Abstract: Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm POre REconstruction and Segmentation is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.

Abstract: Amorphous platinum clusters supported on porous carbon have been envisaged for high-performance fuel cell electrodes. For this application, it is crucial to control the morphology of the Pt layer and the Ptsubstrate interaction to maximize activity and stability. We thus investigate the morphology evolution during Pt cluster growth on a porous carbon substrate employing atomic scale molecular dynamics simulations. The simulations are based on the Pt-C interaction potential using parameters derived from density functional theory and are found to yield a Pt cluster morphology similar to that observed in low loaded fuel cell electrodes prepared by plasma sputtering. Moreover, the simulations show amorphous Pt cluster growth in agreement with X-ray diffraction and transmission electron microscopy experiments on high performance low Pt content (10 μgPt cm−2) loaded fuel cell electrodes and provide a fundamental insight in the cluster growth mechanism.

Abstract: Sustainability guidelines can help to safeguard the sustainable use of biological materials. When these guidelines are legally prescribed, their influence on the economic viability of bioenergy, biofuel and bioliquid projects is increased substantially, through their impact on national subsidy regimes and international trade. One of the key examples is the European directive 2009/28/EC, or the Renewable Energy Directive (RED), and the related COM/2010/11 that integrate guidelines for calculating greenhouse gas impact for various bioenergy pathways. This paper looks further into the sustainability results when influenced by principal decisions that are legally open for debate. Therefore, a concise review is conducted of the legal state-of-the-art on whether a product is waste or not. The review pinpoints uncertainty, leading to four potential legal scenarios. The sustainability of a complex biorefinery is analysed for each scenario. The results show (i) a high sensitivity to the principal decisions on the nature of waste materials in the scenarios, and (ii) to the definition of boundaries between the processes. More detailed rules for the application of the RED guidelines are needed, and should be complemented with methods specifically targeting all relevant sustainability aspects, thereby enhancing the overall understanding of the sustainability of the process. (C) 2014 Elsevier Ltd. All rights reserved.

Abstract: The growing concern for the increase of the global warming effects due to anthropogenic activities raises the challenge of finding novel technological approaches to stabilize CO2 emissions in the atmosphere and counteract impinging interconnected issues such as desertification and loss of biodiversity. Biological-CO2 mitigation, triggered through biological fixation, is considered a promising and eco-sustainable method, mostly owing to its downstream benefits that can be exploited. Microorganisms such as cyanobacteria, green algae and some autotrophic bacteria could potentially fix CO2 more efficiently than higher plants, due to their faster growth. Some examples of the potential of biological-CO2 mitigation are reported and discussed in this paper. In arid and semiarid environments, soil carbon sequestration (CO2 fixation) by cyanobacteria and biological soil crusts is considered an eco-friendly and natural process to increase soil C content and a viable pathway to soil restoration after one disturbance event. Another way for biological-CO2 mitigation intensively studied in the last few years is related to the possibility to perform carbon dioxide sequestration using microalgae, obtaining at the same time bioproducts of industrial interest. Another possibility under study is the exploitation of specific chemotrophic bacteria, such as Ralstonia eutropha (or picketii) and related organisms, for CO2 fixation coupled with the production chemicals such as polyhydroxyalkanoates (PHAs). In spite of the potential of these processes, multiple factors still have to be optimized for maximum rate of CO2 fixation by these microorganisms. The optimization of culture conditions, including the optimal concentration of CO2 in the provided gas, the use of metabolic engineering and of dual purpose systems for the treatment of wastewater and production of biofuels and high value products within a biorefinery concept, the design of photobioreactors in the case of phototrophs are some of the issues that, among others, have to be addressed and tested for cost-effective CO2 sequestration.

Abstract: The tunneling current between two crossed graphene ribbons is described invoking the empirical pseudopotential approximation and the Bardeen transfer Hamiltonian method. Results indicate that the density of states is the most important factor determining the tunneling current between small (similar to nm) ribbons. The quasi-one dimensional nature of graphene nanoribbons is shown to result in resonant tunneling.