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AbstractPreparation of uniform, spherical Li4Ti5O12 with high tap density is significant to achieve a high volumetric energy density in lithium‐ion batteries. Herein, Li4Ti5O12 microspheres with variable tap density and tunable size distribution were synthesized by a newly designed industrial spray‐drying approach. The slurry concentration, sintering time, sintering conditions after spraying, and the effect of lithium/titanium molar ratio on the lithium‐ion (Li+) storage capability were investigated. A narrow particle size distribution of around 10 μm and a high tap density close to 1.4 g cm−3 of the Li4Ti5O12 spheres can be obtained under the optimized conditions. The Li4Ti5O12 spheres can deliver a much higher capacity of 168 mAh g−1 at a rate of 1 C and show a high capacity retention of 97.7 % over 400 cycles. The synthetic conditions are confirmed to be critical for improving the electron conductivity and Li+ diffusivity by adjusting the crystal and spatial structures. As‐prepared high‐performance Li4Ti5O12 is an ideal electrode for lithium‐ion batteries or capacitors; meanwhile, the presented approach is also applicable for preparing other kind of spherical materials.

Abstract As a burgeoning theoretical framework, energy justice has been mostly focused on the energy transition in Western countries, where socio-political settings are largely featured by liberalism and democracy, leaving an obvious gap in its application in other socio-political contexts. As a major energy consumer and a leader of the global low-carbon transition, China is characterized by a distinctive socio-political regime. An array of grand strategies to transform its coal-dominant energy structure have been initiated to ameliorate deteriorating environmental crises in particular and materialize a low-carbon transition in general. Based on extensive evidence, this article incorporates the energy justice framework into the analysis of an ongoing energy transition project in rural Northern China. It contributes to the related research in three dimensions. First, empirically, it demonstrates that the coal-to-gas heating transition project has been swamped with social injustices; the absence of measures to address these would lead this mega-project to profound failure. Second, theoretically, it illustrates that the concerns of justice are even more paramount in an authoritarian context where policy processes are characterized by strong political-administrative intervention and the pursuit of efficiency at all cost. In light of this, it stresses the indispensable role of restorative justice as a core tenet in achieving energy justice in authoritarian socio-political contexts, such as China. Third, this study advocates expanding the evaluation parameters of authoritarian environmentalism to include social consequences.

The vehicle will generate an amount of current while the electric vehicle just starting to regeneratively brake. In order to avoid the impact of high current on the traction battery, a novel electrohydraulic hybrid electric vehicle has been proposed. The main power source is supplied by the electric drive system, and the hydraulic system performs the auxiliary drive system that fully exerts the advantages of the electric drive system and the hydraulic drive system. A proper regenerative braking control strategy is presented, and the control parameters are determined by the fuzzy optimization algorithm. The simulation analysis built the model through the united simulation of AMESim and MATLAB/Simulink. The results illustrated that the optimized control strategy can reduce battery consumption by 1.22% under NEDC-operating conditions.

Sustainable electricity generation is one of the major current challenges for our society. In this context, the evolution of nanomaterials and nanotechnologies has enabled the fabrication of microscopic devices to produce clean energy from a great variety of renewable sources. To expand the possibilities of energy generation, we have designed and fabricated bioinorganic generators capable to produce electricity by conversion of chemical energy from renewable fuel sources. Unlike traditional generators, the systems described herein produce mechanical energy through enzyme-driven gas production which generates vibration and pressure that are thus converted into electricity by the action of a piezoelectric component properly integrated into the device. Our generators are able to produce an electric ernergy from different renewable sources like glucose, ethanol, and amino acids, attaining energy outputs around 250 nJ cm–2 and reaching maximum open-circuit voltages of up to 1 V. In addition, the produced energy can be easily regulated by adjusting both enzyme and fuel concentration which can tune the electrical output according to the application. The systems described herein propose a new concept for self-sufficient energy harvesting that bridges biocatalysis and piezoelectricity, where the energy production is based on the piezoelectric effect triggered by enzymatic action rather than on the enzyme-driven electron transfer that governs biofuel cells. Although the electric output is too low yet to be considered an alternative for energy production, this technology opens the door to power small devices. We envision the utilization of this technology in such remote locations where mechanical energy is lacking but there are chemical energy reservoirs. We would like to acknowledge Marie-Curie Actions (NANOBIENER project), IKERBASQUE foundation for funding F.L.-G., and the support of COST Action CM1303 Systems Biocatalysis. We also acknowledge HERGAR foundation for the funding. Peer reviewed

Abstract This paper uses research-quality, ground measurements of irradiance and temperature that are accurate to ±2% to estimate the electric energy yield of fixed solar modules for utility-scale solar power plants at 18 sites in Saudi Arabia. The calculation is performed for a range of tilt and azimuth angles and the orientation that gives the optimum annual energy yield is determined. A detailed analysis is presented for Riyadh including the impact of non-optimal tilt and azimuth angles on annual energy yield. It is also found that energy yield in March and October are higher than in April and September, due to milder operating temperatures of the modules. A similar optimization of tilt and azimuth is performed each month separately. Adjusting the orientation each month increases energy yield by 4.01% compared to the annual optimum, but requires considerable labour cost. Further analysis shows that an increase in energy yield of 3.63% can be obtained by adjusting the orientation at five selected times during the year, thus significantly reducing the labour requirement. The optimal orientation and corresponding energy yield for all 18 sites is combined with a site suitability analysis taking into account climate, topography and proximity to roads, transmission lines and protected areas. Six sites are selected as having high suitability and high energy yield: Albaha, Arar, Hail, Riyadh, Tabuk and Taif. For these cities the optimal tilt is only slightly higher than the latitude, however the optimum azimuth is from 20° to 53° west of south due to an asymmetrical daily irradiance profile.

AbstractThere is close relationship between science & technology inputs and economic growth. Based on the data of science & technology input and economic growth, the paper makes the econometric models analysis on the economic growth and science & technology input of the three major coastal economic regions of China. The paper analyzes and compares the contribution rate of science & technology inputs to economic growth of the three major economic regions.

This paper examines and optimizes parameters that affect the air cooling of a Lithium-Ion (Li-Ion) battery, used in Electric Vehicles (EVs). A battery pack containing 150 cylindrical type Li-Ion battery cells in a PVC casing is investigated. An equal number of tubes are used in the pack as a medium to cool the battery by using a fan when the vehicle is stationary or with ambient air when in motion. The parameters affecting the air cooling of battery are studied and optimized by considering their practical constraints. The objective function and Number of Transfer Unit (NTU) are developed. Finally, a genetic algorithm method is employed to optimize the decision variables. Analysing the results shows that NTU can be maximized by increasing the diameter of tubes on the battery and keeping the air velocity in a certain range.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.