Directional assist (0 1 0) plane growth in LiMnPO_(4) prepared by solvothermal method with polyols to enhance electrochemical performance

Phosphate material LiMnPO4 is popular for its high energy density(697 W·h·kg^(-1))and safety.When LiMnPO_(4) crystal grows,the potential barrier along b and c axis is strong,which makes the crystal grow along b axis to form a one-dimensional chain structure.However,the main migration channel of lithium ions in olivine structure is plane(010).By shortening the growth in the direction of b axis and enhancing the diffusion along the directions of a and c,two-dimensional nanosheets that are more conducive to the migration of lithium ions are formed.The dosage of polyols is the key factor guiding the dispersion of the crystals to the(010)plane.X-ray diffraction(XRD),Scanning electron microscopy(SEM),transmission electron microscopy(TEM)and other means are used to characterize the samples.After experiments,we found that when the ratio of polyol/water was 2:1,the morphology of the synthesized sample was 20–30 nm thick nanosheets,which had the best electrochemical performance.At 0.1C,the discharge specific capacity reaches 148.9 mA·h·g^(-1),still reaches 144.3 mA·h·g^(-1) at the 50th cycle.and there is still 112.5 mA·h·g^(-1) under high rate(5C).This is thanks to the good dispersion of the material in the direction of the crystal plane(010).This can solve the problem of low conductivity and ionic mobility of phosphate materials.

Adaptive Reduced Basis Methods Applied to Structural Dynamic Analysis

The reduced basis methods (RBM) have been demonstrated as a promising numerical technique for statics problems and are extended to structural dynamic problems in this paper. Direct step-by-step integration and mode superposition are the most widely used methods in the field of the finite element analysis of structural dynamic response and solid mechanics. Herein these two methods are both transformed into reduced forms according to the proposed reduced basis methods. To generate a reduced surrogate model with small size, a greedy algorithm is suggested to construct sample set and reduced basis space adaptively in a prescribed training parameter space. For mode superposition method, the reduced basis space comprises the truncated eigenvectors from generalized eigenvalue problem associated with selected sample parameters. The reduced generalized eigenvalue problem is obtained by the projection of original generalized eigenvalue problem onto the reduced basis space. In the situation of direct integration, the solutions of the original increment formulation corresponding to the sample set are extracted to construct the reduced basis space. The reduced increment formulation is formed by the same method as mode superposition method. Numerical example is given in Section 5 to validate the efficiency of the presented reduced basis methods for structural dynamic problems.

A Real-Time Transient Analysis of a Functionally Graded Material Plate Using Reduced-Basis Methods

Based on the hybrid numerical method (HNM) combining with a reduced-basis method (RBM), the real-time transient response of a functionally graded material (FGM) plates is obtained. The large eigenvalue problem in wavenumber domain has been solved through real-time off-line/on-line calculation. At off-line stage, a reduced-basis space is constructed in sample wavenumbers according to the solved eigenvalue problems. The matrices independent of parameters are projected onto the reduced-basis spaces. At on-line stage, the reduced eigenvalue problems of the arbitrary wavenumbers are built. Subsequently, the responses in wavenumber domain are obtained by the approximated eigen-pairs. Because of the application of RBM, the computational cost of transient displacement analysis of FGM plate is decreased significantly, while the accuracy of the solution and the physics of the structure are still retained. The efficiency and validity of the proposed method are demonstrated through a numerical example.

Controllable Morphology Tailoring with Solvothermal Method Toward LiMnPO_(4)/C Cathode Materials for Improved Performance and Favorable Thermostability

An environmentally friendly method for the synthesis of LiMnPO_(4)/C anode material for lithium-ion batteries by solvothermal method is introduced.The modification of the morphology of this precursor is altered by changing the ratio of the conditioning solvent(water-ethylene glycol solution)and the order of material addition.Ethylene glycol(EG)exerts a considerable influence on synthesizing LiMnPO_(4)/C flake-like nanocrystal,which benefits the extraction/insertion reaction of lithium ions and improves the electrochemical activity and electrochemical performance of LiMnPO_(4)/C material.When the solvent composition is H_(2)O:EG=1:3,exhibiting exceptional charge/discharge performance and rate capability,the specific discharge capacities are 155.8,153.7,148.8,141.4,129.5,and 112.6 mAh g^(−1) at the 0.1,0.2,0.5,1,2,and 5 C rates,respectively.When the charge-discharge rate returns to 0.1 C,the LiMnPO_(4)/C material shows a reversible discharge specific capacity of 153.7 mAh g^(−1).Differential scanning calorimetry(DSC)tests verify that the thermodynamic stability of the prepared LiMnPO_(4)/C(LMP)and commercial LiFePO_(4)(LFP)materials is better than that of commercial nickel-cobalt-aluminum(NCA)ternary materials.These prepared LiMnPO_(4)/C composites have high electrochemical capacity and cycle stability.

Fault diagnosis for lithium-ion batteries in electric vehicles based on signal decomposition and two-dimensional feature clustering

Battery fault diagnosis is essential for ensuring the reliability and safety of electric vehicles(EVs).The existing battery fault diagnosis methods are difficult to detect faults at an early stage based on the real-world vehicle data since lithium-ion battery systems are usually accompanied by inconsistencies,which are difficult to distinguish from faults.A fault diagnosis method based on signal decomposition and two-dimensional feature clustering is introduced in this paper.Symplectic geometry mode decomposition(SGMD)is introduced to obtain the components characterizing battery states,and distance-based similarity measures with the normalized extended average voltage and dynamic time warping distances are established to evaluate the state of batteries.The 2-dimensional feature clustering based on DBSCAN is developed to reduce the number of feature thresholds and differentiate flaw cells from the battery pack with only one parameter under a wide range of values.The proposed method can achieve fault diagnosis and voltage anomaly identification as early as 43 days ahead of the thermal runaway.And the results of four electric vehicles and the comparison with other traditional methods validated the proposed method with strong robustness,high reliability,and long time scale warning,and the method is easy to implement online.

Scanning electron microscopy imaging of single-walled carbon nanotubes on substrates

Scanning electron microscopy （SEM） plays an indispensable role in nanoscience and nanotechnology because of its high efficiency and high spatial resolution in characterizing nanomaterials. Recent progress indicates that the contrast arising from different conductivities or bandgaps can be observed in SEM images if single-walled carbon nanotubes （SWCNTs） are placed on a substrate. In this study, we use SWCNTs on different substrates as model systems to perform SEM imaging of nanomaterials. Substantial SEM observations are conducted at both high and low acceleration voltages, leading to a comprehensive understanding of the effects of the imaging parameters and substrates on the material and surface-charge signals, as well as the SEM imaging. This unified picture of SEM imaging not only furthers our understanding of SEM images of SWCNTs on a variety of substrates but also provides a basis for developing new imaging recipes for other important nanomaterials used in nanoelectronics and nanophotonics.