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Sr2ScSbO5.6F0.4:Mn4+ presents excellent thermal stability and higher internal/external quantum efficiency with application prospects in indoor plant cultivation.

The physicochemical properties of starch acetates with an equal degree of substitution prepared from pea, corn, and wheat starch and their effects on frozen cooked noodle (FCN) quality were investigated. The result showed that the three kinds of starch acetates had different effects on the quality of FCN due to their different blue values, freeze-thaw stability, and crystalline morphology analyzed by XRD (

The joint action of the molecular rearrangement by SBE and a suitable mode of TPS complexation provides a mechanistic basis for inhibiting the digestion rate of CES–TPS complexes.

In this study, the effect of microwave-ultrasound or/and toughening treatment on the physicochemical, structural properties, and in vitro digestibility of A- and B-type granules isolated from wheat starch were investigated. From the SEM, microwave-ultrasound and toughening treatment (MU-T) led to the appearance of irregular and disrupted structure significantly and an increment in the resistant starch content of A- and B-type granule. Furthermore, the MU-T starch possessed the lowest swelling power, light transmittance, and gelatinization temperature range (Tc -To) and the highest ΔH. After MU-T, the relative crystallinity (RC) of X-ray pattern, Fourier transform infrared ratio of 1047/1022 cm-1, and the content of double helix and single helix of 13C CP/MAS NMR had increased significantly. In particular, there was a difference in the content of RS and SDS between A-starch granules and B-starch granules as well as their changes after modification (from 69.305% to 82.93 for A-starch and form 74.97% to 88.17 for B-starch, respectively), which was a similar trend with RC and helix content. This study indicated that, for both A-type granule and B-type granule starches, microwave-ultrasound and toughening treated samples had unique properties compared to singly modified starches.

Solution plasma process (SPP) was employed to degrade chitosan. The effects of the initial pH value and the distance between the electrodes on the steady shear flow behavior, structural characterization, molecular conformation, and antioxidant activity of chitosan were investigated. The results revealed that a lower initial pH value and a narrower distance between the electrodes were beneficial to the decrease in viscosity and increase in shear-thinning capacity. Structural characterization of the chitosan by FT-IR and

Lithium-ion batteries are common energy sources for electric vehicles, energy storage systems, and require characterization techniques to evaluate the states and performance. The low frequency dynamics of lithium-ion batteries are rarely described accurately in existing models, which leads to the inability to establish the equivalence relationship between the time-domain model and the frequency-domain model. In this study, the equivalence of time and frequency domain modeling of lithium-ion batteries is illustrated based on a comparison between the parameter values of the equivalent circuit model (ECM) obtained from the time domain and those of the same ECM from the frequency domain. The time-domain parameters are extracted from the Hybrid Pulse Power Characterization (HPPC), and the frequency-domain ECM is fitted by the Electrochemical impedance spectroscopy (EIS). The equivalence is verified by theoretical derivation and experiments.

In order to clarify the anisotropic mechanical behavior and corresponding microstructure evolution of extruded AZ31 Mg alloy under combined stress states, modified shear-tension specimens (STSs) and shear-compression specimens (SCSs) were specifically designed and tested by means of quasi-static uni-axial loading. The specimens with beveled opposed slots of different angles (0°, 15°, 30°, 45°, 60° and 75°) are used to obtain different τ/σn ratio (SN Ratio, τ/σn). With the SN Ratio increasing, different mechanical properties between STSs and SCSs are observed, i.e., equivalent yield strength and strain-hardening rate. These differences in deformation behavior are resulted from the activation stresses for twinning and slips. It is found that the deformation of extruded AZ31 Mg alloy under combined shear-tension stresses is dominated by the typical slips. In contrast, twinning dominates the deformation under combined shear-compression stresses. Noticeably, the ductility of extruded AZ31 could be effectively improved by a small shear (about half normal stress), because the prismatic slip is further activated under τ stress component and promotes the major deformation under σn stress based on microstructure and texture analysis. In addition, it is found that the fracture mechanism transformed from the micro-voids growth and coalescence to the internal voids shearing with the SN Ratio increasing from 0 to 3.732.

Bastnasite is the main ore mineral in many carbonatite-related rare earth element (REE) deposits, which account for ∼51% of rare-earth oxide reserves worldwide. However, the occurrence, geochemistry, and genetic significance of bastnasite has not been methodically investigated. The Cenozoic Mianning–Dechang (MD) REE belt in Sichuan Province, SW China, contains the Maoniuping, Dalucao, Lizhuang, and Muluozhai deposits as well as numerous smaller REE occurrences. Individual deposits within the belt contain different types of bastnasite-bearing ore, which provides a unique opportunity to explore in detail the common mechanisms controlling the formation of bastnasite-rich REE deposits. Here, we present detailed results from field observations and petrographic, geochemical, and fluid inclusion studies of bastnasite from the main MD deposits. Calcite, fluorite, and barite form stable mineral assemblages that are commonly overprinted by bastnasite. Homogenization temperatures of fluid inclusions in bastnasite of ∼150–270 °C (Dalucao and Lizhuang deposits) and 155–210 °C (Maoniuping deposit) are systematically lower than those of fluid inclusions in gangue minerals. Therefore, the petrographic studies and homogenization temperatures both show that large-scale crystallization of bastnasite took place during the later stage of the hydrothermal system. The bastnasite, relatively geochemically homogeneous within all of the MD deposits, is enriched in Ba (293–8425 ppm), Th (16.4–2527 ppm), and U (4.19–92.7 ppm), and relatively depleted in high field strength elements such as Nb (0.15–17.4 ppm), Ta (0.06–6.48 ppm), Zr (0.71–31.1 ppm), Hf (0.62–5.65 ppm), and Ti ( carbonatite , and ore veins. In comparison, the samples from the study area show an increase in average REE contents from syenites to carbonatites to ore veins (i.e., bastnasite-bearing ores) and finally to bastnasite. Lanthanum and Ce were commonly substituted by Th, U, Sc, Ba, and Sr supplied by more evolved hydrothermal fluids. Combining the present results with existing data, we present a three-stage model for the formation of carbonatite-related REE deposits. First, partial melting of metasomatized sub-continental lithospheric mantle, fluxed by REE- and CO2-rich fluids, forms the parental carbonatite–syenite magma. Second, Sr, Ba, and REEs are strongly partitioned into carbonatite melts during liquid immiscibility in the carbonatite–syenite magmatic system. Third, hydrothermal fluids exsolved from the crystalizing syenite and carbonatite magmas form ore veins with early gangue minerals and later bastnasite overgrowths. Consequently, barite, calcite, and fluorite assemblages are a valuable guide in REE exploration.

Lithium ion batteries experience volume deformation in service, leading to a large internal stress in modules and potential safety issues. Therefore, understanding the mechanism of volume deformation of a lithium ion battery is critical to ensuring the long-term safety of electric vehicles. In this work, the irreversible and reversible deformation of a large-format lithium ion battery under four degradation paths, including cycling at −5°C/1 C, 55°C/1 C and 25°C/4 C, and storage at 55°C/100% state of charge, are investigated using laser scanning. The reversible deformation decreases while the irreversible deformation increases as batteries age, following a linear trend with the state of health. The mechanism behind irreversible deformation is investigated using incremental capacity analysis and scanning electron microscopy. The irreversible deformation of the battery cycled at 25°C/4 C and stored at 55°C becomes extremely large below 80% state of health, mainly because of the additional deposit layers on the anode and increased gas production, respectively. Mechanical calculations show the huge stress in the aged modules. Proper spacers between batteries are suggested to reduce such damage. This study is valuable for understanding the mechanical safety of battery modules.

Lithium plating leads to severe capacity fading and possible safety problems in lithium-ion batteries (LiB). Therefore, it is necessary to provide an in-situ detection methodology of lithium plating evolution during battery cycling. Qualitative analysis of the Distribution of Relaxation Times (DRT), based on Electrochemical Impedance Spectroscopy (EIS) deconvolution, shows a different degradation mechanism between lithium plating and normal aging batteries. A Support Vector Machine (SVM) detection algorithm based on the DRT is proposed. It only relies on the measured capacity and EIS data during battery aging, which is also easy to process and non-destructive to battery sample. The method has a significant advantage in battery safety management and echelon selection of retired batteries.

Zirconium (Zr) alloy is a promising fuel cladding material used widely in nuclear reactors. Usually, it is in service for a long time under the effects of neutron radiation with high temperature and high pressure, which results in thermomechanical coupling behavior during the service process. Focusing on the UO2/Zr fuel elements, the macroscopic thermomechanical coupling responses of pure Zr, Zr-Sn, and Zr-Nb binary system alloys, as well as Zr-Sn-Nb ternary system alloy as cladding materials, were studied under neutron irradiation. As a heat source, the thermal conductivity and thermal expansion coefficient models of the UO2 core were established, and an irradiation growth model of a pure Zr and Zr alloy multisystem was built. Based on the user material subroutine (UMAT) with ABAQUS, the current theoretical model was implemented into the finite element framework, and the consequent thermomechanical coupling behavior under irradiation was calculated. The distribution of temperature, the stress field of the fuel cladding, and their evolution over time were analyzed. It was found that the stress and displacement of the cladding were sensitive to alloying elements due to irradiated growth.

Summary Heating battery at low temperatures is fundamental to avoiding the range anxiety and the time-consuming charging associated with electric vehicles (EVs). One method for achieving fast and uniform battery heating is to polarize the cell under pulse currents. However, the on-board implementation of this method leads to an increase in the cost and size. Therefore, in this study, an adapted EV circuitry compatible with the existing one and an optimized operating condition are proposed to enable rapid battery heating. With this circuit, electricity transfer between the cells can be realized through a motor, leading to remarkably higher battery currents than those of the conventional circuit. The increase in the maximum heating currents (from 1.41C to 4C) resulted in a battery temperature rise of 8.6°C/min at low temperatures. This heating method exhibits low cost, high efficiency, and negligible effects on battery degradation, practical and promising on battery heating of EVs., Graphical abstract, Highlights • Rapid temperature rise, high efficiency, and low cost for battery heating are obtained • The batteries are divided into two modules and connected to the inverter individually • The electricity transferred between battery modules is motivated by a static motor • The pulse currents for battery heating are improved significantly at any frequency, Electrochemistry; Electrochemical Energy Storage; Energy Engineering; Energy Systems; Energy Materials

The solid phase diffusion (SPD) time constant (SPD-TC) is an important parameter of the fractional-order model (FOM) of the lithium-ion battery. The estimation of SPD-TC is one of significant problem for the battery aging analysis. Both a three-electrode pouch cell with a copper micro-reference electrode and the electrochemical impedance spectroscopy (EIS) are employed to identify the SPD-TC recent years but the method is hardly used in the field of engineering applications. This paper proposes a method to estimate the SPD-TC based on time-domain data of two-electrode battery and a back propagation neural-network (BPNN). First, the FOM of the battery is adopted to generate samples to train a BPNN. Then, the terminal voltage of a ternary lithium-ion battery, measured by a step current discharge experiment, is used as the input of the trained BPNN, and SPD-TCs of positive and negative electrodes are estimated. Finally, the error is analyzed according to the EIS of the positive and negative electrodes.

Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.

The corrosion damage is easy to be formed on the surface of a metal structure in the corrosion environment, then the structural mechanical properties are degraded. For this purpose, the cellular automata method was adopted to simulate the uniform corrosion damage behavior of aluminium alloy in this paper. The uniform corrosion of aluminium alloy surfaces is simulated in complex corrosive environments and different concentration of corrosion solution. The forming processes of corrosion and the changed rules under different concentration of corrosion solution c and ambient temperature T are all obtained. It was shown that with the increasing concentration of corrosion c and the ambient temperature T, the number of corrosion cells increased, and the number of corrosion cells presents an approximate power function of etching time t.

The traditional time-domain equivalent circuit model (ECM) for Li-ion batteries may achieve high accuracy by identifying model parameters through limited dynamic conditions. However, the traditional ECM (TECM) parameter matching techniques based on time-domain may have the problem of adaptability of working conditions. To solve the problem of dependence on time-domain working conditions and improve the stability of the full-cycle modeling of lithium batteries, it is critical to establish the ECM based on the principle of electrochemical impedance spectroscopy (EIS). However, the full-frequency domain ECM structures (FECM) and the corresponding parameters based on the whole frequency ranges of the EIS employ too many resources for on-line estimation. In this paper, we firstly analyze the frequency region of the standard operating conditions of electric vehicles and theoretically discuss the rationality of the Simplified ECM base on the low-frequency region of the EIS. The proposed low-frequency domain ECM (LECM) simplifies the elements that describe the medium-high frequency regions of the EIS. It only uses the low-frequency region of the EIS to identify the model parameters. The results show that the accuracy of the proposed LECM is almost the same as that of FECM, and saves an average of 40% of the calculation load.

Battery degradation cost is one of the major concerns when designing energy management strategies of DC microgrids. However, many battery degradation models used in the previous works are over-simplified and the effectiveness of which has not been verified. As a result, this paper presents a comparative study of the impact of battery aging models on energy management of the microgrid. Four popular single factor-based semi-empirical models are investigated while a combined factor-based Combined Arrhenius-Peukert-NREL (CAPN) model is proposed with the best fitting performance compared with the experimental data. The five degradation models are considered as part of the objective function in the particle swarm optimization-based energy management structure of a grid-connect microgrid. The optimized power scheduling and state of charge trajectory of the battery under different single factor-based models exhibit enormous deviations, so as the calculated total costs, which have the maximum error of 63.9% compared with the CAPN model. The application of the studied single factor-based models will also result in 3.5%–12.5% additional actual operating cost under non-optimal conditions. This paper first reveals the significant and unneglectable influence of the simplified degradation models on the microgrid energy management, the abandon of the single factor-based models is also recommended.

Solid phase diffusion plays an important role in the long-term performances of lithium-ion batteries. Current mechanistic model for describing the solid phase diffusion has low computational efficiency and obscure physical meanings. A simple but effective physics-based solid phase diffusion model is of great significance for the impedance characterization and aging diagnosis of lithium-ion batteries. In this paper, a physics-based fractional-order model is established by simplifying the solid phase diffusion process through Pade approximation. A full-cell fractional-order model is constructed by combining the medium-high frequency dynamic model. The proposed model has a clear physical meaning and can be used to characterize full-cell performances. Furthermore, this paper provides solutions to identifying the parameters of the full-cell fractional-order model by decoupling the dynamics in frequency and spatial domain. The established full-cell fractional-order model is validated under various working loads. The results show that the proposed physics-based fractional-order model with simplified solid phase diffusion improves the computational efficiency with little loss of accuracy, indicating that the proposed model is an appropriate candidate for online applications.

Li-ion battery is a strongly coupled nonlinear time-varying device and is difficult to establish its deterministic mathematical model for online parameter identification and state estimation for the performance managements of battery. This paper proposes an AI model based on back-propagation neural network (BPNN). The training process is designed and the parameters of the network are determined referring the electrochemical mechanism of the battery. The performances of BPNN model are compared with the mathematical model using the voltage response of step-discharge current of battery. The experiments verify that BPNN model not only predicts the V-I characteristics accurately, but also shows associative and migratory abilities.

Fractional-order model (FOM) is recognized as a preferable model of Lithium-ion Battery because of the inherent mechanism and the simplicity of the parameters. However the identification of its parameters still difficult if just with a simple engineering process. This paper proposes a parameter identification method for the FOM, which combines a time-domain process and a frequency-domain process. The time-domain process is for identifying the fractional-order parameter of the model based on electrochemical impedance spectroscopy (EIS) and the frequency-domain process is for resistance and capacitor parameters of the model with a modified hybrid pulse power characteristic (HPPC). The inherent mechanism basis of the processes is described and the effectiveness of the method is verified both by constant current and dynamic experiments.

Thermal runaway is a major concern for the large-scale application of lithium-ion batteries. The thermal runaway performance of lithium-ion batteries not only depends on materials and cell design, but also changes with degradation. This paper presents a comparative investigation of the aging effects on the thermal runaway behavior of a large format lithium-ion battery. The batteries are first degraded under four different aging paths. The aging mechanisms are then investigated through post-mortem analysis on the battery at the end of life, by comparing the electrochemical properties, morphology and composition of the fresh and degraded electrodes. The thermal stabilities of the fresh and degraded electrodes are also evaluated using differential scanning calorimetry. Adiabatic thermal runaway tests are performed on the batteries at different states of health using accelerating rate calorimetry to reveal the evolution of battery thermal runaway performance under the four degradation paths. Finally, the correlations between the aging mechanism and the changes in battery thermal runaway behavior are summarized. The results show that the thermal stability of the anode+electrolyte thermodynamic system exhibits obvious changes, which contribute to the evolution of battery thermal runaway performance, while the thermal stability of the cathode remained unchanged. Lithium plating turns out to be the key reason for the deterioration of battery thermal runaway performance during aging process.