The state of health (SOH) is critical to the efficient and reliable use of lithium-ion batteries (LIBs). Recently, the SOH estimation method based on electrochemical impedance spectroscopy (EIS) has ...been proven effective. In response to different practical applications, two models for SOH estimation are proposed in this paper. Aiming at based on the equivalent circuit model (ECM) method, a variety of ECMs are proposed. Used EIS to predict the ECM, the results show that the improved method ensures the correctness of the ECM and improves the estimation results of SOH. Aiming at a data-driven algorithm, proposes a convolution neural network (CNN) to process EIS data which can not only extract the key points but also simplifies the complexity of manual feature extraction. The bidirectional long short-term memory (BiLSTM) model was used for serial regression prediction. Moreover, the improved Particle Swarm Optimization (IPSO) algorithm is proposed to optimize the model. Comparing the improved model (IPSO-CNN-BiLSTM) with the traditional PSO-CNN-BiLSTM, CNN-BiLSTM and LSTM models, the prediction results are improved by 13.6%, 93.75% and 94.8%, respectively. Besides that, the two proposed methods are 27% and 35% better than the existing gaussion process regression (GPR) model, which indicates that the proposed improved methods are more flexible for SOH estimation with higher precision.
Since 2013, China has become the largest emitter of CO2 in the world. Among all emission sources, the building and construction industry contributes significant amounts due to its massive use of ...materials and equipment. However, emissions quantity, growth trends, and influencing factors have yet to be fully investigated. This study aims to calculate construction carbon emissions in China from 1994 to 2012 by identifying the longitudinal impact of seven key driving factors and evaluating the effectiveness of construction emissions policy. The data were collected from publicly accessible statistical yearbooks in China, and analyzed by the Logarithmic Mean Divisia Index (LMDI) to decompose incremental emission changes. Key findings include: (1) carbon emissions of China's building and construction industry reached 115 billion kg in 2012 and contributed 3.4% to the country's emissions; (2) on average, the annual emissions increase for the last 19 years was 6.9%, during which time “building materials consumption” contributed the most (63%) to the total increase of carbon emissions, while “energy intensity” offset the largest amount (54%) of total emissions mitigation; (3) in 2012, construction carbon intensity was far less (only 13.1%) than that of the national intensity level; and (4) the construction industry has met or surpassed most of the domestic emission-reduction targets in both the short- and mid-term, but there is uncertainty on whether long-term targets can be achieved. This research provides new scientific evidence of carbon emissions in China's building and construction industry from a decomposition method and raises new challenges for industry-specific emission regulations.
•Carbon emissions from China's building and construction industry from 1994 to 2012 was calculated.•Total construction emissions annually increased by 6.9%, but the emission intensity annually decreased by 4.7%.•Key influential factors and their quantitative impacts on the changes in emissions are discussed.•Building materials contributed most to increased emissions, while the energy intensity mitigated the most of emissions.•The construction industry accomplished or will mostly fulfill reduction targets in both the short- and mid-term periods.
Lithium-ion batteries stand out from other clean energy sources because of their high energy density and small size. With the increasing application scope and scale of lithium-ion batteries, ...real-time and accurate monitoring of its state of health plays an important role in ensuring the healthy and stable operation of an energy storage system. Due to the interaction of various aging reactions in the aging process of lithium-ion batteries, the capacity attenuation shows no regularity. However, the traditional monitoring method is mainly based on voltage and current, which cannot reflect the internal mechanism, so the accuracy is greatly reduced. Recently, with the development of electrochemical impedance spectroscopy, it has been possible to estimate the state of health quickly and accurately online. Electrochemical impedance spectroscopy can measure battery impedance in a wide frequency range, so it can reflect the internal aging state of lithium-ion batteries. In this paper, the latest impedance spectroscopy measurement technology and electrochemical impedance spectroscopy based on lithium-ion battery health state estimation technology are summarized, along with the advantages and disadvantages of the summary and prospects. This fills the gap in this aspect and is conducive to the further development of this technology.
Lithium-ion batteries (LIBs) are crucial for the large-scale utilization of clean energy. However, because of the complexity and real-time nature of internal reactions, the mechanism of capacity ...decline in LIBs is still unclear. This has become a bottleneck restricting their promotion and application. Electrochemical impedance spectroscopy (EIS) contains rich electrochemical connotations and significant application prospects, and has attracted widespread attention and research on efficient energy storage systems. Compared to traditional voltage and current data, the state-of-health (SOH) estimation model based on EIS has higher accuracy. This paper categorizes EIS measurement methods based on different principles, introduces the relationship between LIBs aging mechanism and SOH, and compares the advantages of different SOH estimation methods. After a detailed analysis of the latest technologies, a review is given. The insights of this review can deepen the understanding of the relationship between EIS and the aging effect mechanism of LIBs, and promote the development of new energy storage devices and evaluation methods.
Photocatalytic water splitting is the most promising process to convert solar energy into high purity chemical fuel (hydrogen), which has received significant attention in recent years. Only several ...photocatalysts have been reported in the literature for pure water splitting under visible light. Herein we report for the first time quantum sized BiVO4 can decompose pure water into H2 and O2 simultaneously under simulated solar light irradiation without any cocatalysts or sacrificial reagents. By electrochemical measurement, we demonstrate that the significantly different photocatalytic activity of the quantum sized BiVO4 arises from the negative shift of conduction band edge by a quantum confinement effect and a decreased overpotential for water reduction. Although the generated H2 and O2 are nonstoichiometric in the present study, these findings establish the great potential of using quantum sized BiVO4 photocatalyst and solar energy for overall water splitting.
•A conceptual framework based on PSR-SENCE model is established, revealing influencing factors covering natural, economic, and social pressure-state-response aspects.•Inner mechanism on urban flood ...resilience in China are explored with Fuzzy-DEMATEL method.•Factors in natural pressure, economic state, social and economic response are proved to be most critical and highly recommended for future urban flood resilience improvement in China.•Proper implications for improving urban flood resilience are discussed with key influencing paths.
Urban flood is one of the most frequent and deadly natural disasters in the world, seriously affecting urban sustainability and people's well-being in China. As the largest developing country in the world, China urgently needs to improve its urban flood resilience. Previous studies related to urban flood resilience are mostly focused on its assessment method and simulation. However, few studies directly aim to reveal the influencing factors of urban flood resilience and their inner relationships. In order to make a significant contribution to the long-term improvement of urban flood resilience in the context of global climate change and urbanization, it is crucial to explore the influencing mechanisms of urban flood resilience. This study aims to identify key influencing factors and their interactions on urban flood resilience in China. To this end, a conceptual framework based on Pressure-State-Response model and Social-Economic-Natural Complex Ecosystem theory (PSR-SENCE model) are established and 24 factors are identified within three dimensions. The relationships between the factors are tested using a fuzzy-DEMATEL method. The results reveal that factors in pressure and response dimensions have a greater impact on the whole system, while the factors in the state dimension are more influenced by the other two dimensions. The results identify 14 critical factors, with four detailed influence paths discussed among the different dimensions. Accordingly, the implications for improving urban flood resilience are discussed within the context of the key influencing paths. The study provides a theoretical basis and approach to directly explore how the factors influencing urban flood resilience and proposes specific impact paths and improvement implications.
•Establishing an assessment method of community resilience from multi-dimensions of social capitals, stakeholders and disaster phases.•Measuring the community resilience using SNA method from the ...perspective of six important disaster-adapting social capitals.•Proposing 4R implements on enhancing the community resilience in different disaster phases.•Helping to improve disaster management efforts in urban communities, especially those that are collaboratively managed by multi-stakeholders.
Facing increasingly frequent disasters, the resilience concept are widely adopted to make up the limitations of traditional community disaster management. The relationships among community stakeholders along with their responsibilities and actions are important social capitals coping with community disaster, which have a significant impact on forming the community resilience. Accordingly, this paper is the first attempt to measure the community resilience using social network analysis (SNA) method from the view of social capitals of stakeholders. Firstly, six key disaster-adapting social capitals in the urban community are identified using systematic literature review (SLR). Then, the social capitals before, during and after the community disaster are calculated based on the SNA to characterize the level of community resilience. Finally, taking a waterlogging disaster in Nanjing city of China, some implements on enhancing the community resilience in different phases are proposed from four aspects: rapidity, robustness, redundancy and resourcefulness. The findings in the case study and the conclusions of this paper provides an easy method to calculate the resilience and social capitals of a community at different stages of a disaster, and also helps to improve disaster prevention and reduction efforts in urban communities, especially those that are collaboratively managed by multi-stakeholders.
Remaining useful life shows extraordinary function in guiding the timely replacement of supercapacitors that reach the service life limit, which has great significance to the security and stability ...of the energy storage system. In order to more accurately predict the remaining useful life of supercapacitors so as to ensure the reliability of the whole supercapacitor bank, a temporal convolutional network is used. Among them, a residual block can solve the problems of gradient explosion and gradient disappearance, which are widespread in the recurrent neural network. Early stopping technology is used to avoid overfitting, and the Adam algorithm was used to optimize the process of parameter adjustment of the temporal convolutional network. The stability and accuracy of the model prediction were verified by using the capacity attenuation dataset of supercapacitors under different experimental conditions. Meanwhile, to verify the generalization ability of the model, the datasets of supercapacitors at different working conditions without training are input into the temporal convolutional network model. Simulation shows that the temporal convolutional network model exhibits strong robustness and high accuracy in predicting the remaining useful life of supercapacitors.
In this paper, numerical simulations of single-jet impingement cooling and double-jet impingement cooling processes of heated L-shaped steel are carried out using the VOF model. The SIMPLEC ...pressure-velocity coupling algorithm and realizable k-ε model are used for the solution. The effects of jet position, water flow, and jet distance in the single-jet condition are analyzed in the simulations. The distributions of impact pressure, turbulence kinetic energy, and Nusselt number were obtained, as well as the variation of the peak values of these three factors with the jet position, water flow, and jet distance. The water flow rate is 3-11 L/min, and the jet distance is 5-25 cm. The effect of the distance between the two nozzles on the jet cooling uniformity under the dual jet condition was also analyzed. The distance between the two nozzles was 15-45 mm. The results showed that the variation of water flow rate had a greater effect on the ability of jet cooling compared with the jet position and jet distance, and the heat transfer efficiency also increased gradually with the increase of water flow, but the increased rate of heat transfer efficiency decreased gradually. When the flow rate increased from 3 to 11 L/min, the maximum instantaneous cooling rates at 1/4 of the thickness of the short side upper side, long side upper side, short side lower side, and long side lower side positions increased by 38.9%, 48.5%, 48.2%, and 32.9%, respectively. To ensure that the jet does not shift, the jet distance should be less than or equal to 10 cm. In the case of the double jet, the nozzle distance is 1.5 cm, and the cooling uniformity of the cooling area between the two nozzles is better. The peak Nusselt number in the cooling area of each part under the double jet cooling condition increased by 5%, 9.4%, 10.2%, and 13.3%, respectively, compared with the single jet.
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•TiO2 nanoflakes/g-C3N4 QDs were prepared by a facile calcination process.•g-C3N4 QDs were intimately hybridized with the giant TiO2 nanoflakes.•Mechanism of charge transfer and ...separation in Z-scheme heterojunction discussed.•High photocatalytic degradation and H2 evolution activity were realized.
The rapid recombination rate of photogenerated carriers in TiO2 has been limiting the photocatalytic performance. Herein, TiO2 thin flakes modified by g-C3N4 quantum dots (g-C3N4 QDs) were fabricated successfully through a facile thermal treatment of restacked single-layer nanosheets of Ti1.73O41.07- in the presence of urea as a source of g-C3N4 QDs. Characterizations showed that g-C3N4 QDs with a size of ~10 nm were homogeneously deposited on the surface of TiO2 thin flakes. Quenching experiments of •OH radicals and the detection of radicals by EPR certified the direct Z-scheme heterojunctions between g-C3N4 QDs and TiO2 flakes. The TiO2 nanoflakes/g-C3N4 QDs hybrid exhibited excellent activity for the photocatalytic hydrogen evolution from a methanol solution and the degradation of RhB due to the enhanced charge separation efficiency and improved light absorption in the direct Z-scheme heterojunctions. This study demonstrates that the rational design of heterojunction is effective for attaining the superior photocatalytic performance.
