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: The number and composition of species in a community can be quantified with alpha-diversity indices, including species richness (R), Simpson's index (D), and the Shannon-Wiener index (HGREEK TONOS). In forest communities, there are large variations in tree size among species and individuals of the same species, which result in differences in ecological processes and ecosystem functions. However, tree size inequality (TSI) has been largely neglected in studies using the available diversity indices. The TSI in the diameter at breast height (DBH) data for each of 999 20 m x 20 m forest census quadrats was quantified using the Gini index (GI), a measure of the inequality of size distribution. The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat. We also examined the relationships of alpha-diversity indices with the GI using correlation tests. The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions, with most root-mean-square errors (990 out of 999 quadrats) being < 0.0030. There were significant positive correlations between each of three alpha-diversity indices (i.e., R, D, and H') and the GI. Nevertheless, the total abundance of trees in each quadrat did not significantly influence the GI. This means that the TSI increased with increasing species diversity. Thus, two new indices are proposed that can balance alpha-diversity against the extent of TSI in the community: (1 – GI) x D, and (1 – GI) x H'. These new indices were significantly correlated with the original D and HGREEK TONOS, and did not increase the extent of variation within each group of indices. This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities, especially in the face of cumulative species loss under global climate change.

Abstract: Single nucleotide point mutations in the KRAS oncogene occur frequently in human cancers, rendering them intriguing targets for diagnosis, early detection and personalized treatment. Current detection methods are based on polymerase chain reaction, sometimes combined with next-generation sequencing, which can be expensive, complex and have limited availability. Here, we propose a novel singlet oxygen (1O2)-based photoelectrochemical detection methodology for single-point mutations, using KRAS mutations as a case study. This detection method combines the use of a sandwich assay, magnetic beads and robust chemical photosensitizers, that need only air and light to produce 1O2, to ensure high specificity and sensitivity. We demonstrate that hybridization of the sandwich hybrid at high temperatures enables discrimination between mutated and wild-type sequences with a detection rate of up to 93.9%. Additionally, the presence of background DNA sequences derived from human cell-line DNA, not containing the mutation of interest, did not result in a signal, highlighting the specificity of the methodology. A limit of detection as low as 112 pM (1.25 ng/mL) was achieved without employing any amplification techniques. The developed 1O2-based photoelectrochemical methodology exhibits unique features, including rapidity, ease of use, and affordability, highlighting its immense potential in the field of nucleic acid-based diagnostics.

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: 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: 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: 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: Weak interlayer van der Waals (vdW) bonding has significant impact on the surface/interface structure, electronic properties, and transport properties of vdW layered materials. Unraveling the complex atomistic dynamics and structural evolution at vdW surfaces is therefore critical for the design and synthesis of the next-generation vdW layered materials. Here, we show that Ge/Bi cation diffusion along the vdW gap in layered GeBi2Te4 (GBT) can be directly observed using in situ heating scanning transmission electron microscopy (STEM). The cation concentration variation during diffusion was correlated with the local Te-6 octahedron distortion based on a quantitative analysis of the atomic column intensity and position in time-elapsed STEM images. The in-plane cation diffusion leads to out-of-plane surface etching through complex structural evolutions involving the formation and propagation of a non-centrosymmetric GeTe2 triple layer surface reconstruction on fresh vdW surfaces, and GBT subsurface reconstruction from a septuple layer to a quintuple layer. Our results provide atomistic insight into the cation diffusion and surface reconstruction in vdW layered materials. Weak interlayer van der Waals (vdW) bonding has significant impact on the structure and properties of vdW layered materials. Here authors use in-situ aberration-corrected ADF-STEM for an atomistic insight into the cation diffusion in the vdW gaps and the etching of vdW surfaces at high temperatures.

Abstract: Two-dimensional (2D) ultra-thin materials are more crucial than their bulk counterparts for the covalent functionalization of their surface owing to atomic thinness, large surface-to-volume ratio, and high reactivity of surface atoms having unoccupied orbitals. Since the surface of a 2D material is composed of atoms having unoccupied orbitals, covalent functionalization enables one to improve or precisely modify the properties of the ultra-thin materials. Chemical functionalization of 2D materials not only modifies their intrinsic properties but also makes them adapted for nanotechnology applications. Such engineered materials have been used in many different applications with their improved properties. In the present Perspective, we begin with a brief history of functionalization followed by the introduction of functionalized 2D materials. Our Perspective is composed of the following sections: the applications areas of 2D graphene and graphene oxide crystals, transition metal dichalcogenides, and in-plane anisotropic black phosphorus, all of which have been widely used in different nanotechnology applications. Finally, our Perspectives on the future directions of applications of functionalized 2D materials are given. The present Perspective sheds light on the current progress in nanotechnological applications of engineered 2D materials through surface functionalization.

Abstract: The highly tunable band structure of the zero-energy Landau level (zLL) of bilayer graphene makes it an ideal platform for engineering novel quantum states. However, the zero-energy Landau level at high electric fields has remained largely unexplored. Here we present magnetotransport measurements of bilayer graphene in high transverse electric fields. We observe previously undetected Landau level crossings at filling factors nu = -2, 1, and 3 at high electric fields. These crossings provide constraints for theoretical models of the zero-energy Landau level and show that the orbital, valley, and spin character of the quantum Hall states at high electric fields is very different from low electric fields. At high E, new transitions between states at nu = -2 with different orbital and spin polarization can be controlled by the gate bias, while the transitions between nu = 0 -> 1 and nu = 2 -> 3 show anomalous behavior.

Abstract: Recent experiments demonstrated that proton transport through graphene electrodes can be accelerated by over an order of magnitude with low intensity illumination. Here we show that this photo-effect can be suppressed for a tuneable fraction of the infra-red spectrum by applying a voltage bias. Using photocurrent measurements and Raman spectroscopy, we show that such fraction can be selected by tuning the Fermi energy of electrons in graphene with a bias, a phenomenon controlled by Pauli blocking of photo-excited electrons. These findings demonstrate a dependence between graphene's electronic and proton transport properties and provide fundamental insights into molecularly thin electrode-electrolyte interfaces and their interaction with light. Recent experiments have shown that proton transport through graphene electrodes can be promoted by light, but the understanding of this phenomenon remains unclear. Here, the authors report the electrical tunability of this photo-effect, showing a connection between graphene electronic and proton transport properties.

Abstract: Using atomistic magnetic simulations we investigate the soliton motion along a pinned skyrmion chain containing an interstitial skyrmion. We find that the soliton can exhibit stable motion along the chain without a skyrmion Hall effect for an extended range of drives. Under a constant drive the solitons have a constant velocity. We also measure the skyrmion velocity-current curves and identify the signatures of different phases including a pinned phase, stable soliton motion, and quasi-free motion at higher drives where all of the skyrmions depin from the pinning centers and move along the rigid wall. In the quasi-free motion regime, the velocity is oscillatory due to the motion of the skyrmions over the pinning sites. For increasing pinning strength, the onset of soliton motion shifts to higher values of current density. We also find that for stronger pinning, the characteristic velocity-current shape is affected by the annihilation of single or multiple skyrmions in the drive interval over which the soliton motion occurs. Our results indicate that stable skyrmion soliton motion is possible and that the solitons could be used as information carriers instead of the skyrmions themselves for technological applications.

Abstract: Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.