Abstract: The global climate is changing, and farmers must increase their adaptive capacity to avoid negative impacts. This study aimed to examine the adaptive capacity of farmers’ household to tolerate climate changes and identify factors affecting the climate in Hamadan province, Iran. The adaptive capacity was evaluated quantitatively by using 23 indicators and was categorized into high, moderate, low, and very low adaptive capacity. The study was based on a cross sectional survey and was conducted with a random sample of 280 household farmers distributed in five counties of Hamadan province in the west of the country whose climatic data revealed signs of climate change. The result showed that farmers’ negative perception toward climate change generally increases during dry seasons and decreases when the precipitation and water resources are more available. Regarding the available information, only 15% of farmers had a high level of adaptive capacity, while 10% of them were highly adapted, and 27.5% showed a very low level of adaptive capacity. Adaptive capacity in the current study was influenced by some socio-economic variables including total farm size, irrigated farm size, number of agricultural land plots, and perception and knowledge of climate change.

Abstract: We address the nature of the disordered state that results from the adsorption of adatoms in graphene. For adatoms that sit at the center of the honeycomb plaquette, as in the case of most transition metals, we show that the ones that form a zero-energy resonant state lead to Anderson localization in the vicinity of the Dirac point. Among those, we show that there is a symmetry class of adatoms where Anderson localization is suppressed, leading to an exotic metallic state with large and rare charge droplets, that localizes only at the Dirac point. We identify the experimental conditions for the observation of the Anderson transition for adatoms in graphene.

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: Advances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the object of interest. If the materials and their spectral responses are known a priori, the image reconstruction step is rather straightforward. If they are not known, however, the maps as well as the responses need to be estimated jointly. A conventional workflow in spectral CT involves performing volume reconstruction followed by material decomposition, or vice versa. However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem. To resolve this issue, we propose 'A Dictionary-based Joint reconstruction and Unmixing method for Spectral Tomography' (ADJUST). Our formulation relies on forming a dictionary of spectral signatures of materials common in CT and prior knowledge of the number of materials present in an object. In particular, we decompose the spectral volume linearly in terms of spatial material maps, a spectral dictionary, and the indicator of materials for the dictionary elements. We propose a memory-efficient accelerated alternating proximal gradient method to find an approximate solution to the resulting bi-convex problem. From numerical demonstrations on several synthetic phantoms, we observe that ADJUST performs exceedingly well compared to other state-of-the-art methods. Additionally, we address the robustness of ADJUST against limited and noisy measurement patterns. The demonstration of the proposed approach on a spectral micro-CT dataset shows its potential for real-world applications. Code is available at https://github.com/mzeegers/ADJUST.

Abstract: We study the adsorption and desorption kinetics of interacting particles moving on a one-dimensional lattice. Confinement is introduced by limiting the number of particles on a lattice site. Adsorption and desorption are found to proceed at different rates, and are strongly influenced by the concentration-dependent transport diffusion. Analytical solutions for the transport and self-diffusion are given for systems of length 1 and 2 and for a zero-range process. In the last situation the self- and transport diffusion can be calculated analytically for any length.

Abstract: The adsorption of C and CHx radicals on anatase (001) was studied using DFT within the generalized gradient approximation using the Perde-Burke-Ernzerhof (PBE) functional. We have studied the influence of oxygen vacancies in and at the surface on the adsorption properties of the radicals. For the oxygen vacancies in anatase (001), the most stable vacancy is located at the surface. For this vacancy, the maximal adsorption strength of C and CH decreases compared to the adsorption on the stoichiometric surface, but it increases for CH2 and CH3. If an oxygen vacancy is present in the first subsurface layer, the maximal adsorption strength increases for C, CH, CH2, and CH3. When the vacancy is present in the next subsurface layer, we find that only the CH3 adsorption is enhanced, while the maximal adsorption energies for the other radical species decrease. Not only does the precise location of the oxygen vacancy determine the maximal adsorption interaction, it also influences the adsorption strengths of the radicals at different surface configurations. This determines the probability of finding a certain adsorption configuration at the surface, which in turn influences the possible surface reactions. We find that C preferentially adsorbs far away from the oxygen vacancy, while CH2 and CH3 adsorb preferentially at the oxygen vacancy site. A fraction of CH partially adsorbs at the oxygen vacancy, and another fraction adsorbs further away from the vacancy.

Abstract: Motivated by the recent realization of graphene sensors to detect individual gas molecules, we investigate the adsorption of H2O, NH3, CO, NO2, and NO on a graphene substrate using first-principles calculations. The optimal adsorption position and orientation of these molecules on the graphene surface is determined and the adsorption energies are calculated. Molecular doping, i.e., charge transfer between the molecules and the graphene surface, is discussed in light of the density of states and the molecular orbitals of the adsorbates. The efficiency of doping of the different molecules is determined and the influence of their magnetic moment is discussed.

Abstract: Adsorption of sulfide ions onto a surface of starch capped silver nanoparticles upon addition of thioacetamide was investigated. UVvis absorption spectroscopy revealed that the adsorption of the sulfide ion on the surface of the silver nanoparticles induced damping as well as blue shift of the silver surface plasmon resonance band. Further increase in thioacetamide concentration led to shift of the resonance band toward higher wavelengths indicating the formation of the continuous Ag2S layer on the silver surface. Thus fabricated nanoparticles were investigated using electron microscopy techniques (TEM, HRTEM, and HAADF-STEM) and X-ray photoelectron spectroscopy (XPS), which confirmed their coreshell structure.

Abstract: Last century the field of heritage sciences expanded beyond imagination. The inventions of X-ray radiography and infrared reflectography allowed experts to investigate paintings below the surface as well. More recent developments led to the advent of the field of hyperspectral imaging, to which the advanced chemical imaging methods, used in this thesis work, belong. These techniques not only allow to identify the components present in artworks, but also to visualize their distribution over these objects. The resulting distribution maps permit a broader public to interpret the scientific data and to relate these results with the artwork itself. During this thesis work a range of flat artworks were investigated in a non-destructive manner using mainly two macroscopic imaging techniques: macroscopic X-ray fluorescence scanning and macroscopic Fourier transformed mid-infrared scanning in reflectance mode. The resulting images were sometimes supplemented with microscopic techniques on a minute selection of samples to fully understand the layer build-up, composition and distribution of these materials over the stratigraphy. Illuminated manuscripts pushed the interpretation of the macroscopic imaging techniques: due to the impossibility of sampling, all answers had to be obtained non-destructively. Documenting masterpieces such as the Ghent Altarpiece by means of chemical imaging techniques, helped the restoration team, assisted by the international commission to make the daring decision of manually removing the non-original paint layers. Scanning stained-glass windows allowed experts to document the panels, create situation reports, identify later infills and guide the restoration process in a more efficient manner. By initially applying non-destructive imaging techniques, many of the research/conservation questions could already be answered. Based on the resulting distribution maps, only a very limited amount of sampling was required to obtain a representative set to answer the remaining questions. In most cases the combination of multiple methods was necessary to fully understand the situation. A similar trend could be seen in the research field: the collaboration between divergent disciples was often required in order to explain all observations. In order to completely break through, the scanning speed of these techniques has to increase even more in order to cover an acceptable surface in one workday. Parallel with the operational speed, the (basic) data treatment should also be streamlined more in order to allow a broader user group to access the results. Once these two improvements are carried out, these techniques become accessible to a larger public.

Abstract: Design and optimization of materials properties can only be performed through a thorough knowledge of the structure of the compound. In this feature article we illustrate the possibilities of advanced electron microscopy in materials science and solid state chemistry. The different techniques are briefly discussed and several examples are given where the structures of complex oxides, often with a modulated structure, have been solved using electron microscopy.

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: <script type='text/javascript'>document.write(unpmarked('We present an advanced method to study spin fluctuations in superconductors quantitatively and entirely from first principles. This method can be generally applied to materials where electron-phonon coupling and spin fluctuations coexist. We employ it here to examine the recently synthesized superconductor iron tetraboride (FeB4) with experimental T-c similar to 2.4 K [H. Gou et al., Phys. Rev. Lett, 111, 157002 (2013)]. We prove that FeB4 is particularly prone to ferromagnetic spin fluctuations due to the presence of iron, resulting in a large Stoner interaction strength, I = 1.5 eV, as calculated from first principles. The other important factor is its Fermi surface that consists of three separate sheets, among which two are nested ellipsoids. The resulting susceptibility has a ferromagnetic peak around q = 0, from which we calculated the repulsive interaction between Cooper pair electrons using the random phase approximation. Subsequently, we combined the electron-phonon interaction calculated from first principles with the spin fluctuation interaction in fully anisotropic Eliashberg theory calculations. We show that the resulting superconducting gap spectrum is conventional, yet very strongly depleted due to coupling to the spin fluctuations. The critical temperature decreases from T-c = 41 K, if they are not taken into account, to T-c = 1.7 K, in good agreement with the experimental value.'));