A Complexing Agent to Enable a Wide-Temperature Range Bromine-Based Flow Battery for Stationary Energy Storage

Bromine-based flow batteries (Br-FBs) are considered one of the most promising energy storage systems due to their features of high energy density and low cost. However, they generally suffer from uncontrolled diffusion of corrosive bromine particularly at high temperatures. That is because the interaction between polybromide anions and the commonly used complexing agent (N–methyl–N–ethyl–pyrrolidinium bromide [MEP]) decreases with increasing temperatures, which causes serious self-discharge and capacity fade. Herein, a novel bromine complexing agent, 1–ethyl–2–methyl–pyridinium bromide (BCA), is introduced in Br-FBs to solve the above problems. It is proven that BCA can combine with polybromide anions very well even at a high temperature of 60 °C. Moreover, the BCA contributes to decreasing the electrochemical polarization of Br⁻/Br₂ couple, which in turn improves their power density. As a result, a zinc–bromine flow battery with BCA as the complexing agent can achieve a high energy efficiency of 84% at 40 mA cm⁻², even at high temperature of 60 °C and it can stably run for more than 400 cycles without obvious performance decay. This paper provides an effective complexing agent to enable a wide temperature range Br-FB.     

Inductive effect in Mn-doped ZnO nanoribon arrays grown on Ni foam: A promising key for boosted capacitive and high specific energy supercapacitors

Transition metal oxides have been explored in supercapacitor applications owing to their safety, low cost, high specific capacitance and high electrochemical activity. Among all transition metal oxides, zinc oxide based materials show remarkable response for designing the supercapacitors with high electrochemical activity. Here in, Mn doped ZnO (Zn_1-xMn_xO₃ with x = 0, 0.25, 0.50, 0.75 and 1) was synthesized by a facile hydrothermal method. Doping of Mn into the ZnO increased the surface area and decease the charge transfer resistance for the Zn_0.5Mn_0.5O₃. All the synthesized materials were characterized by x-ray diffraction (XRD), scanning electron microscopy SEM), BET, electrochemical tests and other various analytical techniques to confirm the structural, morphological, textural and suprcapacitive properties. The synthesized material Zn_0.5Mn_0.5O₃ having the porous nanoribons structure with BET surface area (2490 cm²/g). The electrochemical studies showed significantly enhanced response toward pseudocapacitive nature. The synthesized material exhibited the excellent specific capacitance (515F/g), specific energy (28.61 Wh/kg) and specific power (1000 W/kg) at current density of 2 mA/g. Such impressive and superior properties make the MnZnO₃ material as promising candidate for new generation supercapacitor applications.     

APP软件性能效率研究

性能效率是APP软件的重要质量属性，但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征，基于ISO/IEC 25010标准提出了APP软件的性能效率模型，定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型，通过实验对APP软件的性能效率进行了度量及相关分析。     

Rapid synthesis of garnet-type Li7La3Zr2O12 solid electrolyte with superior electrochemical performance

Li₇La₃Zr₂O₁₂-based garnet-type solid electrolytes are promising candidates for use in all-solid-state lithium batteries (ASSLBs). However, their potential in large-scale commercial applications is largely hindered by the time/energy-consuming and lithium-wasting synthetic method which typically needs a long-duration high temperature solid state reaction process. Herein we invent a fast preparation route that involves a short-period thermal reaction (1100 °C for 10 min) in laboratory muffle furnaces following by conventional hot pressing technique to get almost fully dense (Al, Ga, Ta, Nb)-doped garnet-type electrolytes with high phase purity (>99.9 %). The large and compact grains, low porosity and high phase purities of garnet ceramic electrolytes synthesized in this study ensure superior electrochemical performance. Particularly, Ga-doped cubic Li₇La₃Zr₂O₁₂ shows extremely low E_a values (0.17?0.18 eV) and record-high lithium ionic conductivities (>2 × 10^?3 S cm^-1 at 25 °C).     

Improved energy storage density and energy efficiency of Samarium modified PMNT electroceramic

We report the improved energy storage density and efficiency after 2.5% of Samarium substitution in ferroelectric Pb[(Mg_1/3Nb_2/3)_0.80Ti_0.20]O₃ (PMNT) electroceramic. The microstructure and surface morphology were analyzed and correlated with various functional properties. The energy storage density, leakage current density, ferroelectric and dielectric properties were investigated thoroughly, indicating that Samarium's substitution significantly modified the microstructure, the dielectric strength, breakdown electric field, and turned ferroelectric PMNT to relaxor ferroelectrics. Due to the relaxor nature, the gap between remanent polarization and maximum polarization increases with the substitution of Samarium in PMNT matrix, which further increases the recoverable energy storage density and energy efficiency. A nearly 100% increase in recoverable energy density and efficiency was obtained at an electric field strength of 35 kV/cm at room temperature (～296 K). The electroceramic shows maximum energy density near the ferroelectric phase transition temperature (325 K–345 K) region and provides a moderate energy storage density for possible applications in power microelectronics.     

Forging furnace with thermochemical waste-heat recuperation by natural gas reforming: Fuel saving and heat balance

This paper considers thermochemical recuperation (TCR) of waste-heat using natural gas reforming by steam and combustion products. Combustion products contain steam (H₂O), carbon dioxide (CO₂), and ballast nitrogen (N₂). Because endothermic chemical reactions take place, methane steam-dry reforming creates new synthetic fuel that contains valuable combustion components: hydrogen (H₂), carbon monoxide (CO), and unreformed methane (CH₄). There are several advantages to performing TCR in the industrial furnaces: high energy efficiency, high regeneration rate (rate of waste-heat recovery), and low emission of greenhouse gases (CO₂, NO_x). As will be shown, the use of TCR is significantly increasing the efficiency of industrial furnaces – it has been observed that TCR is capable of reducing fuel consumption by nearly 25%. Additionally, increased energy efficiency has a beneficial effect on the environment as it leads to a reduction in greenhouse gas emissions.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Potential of renewable energy system utilisation at decentralised level in the state of Uttarakhand in India

ABSTRACT

Design and implementation of an effective dissemination programme for decentralised renewable energy system necessitate an accurate estimate of its utilisation potential. Hence, in this study, an attempt has been made to develop frameworks to estimate the utilisation potential of decentralised renewable energy systems in the state of Uttarakhand in India. Estimations imply large resource, technical and economic potentials of the domestic solar water heater, solar home system, solar lantern, family size biogas plant and improved biomass cookstove in Uttarakhand. With higher impact on the purchasing power of households, prevailing soft loan scheme has been found to be more appropriate than a capital subsidy for promoting the usage of decentralised renewable energy systems.     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

Additively manufactured respirators: quantifying particle transmission and identifying system-level challenges for improving filtration efficiency

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy due to a lack of commensurate quality assurance processes. Many open-source respirator designs for AM indicate that they do not provide N95-equivalent protection (filtering 95% of SARS-CoV-2 particles) because they have either not passed aerosol generation tests or not been tested. Few studies have quantified particle transmission through respirator designs outside of the filter medium. This is concerning because several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. No study has isolated these failure mechanisms specifically for respirators. The goal of this paper is to measure particle transmission through printed respirators of different designs, materials, and AM processes. The authors compare the performance of printed respirators to N95 respirators and cloth masks. Respirators in this study printed using desktop- and industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes were not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection. Even while assuming a perfect seal between the respirator and the user’s face, although a few respirators provided >90% efficiency at the 100−300 nm particle range, almost all printed respirators provided <60% filtration efficiency. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but the printed respirators showed similar performance to various cloth masks. The authors further explore the process-driven aspects leading to low filtration efficiency. Although the design/printer/material combination dictates the AM respirator performance, the identified failure modes originate from system-level constraints and are therefore generalizable across multiple AM processes. Quantifying the limitations of AM in producing N95-type respiratory protective masks advances understanding of AM systems toward the development of better part and machine designs to meet the needs of reliable, functional, end-use parts.