements in electrochemical performance were attributed to the increase in electrochemically active surface area, as well as to improved HF-scavenging, resulting in the formation of protective byproducts, generating a more stable interface during prolonged cycling.

Abstract: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Abstract: Metal nanocrystals (NCs) display unique physicochemical features that are highly dependent on nanoparticle dimensions, anisotropy, structure, and composition. The development of synthesis methodologies that allow us to tune such parameters finely emerges as crucial for the application of metal NCs in catalysis, optical materials, or biomedicine. Here, we describe a synthetic methodology to fabricate hollow multimetallic heterostructures using a combination of seed-mediated growth routes and femtosecond-pulsed laser irradiation. The envisaged methodology relies on the coreduction of Ag and Pd ions on gold nanorods (Au NRs) to form Au@PdAg core-shell nanostructures containing small cavities at the Au-PdAg interface. The excitation of Au@PdAg NRs with low fluence femtosecond pulses was employed to induce the coalescence and growth of large cavities, forming multihollow anisotropic Au@PdAg nanostructures. Moreover, single-hollow alloy AuPdAg could be achieved in high yield by increasing the irradiation energy. Advanced electron microscopy techniques, energy-dispersive X-ray spectroscopy (EDX) tomography, X-ray absorption near-edge structure (XANES) spectroscopy, and finite differences in the time domain (FDTD) simulations allowed us to characterize the morphology, structure, and elemental distribution of the irradiated NCs in detail. The ability of the reported synthesis route to fabricate multimetallic NCs with unprecedented hollow nanostructures offers attractive prospects for the fabrication of tailored high-entropy alloy nanoparticles.

Abstract: Superstructures with nanoscale building blocks, when coupled with precise control of the constituent units, open opportunities in rationally designing and manufacturing desired functional materials. Yet, synthetic strategies for the large-scale production of superstructures are scarce. We report a scalable and generalized approach to synthesizing superstructures assembled from atomically precise Ce24O28(OH)8 and other rare-earth metal-oxide nanoclusters alongside a detailed description of the self-assembly mechanism. Combining operando small-angle X-ray scattering, ex situ molecular and structural characterizations, and molecular dynamics simulations indicates that a high-temperature ligand-switching mechanism, from oleate to benzoate, governs the formation of the nanocluster assembly. The chemical tuning of surface ligands controls superstructure disassembly and reassembly, and furthermore, enables the synthesis of multicomponent superstructures. This synthetic approach, and the accurate mechanistic understanding, are promising for the preparation of superstructures for use in electronics, plasmonics, magnetics and catalysis. Synthesizing superstructures with precisely controlled nanoscale building blocks is challenging. Here the assembly of superstructures is reported from atomically precise Ce24O28(OH)8 and other rare-earth metal-oxide nanoclusters and their multicomponent combinations. A high-temperature ligand-switching mechanism controls the self-assembly.

Abstract: The development of coatings with tunable performances is critical to meet a wide range of technological applications each one with different requirements. Using the plasma-enhanced chemical vapor deposition (PECVD) process, scientists can create hydrogenated amorphous carbon coatings doped with metal (a-C:H:Me) with a broad range of mechanical properties, varying from those resembling polymers to ones resembling diamond. These diverse properties, without clear relations between the different families, make the material selection and optimization difficult but also very rich. An innovative approach is proposed here based on projected performance indices related to fracture energy, strength, and stiffness in order to classify and optimize a-C:H:Me coatings. Four different a-C:H:Cr coatings deposited by PECVD with Ar/C2H2 discharge under different bias voltage and pressures are investigated. A path is found to produce coatings with a selective critical energy release rate between 5–125 J/m2 without compromising yield strength (1.6–2.7 GPa) and elastic limit (≈0.05). Finally, fine-tuned coatings are categorized to meet desired applications under different testing conditions.