Abstract: This study examines five benzyl alcohol derivatives and three chemically similar compounds and compares them against benzyl alcohol in gelled emulsions for the removal of overpaint during cleaning of oil paintings. Comparative cleaning tests using xanthan gels, Pemulen® TR-2 gels, and neat solvent were made on overpaint on fragments of a seventeenth-century test painting. This approach demonstrated that molecular changes to a benzyl alcohol core resulted in enhanced control during the cleaning process. In some cases a benzyl alcohol derivative enabled selective removal of non-original material, when benzyl alcohol appeared to affect the original paint. Select derivatives were also tested in an area of overpaint on a sixteenth-century oil on panel painting by Jan van Scorel in the Rijksmuseum Collection through modifying the chemical activity of benzyl alcohol. Finally, two GC-MS-based methods were used to monitor benzyl alcohol retention and possible oxidation in paint layers post-treatment.

Abstract: Ceramics and composites, many of whose physicochemical properties significantly exceed similar properties of metals and their alloys, are processed qualitatively mainly by the electroerosion method. Despite the existing works, the mechanism of the initial stage of the removal of materials has not yet been identified. For a comprehensive understanding of the mechanism of the removal of dielectrics, a new model is proposed based on the experimental results obtained on an improved electroerosion installation. It was revealed that the initial stage of the removal of a dielectric material consists of three successive stages that are associated with the synergistic effect on the process of the anionic group of electrolytes, plasma flare, and the cavitation shock. This makes it possible to better understand the mechanism of the removal of composite and ceramic materials, which should contribute to ensuring the machinability of those materials and their wide use in promising technologies.

Abstract: Air quality currently poses a major risk for human health. Currently, diesel is widely used as fuel and is a significant source of nitrogen oxides (NOx) and particulate matter (PM), both hazardous to human health. A good alternative for mineral diesel is biodiesel, not only for the improvement of hazardous components in the exhaust gases but also because it can be produced in view of a circular economy. Biodiesel consists of a mix of different fatty acid methyl esters, which can react with oxygen. As a consequence, the oxidation stability of biodiesel has to be studied, because the oxidation of biodiesel could affect the performance of the engine due to the wear of injectors and fuel pumps. The oxidation stability could also affect the quality of the exhaust gases due to increases in NOx and PM. The basic question we try to answer in this communication is: 'Can we find an optimal fatty acid composition in order to have a maximal oxidation stability?' In this article, we try to find the optimal fatty acid composition according to the five most common fatty acid methyl esters present in biodiesel in order to reach a maximal oxidation stability. The measurements and statistical analysis show, however, that there is no useful regression model because there are statistically significant two- and three-way interactions among the different fatty acids.

Abstract: Preston's equation is a general model describing the egg shape of birds. The parameters of Preston's equation are usually estimated after re-expressing it as the Todd-Smart equation and scaling the egg's actual length to two. This method assumes that the straight line through the two points on an egg's profile separated by the maximum distance (i.e., the longest axis of an egg's profile) is the mid-line. It hypothesizes that the photographed egg's profile is perfectly bilaterally symmetrical, which seldom holds true because of photographic errors and placement errors. The existing parameter estimation method for Preston's equation considers an angle of deviation for the longest axis of an egg's profile from the mid-line, which decreases prediction errors to a certain degree. Nevertheless, this method cannot provide an accurate estimate of the coordinates of the egg's center, and it leads to sub-optimal parameter estimation. Thus, it is better to account for the possible asymmetry between the two sides of an egg's profile along its mid-line when fitting egg-shape data. In this paper, we propose a method based on the optimization algorithm (optimPE) to fit egg-shape data and better estimate the parameters of Preston's equation by automatically searching for the optimal mid-line of an egg's profile and testing its validity using profiles of 59 bird eggs spanning a wide range of existing egg shapes. We further compared this method with the existing one based on multiple linear regression (lmPE). This study demonstrated the ability of the optimPE method to estimate numerical values of the parameters of Preston's equation and provide the theoretical egg length (i.e., the distance between two ends of the mid-line of an egg's profile) and the egg's maximum breadth. This provides a valuable approach for comparing egg shapes among conspecifics or across different species, or even different classes (e.g., birds and reptiles), in future investigations.

Abstract: WO3 isa 5d compound that undergoes severalstructuraltransitions in its bulk form. Its versatility is well-documented,with a wide range of applications, such as flexopiezoelectricity,electrochromism, gating-induced phase transitions, and its abilityto improve the performance of Li-based batteries. The synthesis ofWO(3) thin films holds promise in stabilizing electronicphases for practical applications. However, despite its potential,the electronic structure of this material remains experimentally unexplored.Furthermore, its thermal instability limits its use in certain technologicaldevices. Here, we employ tensile strain to stabilize WO3 thin films, which we call the pseudotetragonal phase, and investigateits electronic structure using a combination of photoelectron spectroscopyand density functional theory calculations. This study reveals theFermiology of the system, notably identifying significant energy splittingsbetween different orbital manifolds arising from atomic distortions.These splittings, along with the system's thermal stability,offer a potential avenue for controlling inter- and intraband scatteringfor electronic applications.

Abstract: To provide for the globally increasing demand for proteinaceous food, microbial protein (MP) has the potential to become an alternative food or feed source. Phosphorus (P), on the other hand, is a critical raw material whose global reserves are declining. Growing MP on recovered phosphorus, for instance, struvite obtained from wastewater treatment, is a promising MP production route that could supply protein-rich products while handling P scarcity. The aim of this study was to explore struvite dissolution kinetics in different MP media and characterize MP production with struvite as sole P-source. Different operational parameters, including pH, temperature, contact surface area, and ion concentrations were tested, and struvite dissolution rates were observed between 0.32 and 4.7 g P/L/d and a solubility between 0.23 and 2.22 g P-based struvite/L. Growth rates and protein production of the microalgae Chlorella vulgaris and Limnospira sp. (previously known as Arthrospira sp.), and the purple non‑sulfur bacterium Rhodopseudomonas palustris on struvite were equal to or higher than growth on conventional potassium phosphate. For aerobic heterotrophic bacteria, two slow-growing communities showed decreased growth on struvite, while the growth was increased for a third fast-growing one. Furthermore, MP protein content on struvite was always comparable to the one obtained when grown on standard media. Together with the low content in metals and micropollutants, these results demonstrate that struvite can be directly applied as an effective nutrient source to produce fast-growing MP, without any previous dissolution step. Combining a high purity recovered product with an efficient way of producing protein results in a strong environmental win-win.

Abstract: The goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.

Abstract: Purpose Natural deep eutectic solvents (NADES) represent a green alternative to conventional organic solvents as reaction medium, offering more benign properties. To efficiently design NADES for biocatalysis, a better understanding of their effect on these reactions is needed. We hypothesize that this effect can be described by separately considering (1) the solvent interactions with the substrates, (2) the solvent viscosities and (3) the enzyme stability in NADES. Methods We investigated the effect of substrate solvation and viscosity on the reaction rate; and the stability of the enzyme in NADES. To this end, we monitored the conversion over time of the transesterification of vinyl laurate with 1- butanol by the lipase enzyme Candida antarctica B in NADES of different compounds and molar ratios. Results The initial reaction rate is higher in most NADES ( varying between 1.14 and 15.07 mu mol min(-1) mg(-1)) than in the reference n-hexane (4.0 mu mol min(-1) mg(-1))), but no clear relationship between viscosity and initial reaction rate was found. The increased reaction rate is most likely related to the solvation of the substrate due to a change in the activation energy of the reaction or a change in the conformation of the substrate. The enzyme retained part of its activity after the first 2 h of reaction (on average 20 % of the substrate reacted in the 2-24 h period). Enzyme incubation in ethylene glycol-based NADES resulted in a reduced reaction rate ( 15.07 vs. 3.34 mu mol min(-1) mg(-1)), but this may also be due to slow dissolution of the substrate. Conclusions The effect of viscosity seems to be marginal next to the effect of solvation and possible enzyme-NADES interaction. The enzyme retains some of its activity during the 24-hour measurements, but the enzyme incubation experiments did not yield accurate, comparable values. [GRAPHICS] .

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: Supershapes are used in Parametric Design to model, literally, thou-sands of natural and man-made shapes with a single 6 parameter formula. However, users are left to probe such a rich yet dense collection of supershapes using a set of independent 1-D sliders. Some of the formula’s parameters are non-linear in nature, making them particularly difficult to grasp with conventional 1-D sliders alone. VR appears as a promising setting for Parametric Design with supershapes since it empowers users with more natural visual inspection and shape browsing techniques, with multiple solutions being displayed at once and the possibility to design more interesting forms of slider interaction. In this work, we propose VR shape widgets that allow users to probe and select supershapes from a multitude of solutions. Our designs take leverage on thumbnails, mini-maps, haptic feedback and spatial interaction, while supporting 1-D, 2-D and 3-D supershape parameter spaces. We conducted a user study (N = 18) and found that VR shape widgets are effective, more efficient, and natural than conventional VR 1-D sliders while also usable for users without prior knowledge on supershapes. We also found that the proposed VR widgets provide a quick overview of the main supershapes, and users can easily reach the desired solution without having to perform fine-grain handle manipulations.

Abstract: Biological membranes are under constant attack of reactive oxygen and nitrogen species (RONS), which may lead to a complex mixture of nitro-oxidized lipids that are responsible for structural and dynamic changes on the membrane. Because of that, nitro-oxidized lipids are also associated with several tumors and inflammatory and neurodegenerative diseases. Moreover, lipid oxidation may induce membrane phase-separated domains, which also drastically affect the membrane function. Evidence suggests that domain interfaces are “hot spots” for pore formation, but the underlying mechanisms remain elusive. There is an urgent need for an improved understanding of oxidation-induced phase separation on membrane properties. Likewise, the molecular structure at domain interfaces still needs to be elucidated. To evaluate the effect of lipid nitro-oxidation on the permeability of single-phase (homogeneous) and phase-separated (heterogeneous) phospholipid bilayers (PLBs), we performed atomistic molecular dynamics (MD) simulations using: (1) single-phase PLBs composed of several isomers of nitrated and/or oxidized lipids; (2) phase-separated PLBs composed of coexisting liquid ordered (Lo) and liquid disordered (Ld) domains, where the Ld domain is composed of non-oxidized and/or oxidized lipids. Our results show that nitrated lipids increase the membrane permeability of single-phase PLBs by three-fold compared to oxidized lipids. In addition, we show that oxidized lipids in the presence of nitrated lipids decrease the membrane permeability, suggesting an interaction between nitrated and oxidized lipids. Overall, the permeability of single-phase and phase-separated PLBs was comparable, and the presence of oxidized lipids increases the membrane permeability only in single-phase PLBs. Despite the latter, the presence of only 1.5% of lipid aldehydes at the Lo/Ld domain interfaces of phase-separated PLBs was able to increase the membrane permeability. In consequence of this, we also performed coarse-grained MD simulations to evaluate whether lipid aldehydes have a preference to accumulate at the interface between Lo/Ld domains. Our results show that lipid aldehydes derived from mono-unsaturated lipids accumulate at the interface, but those derived from poly-unsaturated lipids remain in the Ld domain. This study is of interest for photodynamic therapy and plasma medicine for cancer treatment, to understand the effects caused by RONS in cell membranes.

Abstract: Photoactive nanoparticles and their light-driven applications have gained tremendous scientific attention towards remediation of the global environmental problems, meeting alternative energy demands, and other new technological discoveries. The research work presented in this dissertation includes a fundamental investigation of such nanoparticles to gain deeper insights that will ultimately benefit their application. In particular, the study of plasmonic metal nanoparticles and metal oxide nanoparticles for light driven applications is the major theme of this work. The investigation begins with isolated plasmonic Au and Ag nanoparticles, followed by a natural extension to nanoparticle clusters, and then further to nanoparticle films. Next, the application of such plasmonic nanoparticle films for gaseous phase sensing of volatile organic compounds is explored. Finally, the film formation of metal-oxide nanoparticles by self-assembly is investigated for the fabrication of photoactive functional interfaces. The fundamental theoretical investigation of the isolated plasmonic nanoparticles encompasses alloy and core-shell nanostructures of Au-Ag bimetallic compositions. First, the optical properties of bimetallic alloy and core-shell nanoparticles are compared for different structures such as nanospheres, nanotriangles and nanorods. Based on the optical properties, the photothermal properties of these nanostructures are also evaluated for relevant light-driven applications. Further, to bridge the gap between the theoretical and experimental optical properties of colloidal plasmonic nanoparticles, the effect of different statistical parameters pertaining to the particle size distribution is studied. Going from isolated nanoparticles to nanoparticle clusters, the changes in the optical properties of plasmonic nanoparticles when they form finite clusters is investigated. A strong effect of clustering on the absorption intensities of the nanoparticles and hence, on the photothermal properties is found. Next, for the study of plasmonic nanoparticle infinite arrays, Au and Ag nanoparticles films are experimentally obtained by the self-assembly at the air-ethylene glycol interface. Upon further validation of the computational models with the experimental optical properties of these films, the near-field and far-field optical response of the plasmonic nanoparticle arrays is investigated. An application of the self-assembled Au nanoparticle film is then demonstrated in the sensing of volatile organic compounds (VOCs). Finally, the focus is shifted from plasmonic nanoparticles to metal oxide nanoparticles for their self-assembly at the air-water interface to obtain self-assembled films. For this, the hydrophobic functionalization of four metal oxides nanoparticles namely, TiO2, ZnO, WO3 and CuO is investigated. The insights from this work is useful for the design and fabrication of functional nanoparticles and interfaces for light driven applications.