• Energy Research
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Abstract Economically harvesting energy from a microbial fuel cell (MFC), increasing its electrical power production, and developing its role as a practical energy supply, needs a low-cost and high-performance design of the MFC compartments. According to this strategy, a novel monolithic membrane electrode assembly (MEA) was fabricated and evaluated as an air–cathode in a single-chamber MFC (SCMFC). The MEA was made of bacterial cellulose (BC), conductive multi-walled carbon nanotubes (CNT), and nano-zycosil (NZ). BC, as a nano-celluloses with oxygen barrier property, can maintain anaerobic conditions for the anode compartment. Binder-less CNT coating on BC avoids costly binders such as poly-tetra fluoro ethylene (PTFE) and Nafion and decreases the MEA charge transfer resistance. NZ, as a very cheap modifier, not only prevents the anolyte leakage but also provides more MEA’s active sites for the oxygen reduction reaction (ORR). The electrochemical performance of the MEA was compared to a PTFE- based gas diffusion electrode (GDE) in the SCMFC. The MEA cell provided a pulse power density of 1790 mW/m2, roughly twice as high as the pulse power density of GDE (920 mW/m2). SCMFC’s internal resistance decreased from 1.84 KΩ (with GDE) to 0.8 KΩ (with MEA). Also, the cell’s columbic efficiency increased from 4.2% (with GDE) to11.7% (with MEA). Additionally, the capacitance of the MEA (65 mF) was much higher than the value for GDE (0.73 mF). Thus, the MEA compared to the GDE showed higher performance in the SCMFC for electricity generation and wastewater treatment at a lower cost.

Efficient integration of solar energy into the electricity mix depends on a reliable anticipation of its intermittency. A promising approach to forecast the temporal variability of solar irradiance resulting from the cloud cover dynamics is based on the analysis of sequences of ground-taken sky images or satellite observations. Despite encouraging results, a recurrent limitation of existing deep learning approaches lies in the ubiquitous tendency of reacting to past observations rather than actively anticipating future events. This leads to a frequent temporal lag and limited ability to predict sudden events. To address this challenge, we introduce ECLIPSE, a spatio-temporal neural network architecture that models cloud motion from sky images to not only predict future irradiance levels and associated uncertainties, but also segmented images, which provide richer information on the local irradiance map. We show that ECLIPSE anticipates critical events and reduces temporal delay while generating visually realistic futures. The model characteristics and properties are investigated with an ablation study and a comparative study on the benefits and different ways to integrate auxiliary data into the modelling. The model predictions are also interpreted through an analysis of the principal spatio-temporal components learned during network training. Manuscript accepted for publication in Applied Energy

Thin-film photovoltaics (PV) cells offer several benefits over conventional first-generation PV technologies, including lighter weight, flexibility, and lower power generation cost. Among the competing thin-film technologies, chalcogenide solar cells offer promising performance on efficiency and technological maturity level. However, in order to appraise the performance of the technology thoroughly, issues such as raw materials scarcity, toxicity, and environmental impacts need to be investigated in detail. This paper therefore, for the first time, presents a cradle to gate life cycle assessment for four different emerging chalcogenide PV cells, and compares their results with copper zinc tin sulfide (CZTS) and the commercially available CIGS to examine their effectiveness in reducing the environmental impacts associated with PV technologies. To allow for a full range of indicators, life cycle assessment methods CML 2001, IMPACT 2002+, and ILCD 2011 were used to analyse the results. The results identify environmental hotspots associated with different materials and components and demonstrate that using current efficiencies, the environmental impact of copper indium gallium selenide (CIGS) for generating 1kWh electricity was lower than that of the other studied cells. However, at comparable efficiencies the antimony-based cells offered the lowest environmental impacts in all impact categories. The effect of materials used was also found to be lower than the impact of electricity consumed throughout the manufacturing process, with the absorber layer contributing the most to the majority of the impact categories examined. In terms of chemicals consumed, cadmium acetate contributed significantly to the majority of the environmental impacts. Stainless steel in the substrate/insulating layer and molybdenum in the back contact both contributed considerably to the toxicity and ozone depletion impact categories. This paper demonstrates considerable environmental benefits associated with non-toxic chalcogenide PV cells suggesting that the current environmental concerns can be addressed effectively using alternative materials and manufacturing techniques if current efficiencies are improved. Peer Reviewed

Abstract The methodology, the site and the dataset as well as the emissions scenario considered in the weather file definition influence the numerical evaluation of efficiency measures resilience. With a complete statistical and critical approach, the paper analyzes the importance of these aspects by means of a residential case study simulated in Benevento, a city of south Italy. Using data monitored from 2015 to 2020, a current weather file is built with different methodologies. The comparison indicates that there is not repeatability of the year chosen as a reference for the various months and thus the resolution of the building energy balance could bring different results. Some future climate projections are also generated on medium (2050 s) and long (2080 s) term considering different emission scenarios. With long term projection, the heating degree days are reduced also of − 21% meanwhile the cooling degree days are more than double compared with the current condition. This suggests a remarked transition towards a dominant cooling climate for Benevento. Moreover, when the climate change is considered, the insulation intervention and the installation of double glazed low emissive window is not resilient because the heating energy need decreases also of −56%, but the cooling energy need increases of + 62% (2080 s). If the efficiency measures include also the cool roof and the external shadings, the cooling demand could be reduced until –33% in some scenarios (e.g. RCP 4.5-50th percentile) and increased (+31%) in some others (e.g. 2080 s).