Frontiers in Energy最新文献

The hydrogen fuel cell vehicle is rapidly developing in China for carbon reduction and neutrality. This paper evaluated the life-cycle cost and carbon emission of hydrogen energy via lots of field surveys, including hydrogen production and packing in chlor-alkali plants, transport by tube trailers, storage and refueling in hydrogen refueling stations (HRSs), and application for use in two different cities. It also conducted a comparative study for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs). The result indicates that hydrogen fuel cell vehicle (FCV) has the best environmental performance but the highest energy cost. However, a sufficient hydrogen supply can significantly reduce the carbon intensity and FCV energy cost of the current system. The carbon emission for FCV application has the potential to decrease by 73.1% in City A and 43.8% in City B. It only takes 11.0%–20.1% of the BEV emission and 8.2%–9.8% of the ICEV emission. The cost of FCV driving can be reduced by 39.1% in City A. Further improvement can be obtained with an economical and “greener” hydrogen production pathway.

The Haber-Bosch process is the most widely used synthetic ammonia technology at present. Since its invention, it has provided an important guarantee for global food security. However, the traditional Haber-Bosch ammonia synthesis process consumes a lot of energy and causes serious environmental pollution. Under the serious pressure of energy and environment, a green, clean, and sustainable ammonia synthesis route is urgently needed. Electrochemical synthesis of ammonia is a green and mild new method for preparing ammonia, which can directly convert nitrogen or nitrate into ammonia using electricity driven by solar, wind, or water energy, without greenhouse gas and toxic gas emissions. Herein, the basic mechanism of the nitrogen reduction reaction (NRR) to ammonia and nitrate reduction reaction (NO ⁻₃ RR) to ammonia were discussed. The representative approaches and major technologies, such as lithium mediated electrolysis and solid oxide electrolysis cell (SOEC) electrolysis for NRR, high activity catalyst and advanced electrochemical device fabrication for NO ⁻₃ RR and electrochemical ammonia synthesis were summarized. Based on the above discussion and analysis, the main challenges and development directions for electrochemical ammonia synthesis were further proposed.

As the intersection of disciplines deepens, the field of battery modeling is increasingly employing various artificial intelligence (AI) approaches to improve the efficiency of battery management and enhance the stability and reliability of battery operation. This paper reviews the value of AI methods in lithium-ion battery health management and in particular analyses the application of machine learning (ML), one of the many branches of AI, to lithium-ion battery state of health (SOH), focusing on the advantages and strengths of neural network (NN) methods in ML for lithium-ion battery SOH simulation and prediction. NN is one of the important branches of ML, in which the application of NNs such as backpropagation NN, convolutional NN, and long short-term memory NN in SOH estimation of lithium-ion batteries has received wide attention. Reports so far have shown that the utilization of NN to model the SOH of lithium-ion batteries has the advantages of high efficiency, low energy consumption, high robustness, and scalable models. In the future, NN can make a greater contribution to lithium-ion battery management by, first, utilizing more field data to play a more practical role in health feature screening and model building, and second, by enhancing the intelligent screening and combination of battery parameters to characterize the actual lithium-ion battery SOH to a greater extent. The in-depth application of NN in lithium-ion battery SOH will certainly further enhance the science, reliability, stability, and robustness of lithium-ion battery management.

Platinum (Pt)-based materials are still the most efficient and practical catalysts to drive the sluggish kinetics of cathodic oxygen reduction reaction (ORR) in proton exchange membrane fuel cells (PEMFCs). However, their catalysis and stability performance still need to be further improved in terms of corrosion of both carbon support and Pt catalyst particles as well as Pt loading reduction. Based on the developed synthetic strategies of alloying/nanostructuring Pt particles and modifying/innovating supports in developing conventional Pt-based catalysts, Pt single-atom catalysts (Pt SACs) as the recently burgeoning hot materials with a potential to achieve the maximum utilization of Pt are comprehensively reviewed in this paper. The design thoughts and synthesis of various isolated, alloyed, and nanoparticle-contained Pt SACs are summarized. The single-atomic Pt coordinating with non-metals and alloying with metals as well as the metal-support interactions of Pt single-atoms with carbon/non-carbon supports are emphasized in terms of the ORR activity and stability of the catalysts. To advance further research and development of Pt SACs for viable implementation in PEMFCs, various technical challenges and several potential research directions are outlined.

Bifacial photovoltaics (BPVs) are a promising alternative to conventional monofacial photovoltaics given their ability to exploit solar irradiance from both the front and rear sides of the panel, allowing for a higher amount of energy production per unit area. The BPV industry is still emerging, and there is much work to be done until it is a fully mature technology. There are a limited number of reviews of the BPV technology, and the reviews focus on different aspects of BPV. This review comprises an extensive in-depth look at BPV applications throughout all the current major applications, identifying studies conducted for each of the applications, and their outcomes, focusing on optimization for BPV systems under different applications, comparing levelized cost of electricity, integrating the use of BPV with existing systems such as green roofs, information on irradiance and electrical modeling, as well as providing future scope for research to improve the technology and help the industry.

Lithium-ion batteries (LIBs) are widely used in transportation, energy storage, and other fields. The prediction of the remaining useful life (RUL) of lithium batteries not only provides a reference for health management but also serves as a basis for assessing the residual value of the battery. In order to improve the prediction accuracy of the RUL of LIBs, a two-phase RUL early prediction method combining neural network and Gaussian process regression (GPR) is proposed. In the initial phase, the features related to the capacity degradation of LIBs are utilized to train the neural network model, which is used to predict the initial cycle lifetime of 124 LIBs. The Pearson coefficient’s two most significant characteristic factors and the predicted normalized lifetime form a 3D space. The Euclidean distance between the test dataset and each cell in the training dataset and validation dataset is calculated, and the shortest distance is considered to have a similar degradation pattern, which is used to determine the initial Dual Exponential Model (DEM). In the second phase, GPR uses the DEM as the initial parameter to predict each test set’s early RUL (ERUL). By testing four batteries under different working conditions, the RMSE of all capacity estimation is less than 1.2%, and the accuracy percentage (AP) of remaining life prediction is more than 98%. Experiments show that the method does not need human intervention and has high prediction accuracy.

China is vigorously promoting the “whole county promotion” of distributed photovoltaics (DPVs). However, the high penetration rate of DPVs has brought problems such as voltage violation and power quality degradation to the distribution network, seriously affecting the safety and reliability of the power system. The traditional centralized control method of the distribution network has the problem of low efficiency, which is not practical enough in engineering practice. To address the problems, this paper proposes a cluster voltage control method for distributed photovoltaic grid-connected distribution network. First, it partitions the distribution network into clusters, and different clusters exchange terminal voltage information through a “virtual slack bus.” Then, in each cluster, based on the control strategy of “reactive power compensation first, active power curtailment later,” it employs an improved differential evolution (IDE) algorithm based on Cauchy disturbance to control the voltage. Simulation results in two different distribution systems show that the proposed method not only greatly improves the operational efficiency of the algorithm but also effectively controls the voltage of the distribution network, and maximizes the consumption capacity of DPVs based on qualified voltage.

Interconnector is a critical component to construct solid oxide cells (SOCs) stack. Oxidation of metallic interconnectors and Cr poisoning caused by oxidation are important factors that lead to long-term performance degradation of SOCs. Coating on the interconnector surface is an important approach to inhibit the oxidation and Cr migration of the interconnector. Herein, (La_0.75Sr_0.25)_0.95MnO_3−δ (LSM) and Mn_1.5Co_1.5O₄ (MCO) are used to fabricate the coatings of interconnector. Two advanced thermal spray technology, atmospheric plasma spraying (APS) and low-pressure plasma spray (LPPS), are adopted for the coating preparation. The electrochemical performance, rising and cooling cycle stability, and Cr diffusion inhibition performance of the coatings are tested and evaluated. The result indicates that MCO can generate more uniform and denser coatings than LSM. In addition, MCO coatings prepared by LPPS shows the best electrochemical performance, rising and cooling cycle stability, and Cr diffusion inhibition. The initial area specific resistance (ASR) is 0.0027 Ω·cm² at 800 °C. After 4 cooling cycle tests, the ASR increases to 0.0032 Ω·cm² but lower than other samples. Meanwhile, the relative intense of Cr at the interface of SUS430 with MCO coatings fabricated by LPPS is lower than that of MCO fabricated by APS after 4 rising and cooling cycle operations, showing more favorable Cr diffusion inhibition performance.

Aqueous zinc-ion batteries (ZIBs) have great prospects for widespread application in massive scale energy storage. By virtue of the multivalent state, open frame structure and high theoretical specific capacity, vanadium (V)-based compounds are a kind of the most developmental potential cathode materials for ZIBs. However, the slow kinetics caused by low conductivity and the capacity degradation caused by material dissolution still need to be addressed for large-scale applications. Therefore, sodium vanadate Na₂V₆O₁₆·3H₂O (NVO) was chosen as a model material, and was modified with alumina coating through simple mixing and stirring methods. After Al₂O₃ coating modification, the rate capability and long-cycle stability of Zn//NVO@Al₂O₃ battery have been significantly improved. The discharge specific capacity of NVO@Al₂O₃ reach up to 228 mAh/g (at 4 A/g), with a capacity reservation rate of approximately 68% after 1000 cycles, and the Coulombic efficiency (CE) is close to 100%. As a comparison, the capacity reservation rate of Zn//NVO battery is only 27.7%. Its superior electrochemical performance is mainly attributed to the Al₂O₃ coating layer, which can increase zinc-ion conductivity of the material surface, and to some extent inhibit the dissolution of NVO, making the structure stable and improving the cyclic stability of the material. This paper offers new prospects for the development of cathode coating materials for ZIBs.

Advancing portable electronics and electric vehicles is heavily dependent on the cutting-edge lithium-ion (Li-ion) battery technology, which is closely linked to the properties of cathode materials. Identifying trends and prospects of cathode materials based on patent analysis is considered a kernel to optimize and refine battery related markets. In this paper, a patent analysis is performed on 6 popular cathode materials by comprehensively considering performance comparison, development trend, annual installed capacity, technology life cycle, and distribution among regions and patent assignees. In the technology life cycle, the cathode materials majorly used in electric vehicle have entered maturity stage, while the lithium cobalt oxide (LCO) cathode that is widely used in portable electronics is still in the growth stage. In global patent distributions, China holds more than 50% of total patents. In the top 10 patent assignees of 6 cathode materials, 2 institutes are from China with the rest being Japan (6) and Republic of Korea (2), indicating that the technology of cathode materials in China is relatively scattered while cathode research is highly concentrated in Japan and Republic of Korea. Moreover, the patent distribution has to consider practical issues as well as the impacts of core patents. For example, the high cost discourages the intention of applying international patents. This paper is expected to stimulate battery research, understand technical layout of various countries, and probably forecast innovative technology breakthroughs.