Abstract: Lignocellulosic biomass is the most abundant source of renewable biomass and is seen as a high-potential replacement for petroleum-based resources. The conversion technologies to advanced biofuels are still at a low maturity level, thus allowing for future cost reductions through technological learning. This fact is barely considered in state-of-the-art techno-economic assessments and a structured approach to account for technological learning in techno-economic assessments is needed. In this study, a framework for techno-economic assessments of advanced biofuels, integrating learning curves, is proposed. As a validation of this framework, the economic feasibility of the valorization of corn stover for the production of second-generation bioethanol in Belgium is studied. Process flowsheet simulations in Aspen Plus are developed, with an emphasis on the comparison of four different pretreatment technologies and two plant capacities at 156 dry kt biomass/y and 667 dry kt/y. The dilute acid pretreatment model of the large-scale biorefinery required the lowest minimum learning rate to reach an economically feasible biorefinery by 2030, being 3.9%, almost half as the one calculated for the smaller scale plant. This learning rate seems to be achievable based on learning rates commonly estimated in literature. We conclude that there is a potential for advanced ethanol production in Belgium under the current state of technology for large-scale biorefineries, which require additional biomass imports, when accounting for future cost reductions through learning

Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.

Abstract: Encompassing a broad spectrum of methodological approaches and aims, the scholars contributing to this volume offer renewed perspectives on the multifaceted oeuvre of Diego Velázquez. The seventeenth-century artist’s exceptional religious works as well as his numerous portraits are examined within the social and historical context of Velázquez’s milieu which included both the Spanish court as well as circles comprising important intellectual figures of his time. Following a close investigation of his works, which also includes the results of recent technological examinations on his paintings, the contributors to this volume offer new, exciting findings and discussions on the inspirations, sources and possible intentions of Velázquez.

Abstract: At or below the surface of painted works of art, valuable information is present that provides insights into an object’s past, such as the artist’s technique and the creative process that was followed or its conservation history, but also on its current state of preservation. Typically, a (very) limited set of small paint samples is taken which provide direct access to the individual paint layers. The chemical build-up of these layers can then be investigated in great detail using various microscopic analytical methods. However, in recent years a new trend towards both elemental and chemical imaging techniques has been set which are capable of visualizing the (often) heterogeneous composition of painted objects on a macroscopic scale. In this dissertation, various forms of specificity attainable with X‑ray powder diffraction (XRPD) imaging are explored: at the chemical, material and spatial level. This high specificity is illustrated throughout several applications stemming from the field of cultural heritage, both at the macroscopic (MA) and microscopic (µ) scale. As a first step, XRPD imaging was transformed to a transportable instrument that can be employed for the in situ investigation of artworks, e.g., inside museums and conservation workshops. With this unique instrument large‑scale maps (cm2 – dm2) reflecting the distribution of crystalline phases on/below the surface of flat painted artefacts can be visualized in a noninvasive manner. In this way compound-specific information was attained which can be related to original pigments or materials that have been added in a later stage and even degradation/secondary products that have formed spontaneously inside the paint layers. Additionally, with MA‑XRPD imaging it was possible to link quantitative information of pigment compositions and preferred orientation effects to the 2D compound‑specific distribution images, allowing for a further distinction between very similar artists’ materials. Furthermore, promising results for the limited depth-selectivity of this technique, obtained by exploiting the small shift in the position of the diffraction signals originating from the layered sequence of the pigments, are shown. Finally, a minute paint sample from Wheat stack under a cloudy sky by Van Gogh was investigated at a synchrotron radiation facility with tomographic µ‑XRPD imaging at the microscopic scale. The high chemical and spatial specificity of this imaging method was exploited to further elucidate the degradation pathway of the red lead pigment.

Abstract: The process intensification abilities of gas–solid vortex units (GSVU) are very promising for gas–solid processes. By working in a centrifugal force field, much higher gas–solid slip velocities can be obtained compared to gravitational fluidized beds, resulting in a significant increase in heat and mass transfer rates. In this work, local azimuthal and radial particle velocities for an experimental GSVU are simulated using the Euler–Euler framework in OpenFOAM and compared with particle image velocimetry measurements. With the validated model, the effect of the particle diameter, number of inlet slots and reactor length on the bed hydrodynamics is assessed. Starting from 1g-Geldart-B type particles, increasing the particle diameter or density, increasing the number of inlet slots or increasing the gas injection velocity leads to an increased bed stability and uniformity. However, a trade-off has to be made since increased bed stability and uniformity lead to higher shear stresses and attrition.

Abstract: The characteristics of confined magnetoelastic waves in nanoscale ferromagnetic magnetostrictive waveguides have been investigated by a combination of analytical and numerical calculations. The presence of both magnetostriction and inverse magnetostriction leads to the coupling between confined spin waves and elastic Lamb waves. Numerical simulations of the coupled system have been used to extract the dispersion relations of the magnetoelastic waves as well as their mode profiles.

Abstract: Adding 20mg of 1-(2-pyridylazo)-2-naphthol (PAN) to a water sample at 70°, and filtering off the precipitate after cooling, gives efficient preconcentration prior to X-ray fluorescence analysis of water. Up to the capacity of about 100 μeq of PAN used, the trace metal recoveries are around 90% or higher for Cr3+, Mn2+, Ni2+, Cu2+, Zn2+, Hg2+ and Eu3+, and above 70% for many other ions. The recovery yields usually do not vary critically with pH in the neutral pH-range, and are practically independent of the sample salinity, sample volume and trace-metal concentration. Enrichment factors as high as 2 × 105 can be achieved. Counting statistics would then allow detection limits of 0.03 ppM. The blank levels in commercial PAN, however, lead to typical detection limits of about 1 ppm. The coefficient of variation is typically in the 510% range at the 10-ppM level. The accuracy and applicability of the procedure are illustrated by comparative analyses on samples of synthetic solutions, river and drinking water.

Abstract: Nitrification and denitrification, the key biological processes for thermophilic nitrogen removal, have separately been established in bioreactors at 50 °C. A well-characterized set of kinetic parameters is essential to integrate these processes while safeguarding the autotrophs performing nitrification. Knowledge on thermophilic nitrifying kinetics is restricted to isolated or highly enriched batch cultures, which do not represent bioreactor conditions. This study characterized the stoichiometry and kinetics of two thermophilic (50 °C) nitrifying communities. The most abundant ammonia oxidizing archaea (AOA) were related to the Nitrososphaera genus, clustering relatively far from known species Nitrososphaera gargensis (95.5% 16S rRNA gene sequence identity). The most abundant nitrite oxidizing bacteria (NOB) were related to Nitrospira calida (97% 16S rRNA gene sequence identity). The nitrification biomass yield was 0.200.24 g VSS g−1 N, resulting mainly from a high AOA yield (0.160.20 g VSS g−1 N), which was reflected in a high AOA abundance in the community (5776%) compared to NOB (511%). Batch-wise determination of decay rates (AOA: 0.230.29 d−1; NOB: 0.320.43 d−1) rendered an overestimation compared to in situ estimations of overall decay rate (0.0260.078 d−1). Possibly, the inactivation rate rather than the actual decay rate was determined in batch experiments. Maximum growth rates of AOA and NOB were 0.120.15 d−1 and 0.130.33 d−1 respectively. NOB were susceptible to nitrite, opening up opportunities for shortcut nitrogen removal. However, NOB had a similar growth rate and oxygen affinity (0.150.55 mg O2 L−1) as AOA and were resilient towards free ammonia (IC50 > 16 mg NH3-N L−1). This might complicate NOB outselection using common practices to establish shortcut nitrogen removal (SRT control; aeration control; free ammonia shocks). Overall, the obtained insights can assist in integrating thermophilic conversions and facilitate single-sludge nitrification/denitrification.