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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

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.

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.

The energy considered as waste heat in industrial furnaces owing to inefficiencies represents a substantial opportunity for recovery by means of thermal energy storage (TES) implementation. Although conventional systems based on sensible heat are used extensively, these systems involve technical limitations. Latent heat storage based on phase change materials (PCMs) results in a promising alternative for storing and recovering waste heat. Within this scope, the proposed PCM-TES allows for demonstrating its implementation feasibility in energy-intensive industries at high temperature range. The stored energy is meant to preheat the air temperature entering the furnace by using a PCM whose melting point is 885 °C. In this sense, a heat transfer model simulation is established to determine an appropriate design based on mass and energy conservation equations. The thermal performance is analysed for the melting and solidification processes, the phase transition and its influence on heat transference. Moreover, the temperature profile is illustrated for the PCM and combustion air stream. The obtained results prove the achievability of very high temperature levels (from 700 to 865 °C) in the combustion air preheating in a ceramic furnace; so corroborating an energy and environmental efficiency enhancement, compared to the initial condition presenting an air outlet at 650 °C.

Short term load forecasting plays an increasingly important role in Smart Grid. Short term load forecasting is also an important part of enterprise power system management. Providing accurate load time series data for a certain period of time in the future can enable enterprises to ensure the smooth operation of production while making a reasonable power plan, reducing power consumption and basic electricity charges, thus reducing the production cost of enterprises. In addition, lower electricity consumption means lower carbon dioxide emissions, which has far-reaching implications for sustainable development strategies. This paper presents a short-term load forecasting method based on time series. The model divides the time series data into four parts: trend item, period item, holiday item and error item. In the experiment part, this paper provides a set of preprocessing method flow. Aiming at the problem that the sampling rate of the current smart grid data is not constant, a data smoothing algorithm is proposed.