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In this study, the effects of discharge rate and LiMn2O4 cathode properties (thickness, porosity, particle size, and solid-state diffusivity and conductivity) on the gravimetric energy and power density of a lithium-ion battery cell are analyzed simultaneously using a cell-level model. Surrogate-based analysis tools are applied to simulation data to construct educed-order models, which are in turn used to perform global sensitivity analysis to compare the relative importance of cathode properties. Based on these results, the cell is then optimized for several distinct physical scenarios using gradient-based methods. The complementary nature of the gradient- and surrogate-based tools is demonstrated by establishing proper bounds and constraints with the surrogate model, and then obtaining accurate optimized solutions with the gradient-based optimizer. These optimal solutions enable the quantification of the tradeoffs between energy and power density, and the effect of optimizing the electrode thickness and porosity. In conjunction with known guidelines, the numerical optimization framework developed herein can be applied directly to cell and pack design.

Thin films of NiO have been prepared using potentiostatic electrodeposition technique from an aqueous electrolytic bath containing NiSO4. Deposited films have been characterized using x-ray diffraction, scanning electron microscopy and energy dispersive analysis by x-rays. X-ray diffraction patterns showed that the prepared films possess polycrystalline nature with face centered cubic structure. Surface morphology and film composition showed that films with better stoichiometry and smooth surface are obtained at optimized growth condition. Optical absorption analysis showed that the prepared films possess direct band gap value around 3.46 eV.

In general, rain-fed agriculture is practised in many areas in western Sudan. Therefore, it is imperative to adopt appropriate rainwater harvesting and reuse technique(s) by promoting soil and water management research to sustain crop productivity. Sorghum (Sorghum bicolor L.) is a primary stable crop of Sudan. Extensive field experiments were conducted to study the effect of water harvesting techniques (WHTs) and supplemental irrigation (SI) on infiltration rate (IR), soil moisture content (SMC), growth and productivity of sorghum during two rainy seasons (2012 and 2013).The results showed that the WHTs and SI affected the soil physical properties, growth and productivity parameters of sorghum. The results indicated that the tied-ridging with SI (TRwSI) produced the highest values of accumulative IR, SMC and sorghum productivity (115 mm, 13% and 4000 kg h(-1) , in season 2012, respectively, whereas in season 2013 the values were 145 mm, 10% and 5000 kg h(-1) , for accumulative IR, SMC and sorghum productivity, respectively. Basin with SI (BwSI) ranked second, next to TRwSI in the both seasons.Hence, water harvesting and SI are expected to play a significant role in terms of sustainable agricultural and socio-economic development in western Sudan and similar areas.

Abstract The present work correlates the heat transport phenomenon coupled with reaction kinetics occurring in the pyrolysis of the coconut shell biomass. The kinetics was modelled assuming an independent parallel reaction of three prominent constituents of biomass namely hemicellulose, cellulose and lignin. Based on the Arrhenius theory and three first order reactions, the kinetic parameters were determined. The activation energy was obtained as 145.20 kJ mol−1, 124.55 kJ mol−1 and 78.60 kJ mol−1 for hemicellulose, cellulose and lignin respectively at a heating rate 10 K/min. The corresponding pre-exponential factor ranges from 5.30х106 to 9.60х109 min−1. The kinetic parameters followed a linear relationship showing an energy compensation effect with its parameters 0.1020 mol kJ−1 min−1 and 7.7753 min−1. Further, these kinetic values for individual components along with other thermo-physical properties had been used to evaluate the transport properties of each. Subsequently, heat transfer map predicted the controlling mechanism with varying particle size for three constituents. Pyrolysis number showed the heat propagation was highest for hemicelluloses of the order 1010, which was further 100 times slower for cellulose and least for lignin. Also, particle size had a predominant effect on transfer properties with a critical size controlling the change of regime for different components.

Abstract Globally, even as environmental protection and sustainability are becoming increasingly important, freight transportation firms are faced with the enormous need to reduce the significant environmental burdens that accrue from transport vehicles. Eco-innovation can aid freight transport firms through fostering sustainable transportation alternatives at best possible costs to ensure effective decision- making for freight logistics sustainability. Yet, freight logistics companies are faced with numerous difficulties when attempting to implement eco-innovation practices along their supply chains. This paper therefore identifies the challenges to implementing eco-innovation practices for freight logistics sustainability to aid management to take informed decisions to overcome these challenges before the environmental burdens become critical. The Best- Worst method is adopted to evaluate and rank these challenges in terms of their relative importance in Nigeria, an emerging economy, which is characterized by increased consumption due to huge population size coupled with government green requirements. The results depict that unavailable funds, lack of clarity on the financial benefits of eco-innovation practices, poor technology infrastructure and reluctant attitude towards eco-innovation practices are the most pressing challenges amongst the challenges faced by Nigeria freight logistics companies. These results will provide insight and guidelines for decision-makers and policymakers in the freight logistics sector who seeks to integrate eco-innovation initiatives to achieve sustainability.

In this review article, discuss the many ways utilized by the dairy sector to treat pollutants, emphasizing their influence on the quality and efficiency with which contamination is removed. It focuses on biotechnology possibilities for valorizing dairy waste in particular. The findings revealed that dairy waste may be treated using physicochemical, biological, and biotechnological techniques. Notably, this article highlighted the possibility of dairy waste being used as a feedstock not only for the generation of biogas, bioethanol, biohydrogen, microbial fuel cells, lactic acid, and fumaric acid via microbial technology but also for the production of biooil and biochar by pyrolysis. In addition, this article critically evaluates the many treatment techniques available for recovering energy and materials from dairy waste, their combinations, and implementation prospects. Valorization of dairy waste streams presents an opportunity to extend the dairy industry's presence in the fermented functional beverage sector.

AbstractBy using quarterly data over the period 1970Q1‐2017Q4, this paper examines the dynamic causal relationship between globalization and energy consumption by using rolling and recursive rolling Granger causality methods. This study is pioneering effort to examine the dynamic causal relationship between globalization and energy consumption using time‐varying Granger causality tests for 20 top and bottom globalized economies. The empirical results reveal that the dynamic causality relationship between globalization and energy consumption is time‐varying. Although, the causal relationship could not be observed for some of the study periods, bidirectional causality is found in many sub‐samples. From the empirical findings, we observe that unidirectional causality running from globalization to energy consumption has grievous impact on trade and environmental quality. In general, our empirical results resonate with the previous findings of globalization energy‐driven hypothesis, with significant policy implications for top and bottom globalized countries.

Accurate classification of gases/odors is a classical challenge. Gas sensor arrays are generally used to enhance classification accuracy as they generate unique signature patterns for each individual gas/odor sample. However, instead of using these raw signatures directly, analyzing these signatures in certain hyperspaces also improves classification results. Most of the clusters created using existing transformations and normalization techniques are usually non-spherical and overlapping, leading to ambiguous classification results. In this paper, a new transformation called normalized difference sensor response transformation has been proposed. Here, virtual multi-sensor responses are generated from raw signature responses. These virtual responses show unambiguous association between data belonging to respective gases/odors. In addition, the signatures generated from virtual responses are grossly concentration independent, which further enhances the accuracy of classification. Experiments were conducted by using a thick-film four-element gas sensor array for four hazardous gases viz., acetone, carbon tetrachloride (CCl4), ethyl methyl ketone, and xylene. The results show cluster compaction by an average of 94.38% in terms of intra-cluster distance with respect to raw sensor responses. In addition, when compared with existing techniques, only the proposed transformation could generate non-overlapping clusters. Furthermore, minimum inter-cluster separation was 0.80 units.

The present study reports mathematical modelling of palm oil mill effluent and palm-pressed fiber mixtures (0% to 100%) during vermicomposting process. The effects of different mixtures with respect to pH, C:N ratio and earthworms have been optimized using the modelling parameters. The results of analysis of variance have established effect of different mixtures of palm oil mill effluent plus palm press fiber and time, under selected physicochemical responses (pH, C:N ratio and earthworm numbers). Among all mixtures, 60% mixture was achieved optimal growth at pH 7.1 using 16.29 C:N ratio in 15 days of vermicomposting. The relationship between responses, time and different palm oil mill waste mixtures have been summarized in terms of regression models. The obtained results of mathematical modeling suggest that these findings have potential to serve a platform for further studies in terms of kinetic behavior and degradation of the biowastes via vermicomposting.