An investigation of post treatment on properties and structure of ultrahigh molecular weight polyethylene parts prepared by selective laser sintering for biomedical application

Combined with customization advantage of selective laser sintering (SLS) and excellent performance of ultrahigh molecular weight polyethylene (UHMWPE), it is possible to meet the requirements of artificial joints for biomedical application. However, high viscosity of UHMWPE melt limits the strength of UHMWPE sintered parts. Inspired from metal and ceramic materials, this work aims to improve the performance of UHMWPE parts prepared by SLS using post treatment methods, including heat treatment and hot isostatic pressure (HIP) treatment. Consequently, HIP treatment shows superiority on promoting the performance of UHMWPE sintered parts compared with heat treatment. With the condition of temperature and isostatic pressure, a novel definition of “bonding neck” is given to explain the enhancement of cohesion between each UHMWPE particle in different post treatment. Without any fortifier, the biological safety of artificial joints manufactured by SLS is further guaranteed. Under the isostatic pressure of 12 MPa and temperature of 185°C in HIP treatment, the mechanical strength, tribological performance and other properties are improved dramatically. The tensile strength of the specimen is up to 8.0 MPa, the elongation at break is 99.3%, the impact strength is 8.8 MPa, the friction coefficient is 0.11, the wear rate is 9.3 × 10^?4 mm³/Nm and samples do not show cytotoxicity at the same time.     

锂离子电池正极材料的第一性原理

锂离子电池的发展主要依赖于电极材料的突破,解决现有电极材料存在的问题和预测新型未知材料是提高锂离子电池性能的关键,而第一性原理计算的出现能够较好地满足这一需求.本文介绍了第一性原理计算在锂离子电池正极材料研究方面的原理和应用,对该原理在正极材料的平均嵌锂电压计算、嵌/脱锂机理、结构稳定性研究及新材料预测等方面的应用进行了详细论述,并指出了这一理论计算工具在电池材料设计过程中的重要性和局限性.     

Continuous detrended cross-correlation analysis on generalized Weierstrass function

The paper mainly introduces a continuous detrended cross-correlation analysis method to detect the long-range fractal scaling behaviors of continuous and integrable functions. The effects of such method are tested by the generalized Weierstrass function with various seeds. It presents accurate scaling characterization as desired by comparing with that from the popular detrended cross-correlation analysis method of discrete case.     

Intelligent detection of rail corrugation using ACMP-based energy entropy and LSSVM

In this paper, an intelligent method to diagnose rail corrugation based on signal decomposition and entropy theory is proposed. The axle box acceleration signals are first decomposed into several components with different frequency bands by ACMP, EEMD and MODWT. By comparison, ACMP is able to successfully extract rail corrugation component from original signal without mode mixing. Energy entropy is then introduced here to quantify the degree of the rate of energy concentration. The analysis results show that the energy will change when rail corrugation occurs and the entropy will become small. It has been also proved that the entropy difference of rail corrugation and normal signal based on ACMP is the most significant. In addition, to intelligently diagnose rail corrugation, we combine energy entropy with energy index and the first mode energy, regarded as the input feature vector of LSSVM, to distinguish rail corrugation from mass data sets. It is obvious that the accuracy of ACMP-based technique is the highest.

     

Estimation on complexity of time series using generalized distance components statistics

Nonlinear Dynamics - In this paper, we propose the generalized distance components (GDISCO) approach that enables us to estimate the complexity of time series from the perspectives of time and...     

Improved properties of polymer electrolyte by ionic liquid PP1.3TFSI for secondary lithium ion battery

A new kind of polymer electrolyte is prepared from N-methyl-N-propylpiperidinium bis (trifluoromethanesulfonyl) imide (PP1.3TFSI), polyethylene oxide (PEO), and lithium bis (trifluoromethanesulfonyl) imide (LiTFSI). IR and X-ray diffraction results demonstrate that the addition of ionic liquid decreases the crystallization of PEO. Thermal and electrochemical properties have been tested for the solid polymer electrolytes, the addition of the room temperature molten salt PP1.3TFSI to the conventional P(EO)₂₀LiTFSI polymer electrolyte leads to the improvement of the thermal stability and the ionic conductivity (x = 1.27, 2.06 × 10⁻⁴ S cm⁻¹ at room temperature), and the reasonable lithium transference number is also obtained. The Li/LiFePO₄ cell using this polymer electrolyte shows promising reversible capacity, 120 mAh g⁻¹ at room temperature and 164 mAh g⁻¹ at 55 °C.     

对称性对Schrodinger算子特征向量存在性的影响

讨论了sl2（C）中矩阵乘积的迹的性质；证明了离散Schrodinger算子H在其势Vn为Thue－Morse序列或准对称序列时，在空间Co（Z）内不存在特征向量．     

Multifractal Fourier detrended cross-correlation analysis of traffic signals

Multifractal detrended cross-correlation analysis (MF-DXA) has been developed to detect the long-range power-law cross-correlation of considered signals in the presence of non-stationarity. However, crossovers arising from extrinsic periodic trends make the scaling behavior difficult to analyze. We introduce a Fourier filtering method to eliminate the trend effects and systematically investigate the multifractal cross-correlation of simulated and real traffic signals. The crossover locations are found approximately corresponding to the periods of underlying trend. Traffic velocity on one road and flows on adjacent roads show strong cross-correlation. They also present weak multifractality after periodic trends are removed. The traffic velocity and flow are cross-correlated in opposite directions which is accordant to their actual evolution.     

Weighted multiscale permutation entropy of financial time series

In this paper, we propose the weighted multiscale permutation entropy (WMPE) as a novel measure to quantify the complexity of nonlinear time series containing amplitude-coded information. WMPE is different from multiscale permutation entropy (MPE) in the sense that it suits better signals having considerable amplitude information and also succeed in accounting for the multiple time scales inherent in the financial systems. We first perform the MPE and WMPE methods on synthetic data showing the power of WMPE. Then, we apply the MPE and WMPE methods to the US and Chinese stock markets and make a comparison to discuss their differences and similarities between these different markets. The WMPE of each US and Chinese stock market points out the necessity of applying permutation entropy on multiple scales and reveals amplitude-coded information contained in the signals and immunity to degradation by noise when \(m = 5-7\) . Some new conclusions are gotten by the new characteristics we detected in the comparison. WMPE method can distinguish ShangZheng and ShenCheng from these markets and imply that HSI is more similar to the US markets. WMPE moves the fluctuation range of entropy values of different market down differently reflecting more accurate complexity of different stock markets containing amplitude information. Compared WMPE of ShangZheng and ShenCheng with the WMPE of US markets and HSI, US stock market and HSI may have more amplitude information carried by the signals of stock market. Furthermore, compared with MPE, WMPE can reduce the standard deviation which ensures the results more robust. The conclusion that \(m = 7\) is the best embedding dimension to investigate the WMPE results can be drawn because the WMPE tends to be stable in a certain range and reflects the necessity of investigation on multiscale and advantages of adding different weight, and it can distinguish these markets while reducing the standard deviations of all the markets.     

Modified generalized multiscale sample entropy and surrogate data analysis for financial time series

Nonlinear Dynamics - Complexity in time series is an intriguing feature of living dynamical systems such as financial systems, with potential use for identification of system state. Multiscale...