Heterogeneous Catalyst Design For Biomass Conversion

Catalytic upgrading of bio-based feedstocks to commodity chemicals and fuels is pivotal to a more sustainable, renewable, and environmentally benign chemical economy. However, due to the high oxygen content, high water solubility, excessive reactivity, and thermal instability, typical and well-developed catalytic material and reactor processes reliably utilized in conventional petrochemical industry are, in general, not suitable for the processing of biomass feedstocks. Therefore, the development of novel heterogeneous catalysts is necessary in order to design new high-performance catalytic reactor systems. However, rational catalyst design is a multifaceted problem, and a myriad of factors influencing the catalytic performance at the reactor scale must be considered in order to design active and selective heterogeneously catalytic materials. In this work we aim to develop and validate a hierarchy of multi-scale methods for computing reaction and activation free energies of elementary processes occurring at solid-gas and solid-liquid interfaces and to apply these methods to develop fundamental insight into the nature of catalytic active sites and their interactions with the bulk chemical environment. Only with such a level of insight could one design novel heterogeneous catalysts with exceptional activity, selectivity, and stability for the conversion of lignocellulosic biomass under gas and condensed phase processing environments

Extraction of photovoltaic generator parameters through combination of an analytical and iterative approach

In the present work, we propose an improved method based on a combination of an analytical and iterative approach to extract the photovoltaic (PV) module parameters using the measured current-voltage characteristics and the simple diode model. First, we calculate the series resistance using a set of analytical formulas for the base values of the three current-voltage curves. Then, the three other parameters are analytically expressed as functions of serial resistance and ideality factor based on the linear least-squares method. Finally, the ideality factor is calculated applying an iterative algorithm to minimize the normalized root mean square error (NRMSE) value. The proposed method was validated with a real experimental set of two PV generators, which showed the best fit to the I-V curve. Moreover, the proposed method needs only the initial value of the ideality factor

Cowpea: a legume crop for a challenging environment

Running title: Cowpea for a challenging environmentCowpea is a grain legume native from Africa and is a primary source of protein for millions of people in sub-Saharan Africa and other parts of the developing world. The main important characteristics of this crop include a good protein quality with a high nutritional value, its nitrogen-fixing ability, and an ability to be more drought- and heat-tolerant than most of its legume relatives. In a research perspective, studies of cowpea are relatively scarce, despite its relevance to agriculture in the developing world and its resilience to stress. The present review provides an overview of different aspects of cowpea, with a special emphasis on the molecular markers for assessing genetic diversity, as well as on biochemical and transcriptomic data with respect to evaluating cowpea drought stress tolerance. The integration of both datasets will be useful for the improvement of cowpea because research on drought stress tolerance is of major interest for this crop in a challenging environment. © 2017 Society of Chemical Industry.This work is supported by European Investment Funds by FEDER/COMPETE/POCI—Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT—Portuguese Foundation for Science and Technology, under the project UID/AGR/04033/2013.info:eu-repo/semantics/publishedVersio

Numerical approach for extraction of photovoltaic generator single-diode model parameters

In this work, a numerical approach has been proposed to estimate the five single-diode circuit model physical parameters of photovoltaic generators from their experimental current-voltage characteristics. Linear least square method has been used to solve the system of three linear equations to express the shunt resistance, the saturation current and the photocurrent as a function of the series resistance and the ideality factor. Two key points have been used to solve the system of two nonlinear equations to extract values of series resistance and ideality factor. The advantage of the proposed method with respect of existing numerical techniques is that use only two key points of the experimental characteristic and need only two initial guesses and does not use any approximation. To evaluate the proposed method, three PV generators data have been used to compare the experimental and the theoretical curves. The application of the proposed method provides a good agreement with the experimental.</jats:p