Abstract: This study reports the low temperature and low pressure conversion (up to 160 °C, p = 3.5 bar) of CO2 and H2 to CO using plasmonic Au/TiO2 nanocatalysts and mildly concentrated artificial sunlight as the sole energy source (up to 13.9 kW·m-2 = 13.9 suns). To distinguish between photothermal and non-thermal contributors, we investigated the impact of the Au nanoparticle size and light intensity on the activity and selectivity of the catalyst. A comparative study between P25 TiO2-supported Au nanocatalysts of a size of 6 nm and 16 nm displayed a 15 times higher activity for the smaller particles, which can only partially be attributed to the higher Au surface area. Other factors that may play a role are e.g., the electronic contact between Au and TiO2 and the ratio between plasmonic absorption and scattering. Both catalysts displayed ≥84% selectivity for CO (side product is CH4). Furthermore, we demonstrated that the catalytic activity of Au/TiO2 increases exponentially with increasing light intensity, which indicated the presence of a photothermal contributor. In dark, however, both Au/TiO2 catalysts solely produced CH4 at the same catalyst bed temperature (160 °C). We propose that the difference in selectivity is caused by the promotion of CO desorption through charge transfer of plasmon generated charges (as a non-thermal contributor).

Abstract: Bamboo is an important component in subtropical and tropical forest communities. The plant has characteristic long lanceolate leaves with parallel venation. Prior studies have shown that the leaf shapes of this plant group can be well described by a simplified version (referred to as SGE-1) of the Gielis equation, a polar coordinate equation extended from the superellipse equation. SGE-1 with only two model parameters is less complex than the original Gielis equation with six parameters. Previous studies have seldom tested whether other simplified versions of the Gielis equation are superior to SGE-1 in fitting empirical leaf shape data. In the present study, we compared a three-parameter Gielis equation (referred to as SGE-2) with the two-parameter SGE-1 using the leaf boundary coordinate data of six bamboo species within the same genus that have representative long lanceolate leaves, with >300 leaves for each species. We sampled 2000 data points at approximately equidistant locations on the boundary of each leaf, and estimated the parameters for the two models. The root–mean–square error (RMSE) between the observed and predicted radii from the polar point to data points on the boundary of each leaf was used as a measure of the model goodness of fit, and the mean percent error between the RMSEs from fitting SGE-1 and SGE-2 was used to examine whether the introduction of an additional parameter in SGE-1 remarkably improves the model’s fitting. We found that the RMSE value of SGE-2 was always smaller than that of SGE-1. The mean percent errors among the two models ranged from 7.5% to 20% across the six species. These results indicate that SGE-2 is superior to SGE-1 and should be used in fitting leaf shapes. We argue that the results of the current study can be potentially extended to other lanceolate leaf shapes.

Abstract: Geotourism is a sustainable type of tourism that focuses on the geological and geomorphological heritages of an area, and the associated cultural and biodiversity features. Though the popularity of geotourism is rapidly growing, research on the demand side, particularly on segmenting tourists to geosites and understanding their profiles, is limited. This obviously makes the designing of effective tourism policies that aim at developing geotourism sustainably very difficult. Hence, the main objectives of this study were to segment and profile tourists to geosites based on the benefits sought, and to show its implications for sustainable development of geotourism. With a survey of 415 tourists, this study clustered tourists to geosites in the southern Lake Tana region in Ethiopia based on the benefits sought. A factor-cluster method was applied to segment the tourists. The study identified four distinct segments: Activity-Nature Lovers, Culture Lovers, Nature-Culture Lovers, and Want-It-Alls. These segments differed in their demographic, trip, and behavioral characteristics. The findings implied that for sustainable development, destination managers and marketers need to customize their geotourism product development and marketing strategies based on the needs and characteristics of each market segment.

Abstract: The Lamé curve is an extension of an ellipse, the latter being a special case. Dr. Johan Gielis further extended the Lamé curve in the polar coordinate system by introducing additional parameters (n1, n2, n3; m): rφ=1Acosm4φn2+1Bsinm4φn3−1/n1, which can be applied to model natural geometries. Here, r is the polar radius corresponding to the polar angle φ; A, B, n1, n2 and n3 are parameters to be estimated; m is the positive real number that determines the number of angles of the Gielis curve. Most prior studies on the Gielis equation focused mainly on its applications. However, the Gielis equation can also generate a large number of shapes that are rotationally symmetric and axisymmetric when A = B and n2 = n3, interrelated with the parameter m, with the parameters n1 and n2 determining the shapes of the curves. In this paper, we prove the relationship between m and the rotational symmetry and axial symmetry of the Gielis curve from a theoretical point of view with the condition A = B, n2 = n3. We also set n1 and n2 to take negative real numbers rather than only taking positive real numbers, then classify the curves based on extremal properties of r(φ) at φ = 0, π/m when n1 and n2 are in different intervals, and analyze how n1, n2 precisely affect the shapes of Gielis curves.

Abstract: Vertical integration is a means of increasing market power. For some agricultural products, it is easier for farmers to exert control over their product beyond the farm gate, but for others it is more difficult. Cases in the latter category have two main characteristics. First, the farmer cannot sell the respective product to final consumers without processing. Second, processing is capital-intensive. Consequently, farmers have limited sales channels, and vertical integration of the supply chain is complex and challenging. It implies cooperation among farmers to process the raw material at a profitable scale and to finance the installation of processing facilities. Thus, for these product categories, farmers are prone to market power issues, since they depend on private businesses that have the financial means to install processing facilities and the logistical capacities to organize the collection of large amounts of raw material. This paper aims to identify and analyze the role of supply chain integration for farmers who are already cooperating horizontally. Two case studies serve as the basis for the analysis: sugar beet in Flanders, Belgium, and oilseed rape in Hessen, Germany. The analysis is based on a qualitative research approach combining interviews, focus groups, and workshops with farmers and processors. While for sugar beet, the effects of market power are emerging only now with the termination of the quota system, farmers growing oilseed rape have been experiencing these problems since the 1990s. Our analysis concludes that most strategies to maintain or improve farm income have been exhausted. Even various forms of vertical integration supported by European policies do not necessarily work as a successful strategy.

Abstract: The interaction of diatoms with sunlight is fundamental in order to deeply understand their role in terrestrial ecology and biogeochemistry, essentially due to their massive contribution to global primary production through photosynthesis and its e↵ect on carbon, oxygen and silicon cycles. Following the journey of light through natural waters, its propagation through the intricate frustule micro- and nano-structure and, finally, its fate inside the photosynthetic machinery of the living cell requires several mathematical and computational models in order to accurately describe all the involved phenomena taking place at di↵erent space scales and physical regimes. In this chapter, we review the main analytical models describing the underwater optical field, the essential numerical algorithms for the study of photonic properties of the diatom frustule seen as a natural metamaterial, as well as the principal models describing photon harvesting in diatom plastids and methods for complex EM propagation problems and wave propagation in dispersive materials with multiple relaxation times. These mathematical methods will be integrated in a unifying geometric perspective.

Abstract: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.

Abstract: This piece of work is twofold. First, the time evolution of wave-packets in 2D systems is analyzed by the Split-Operator technique in three different scenarios: in multilayer phosphorene, the transient oscillations in the time-dependent average of position and momentum were observed due to the zitterbewegung effect, and the wave packet propagates non-uniformly along the space deforming itself into an elliptical shape. These results were corroborated by the Green’s function formalism except for large values of the wave-vector and long times; in 2D semiconductor quantum wires (QWs) with anisotropic effective masses and different angle orientations with respect to the anisotropic axis. We have shown that the greater this angle, the smaller is the energy levels spacing implying in an increase of the accessible electronic states. Additionally, for non-null magnetic field, the quantum Hall edge states are significantly affected by the edge orientation. In the anisotropic case damped oscillations in the average values of velocity in both x and y directions where obtained. Theses oscillations are originated by the QW geometry but also from subwavepackets with different momentum orientations, whereas for isotropic QWs the wavepacket disperses without splitting; in the third scenario the split-operator technique was used to study the Landau levels, the wave packet trajectories and velocities of electrons in graphene at low-energy regime described by a modified Dirac equation where the momentum-operator is written in a generalized form as result of applying the position-dependent translation operator formalism (PDTO). In the second part of this thesis, the electronic and tunneling properties of α − T3 lattices were studied. Electrons in these lattices behave analogous to integer-spin Dirac Fermions. The presence of a third atomic site in the unit cell leads to a flat band in the energy spectrum, providing unique electronic and tunneling properties. The presence of a super-periodic potential and the inclusion of symmetry-breaking terms results in deviations of the atomic equivalence between the atomic sites affecting the Dirac points and the band-gap. Small deviations in the equivalence between the atomic sites and the number of barriers change the transmission properties in these lattices. Additionally, new tunneling regions are possible by adjusting the symmetry between the atomic sites and affect the omnidirectional total transmission called super-Klein tunneling observed in these lattices. We compare those results to the tunneling probabilities through regions where the energy spectrum changes from linear with a middle flat band to a hyperbolic dispersion.

Abstract: Ever since the industrial revolution, the emission of greenhouse gasses dramatically increased, resulting in high CO2 concentration in the atmosphere. The electrochemical conversion of CO2 to value added products, such as carbon monoxide, formic acid, methane, ethylene and ethanol is a very promising strategy to inhibit CO2 emissions. Nevertheless, at the moment, the electrochemical CO2 reduction (eCO2R) is not yet industrially viable, mainly due to the lack of good electrocatalysts. On the other hand, core-shell nanoparticles (NPs) have emerged over the last couple of years as promising candidates. It is believed that bimetallic enhancement effects are behind the improved performance of these core-shell NPs when compared to the individual metals. Although widely investigated, there are still some remaining issues and/or open questions. Indeed, the development of a robust and straightforward synthesis method along with fundamental insight into their resistance towards electrochemical stress remains absent. A good control over morphology, size and composition is key in determining which properties are beneficial for the eCO2R. Since these catalysts are designed to be implemented in electrolyzers, they have to maintain long-term performance. This makes the design of a reproducible method, unveiling structure-performance relationships the effect of electrochemical stress, a crucial aspect. Exploring and modifying existing synthesis methods, have led to the acquisition of a robust and reproducible synthesis method where thermal decomposition of the Cu core is combined with the galvanic replacement of Ag in organic solvents. The implementation of this method has led to the design of a wide variety of Cu-Ag bimetallic NPs and enabled to investigate their composition-selectivity profile. Introducing Ag on Cu suppressed hydrogen and increased the CO formation. CO production was boosted by using Cu@Ag core-shells and was promoted even more by changing the type of electrolyte. As these nanoparticles suffered from degradation, the 3D mapping of the structural changes of Cu@Ag core-shells under operating conditions led to the hypothesis of a two-step degradation mechanism where initially Cu leaching was observed with the subsequent sintering of the Ag shells. One approach to avoid this electrochemical degradation, investigated in this research, was the application of an ultrathin carbon layer to protect the active layer. This ultrathin carbon layer operated as a protective layer, suppressing hydrogen production and increasing the stability of the electrocatalyst. In conclusion, the product selectivity can be tuned by using different Cu-Ag bimetallic nanoparticles synthesized through a robust method. Their unique degradation pathway of Cu@Ag core-shell nanoparticles has led to the proposition of a more accurate stabilization strategy. These findings can contribute significantly in the quest for improved electrocatalysts for the eCO2R.

Abstract: Among all types of discovered crystals, those formed by organic molecules show the greatest diversity, which results from the intrinsic complexity of the organic molecules and the weak interactions between them. Even for a given compound, different crystal structures can exist. This feature is referred to as polymorphism in the modern crystallographic context and those different crystal forms are called polymorphs. In reality, the crystallization of organic molecules is often performed at the surface of a substrate, giving rise to heterogeneous crystallization. Except for the well-known catalyzing effects, the existence of substrates brings more possibilities to the polymorphic behaviors of organic molecules, promoting the formation of new polymorphs that are only stable in the vicinity of the substrates. For this reason, these new polymorphic forms are often described as substrate-induced polymorphs (SIPs). It is of great importance to understand the formation of SIPs for organic molecules as it has been reported that SIPs can show superior properties with respect to their bulk form counterparts. Up to now, most studies focus on the identifying and characterizing the presence of SIPs, which relies mainly on X-ray diffraction techniques. However, a detailed explanation about the origin of SIPs is still missing. In this work, we have combined several powerful experimental characterization techniques, including X-ray diffraction, transmission electron microscopy (TEM) and scanning tunneling microscopy (STM) in order to reach an integrated view over the formation of SIPs. These experimental studies are strongly supported by computational chemistry simulations, such as density functional theory and molecular dynamics. A big advantage of using atomistic simulations is that it enables the possibility to predict a priori the crystal structures of SIPs and to establish a posteriori the general rules for the formation of SIPs. In practice, this thesis employs state-of-art atomistic simulation approaches in order to bridge substrate-induced polymorphism with a conceptually-connected research area: the self-assembly of molecular networks (SAMNs), also called 2D crystallization. Unlike SIPs, which extend at least several molecular layers, SAMNs are composed of a single layer of molecules with ordered packing. Our simulations have enabled a more comprehensive understanding about the role of substrate during the formation of SIPs and we elucidate how the positional and orientational order of molecules propagates from the substrate to the upper 2D and even 3D crystal layers. In this way, a fundamental understanding of the substrate-induced crystallization is gained by connecting 2D and 3D crystallization using substrate-induced approaches.

Abstract: The plasma-based dry reforming in a dielectric barrier discharge (DBD) reactor is important to achieve sustainable goals, but many challenges remain. For example, the conversion and energy yield of DBD reactors are relatively low, and the catalysts or packing materials used in existing studies cannot improve them, possibly due to the unsuitable properties and structures of catalysts or packing materials for plasma processes. In order to study the effect of catalyst structure on plasma-based dry reforming, a controllable synthesis of the catalyst supports or templates was explored. In Chapter 2, an initially immiscible synthesis method was proposed to synthesize uniform silica spheres, which can replace the organic solvent-based Stöber method to successfully synthesize silica particles with the same size ranges as the original Stöber process without addition of organic solvents. Using the silica spheres as templates, 3D porous Cu and CuO catalysts with different pore sizes were synthesized in Chapter 3 to study the effect of catalyst pore size on the plasma-catalytic dry reforming. In most cases, the smaller the pore size, the higher the conversion of CH4 and CO2 due to the reaction of radicals and ions formed in the plasma. An exception are the samples synthesized from 1 μm silica, which show better performance due to the electric field enhancement for pore sizes close to the Debye length. Besides the pore size, the particle diameter of the catalyst or packing is also one of the important factors affecting the interaction between plasma and catalyst. In Chapter 4, SiO2 spheres (with or without supported metal) were used to study the effect of different support particle sizes on plasma-based dry reforming. We found that a uniform SiO2 packing improves the conversion of plasma-based dry reforming. The conversion of plasma-based dry reforming first increases and then decreases with increasing particle size, due to the balance between the promoting and hindering effect of the particle filling on the plasma discharge. Chapter 5 is to improve the design of the DBD reactor itself, in order to try to increase its low energy yield. Some stainless steel rings were put over the inner electrode rod of the DBD reactor. The presence of rings increases the local electric field, the displaced charges and the discharge fraction, and also makes the discharge more stable and with more uniform intensity. The placement of the rings improves the performance of the reactor at 30 W supplied power.