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: Using first-principles calculations we have studied the electronic and structural properties of cation vacancies and their complexes with hydrogen impurities in SnO2, In2O3 and β-Ga2O3. We find that cation vacancies have high formation energies in SnO2 and In2O3 even in the most favorable conditions. Their formation energies are significantly lower in β-Ga2O3. Cation vacancies, which are compensating acceptors, strongly interact with H impurities resulting in complexes with low formation energies and large binding energies, stable up to temperatures over 730 °C. Our results indicate that hydrogen has beneficial effects on the conductivity of transparent conducting oxides: it increases the carrier concentration by acting as a donor in the form of isolated interstitials, and by passivating compensating acceptors such as cation vacancies; in addition, it potentially enhances carrier mobility by reducing the charge of negatively charged scattering centers. We have also computed vibrational frequencies associated with the isolated and complexed hydrogen, to aid in the microscopic identification of centers observed by vibrational spectroscopy.

Abstract: We analyze the paradigmatic competition between intraband and crossband Cooper-pair formation in twoband superconductors, neglected in most works to date. We derive the phase-sensitive gap equations and describe the crossover between the intraband-dominated and the crossband-dominated regimes, delimited by a “gapless” state. Experimental signatures of crosspairing comprise notable gap splitting in the excitation spectrum, non-BCS behavior of gaps versus temperature, as well as changes in the pairing symmetry as a function of temperature. The consequences of these findings are illustrated on the examples of MgB2 and Ba0.6K0.4Fe2As2.

Abstract: Ru catalysts are part of a set of late transition metal nanocatalysts that have garnered much interest for catalytic applications such as ammonia synthesis and fuel cell production. Their performance varies greatly depending on their morphology and size, these catalysts are widely studied using electron microscopy. Using recent developments in Annular Dark Field (ADF) Scanning Transmission Electron Microscopy (STEM) quantification techniques, a rapid atom counting procedure was utilized to document the evolution of a heterogeneous Ru catalyst supported on carbon black. Areas of the catalyst were imaged for approximately 15 minutes using ADF STEM. When the Ru clusters were exposed to the electron beam, the clusters changed phase from amorphous to crystalline. To quantify the thickness of the crystalline clusters, two techniques were applied (simulation and statistical decomposition) and compared. These techniques show that stable face centredcubic crystal structures in the form of rafts, between 2 and 8 atoms thick, were formed after the initial wetting of the carbon support.

Abstract: Rutherford backscattering and channeling spectrometry (RBS), photoluminescence (PL) spectroscopy and transmission electron microscopy (TEM) have been used to investigate macroscopic and microscopic segregation in MOCVD grown InGaN layers. The PL peak energy and In content (measured by RES) were mapped at a large number of distinct points on the samples. An indium concentration of 40%, the highest measured in this work, corresponds to a PL peak of 710 nn strongly suggesting that the light-emitting regions of the sample me very indium-rich compared to the average measured by RES. Cross-sectional TEM observations show distinctive layering of the InGaN films. The TEM study further reveals that these layers consist of amorphous pyramidal contrast features with sizes of order 10 nm The composition of these specific contrast features is shown to be In-rich compared to the nitride matrix.

Abstract: Most farm adaptations are reactive actions that run the risk of locking farm systems into suboptimal long-term trajectories. This is especially the case with regard to water management as water scarcity will be aggravated by climate change. This paper looks into farm irrigation choices in combination with crop choices because a proper crop choice has the potential to reduce water requirements. It proposes an extended Ricardian model to capture multiple adaptation decisions explicitly. The new simultaneous irrigation-crop farm decision model uses spatially detailed farm-level data of over 18,000 European farms on irrigation and seven different crop choices. The analysis shows that larger farmers and farmers in less water-scarce regions that use irrigation are more sensitive to temperature increases than rain-fed agriculture. This might be explained by the fact that these farmers do not experience the real cost of water scarcity because of which they take less efficient decisions.

Abstract: Agricultural adaptation to climate change is indispensable. However, the degree of adaptation depends on adaptive capacity levels and it only takes place if the appropriate resources are present. Cross-sectional climate response models ignore this requirement. This paper adapts the Ricardian method to control for a generic territorial adaptive capacity index. The results for a sample of over 60.000 European farms show a significant non-linear positive relationship between adaptive capacity and climate responsiveness and that some regions in Europe can increase their climate responsiveness significantly. This confirms that improvement of adaptive capacity is an important policy tool to enhance adaptation.

Abstract: Dissemination programs of nontraditional cookstoves often fail. Nontraditional cookstoves aim to solve problems associated with biomass fuel usage in developing countries. Recent studies do not explain what drives user's cookstove choice. This study therefore builds a holistic framework that centralizes product-specific preferences or needs. The case study identifies product-specific factors that influence rural Senegalese inhabitants to switch to solar cooking, using best worst scaling. Looking at the preferences, the case study classified 126 respondents, in three distinct market segments with different solar cooking expectations. The paper identifies socio-demographic characteristics that explain these differences in the respondents' preferences. Finally, the respondent sample is divided in two groups: solar cooker owners and non-owners. When studied with regard to the same issue, solar cooker owners appear to value benefits of the solar cooker lower than non-owners. This is due to program factors (such as formations, after-sales network) and miscommunication (such as a wrong image of the solar cooker) that highly influenced the respondents' cookstove choice. As a conclusion, solar cookers and solar cooking programs are not always adapted to the needs and requirements of the end-users. Needs-oriented and end-user adopted strategies are necessary in order to successfully implement nontraditional cookstoves programs. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract: HAADF-STEM tomography is a widely used experimental technique for analyzing nanometer-scale crystalline structures of a large variety of materials in three dimensions. Unfortunately, the acquisition of conventional HAADF-STEM tilt series can easily take up one hour or more, depending on the complexity of the experiment. It is therefore far from straightforward to investigate samples that do not withstand long acquisition or to acquire large amounts of tilt series during a single TEM experiment. The latter would lead to the ability to obtain statistically meaningful 3D data, or to perform in situ 3D characterizations with a much shorter time resolution. Various HAADF-STEM acquisition strategies have been proposed to accelerate the tomographic acquisition and reduce the required electron dose. These methods include tilting the holder continuously while acquiring a projection “movie” and a hybrid, incremental, methodology which combines the benefits of the conventional and continuous technique. However, until now an experimental evaluation has been lacking. In this paper, the different acquisition strategies will be experimentally compared in terms of speed, resolution and electron dose. This evaluation will be performed based on experimental tilt series acquired for various metallic nanoparticles with different shapes and sizes. We discuss the data processing involved with the fast HAADF-STEM tilt series and provide a general guideline when which acquisition strategy should be preferentially used.

Abstract: A thorough understanding of the thermal stability and potential reshaping of anisotropic gold nanostars is required for various potential applications. Combination of a tomographic heating holder with fast tilt series acquisition has been used to monitor temperature-induced morphological changes of Au nanostars. The outcome of our 3D investigations can be used as an input for boundary element method simulations, enabling us to investigate the influence of reshaping on the nanostars’ plasmonic properties. Our work leads to a better understanding of the mechanism behind thermal reshaping. In addition, the approach presented here is generic and can hence be applied to a wide variety of nanoparticles made of different materials and with arbitrary morphology.