Enhanced cycling performance and high energy density of LiFePO4 based lithium ion batteries

LiFePO4 attracts a lot of attention as cathode materials for the next generation of lithium ion batteries. However, LiFePO4 has a poor rate capability attributed to low electronic conductivity and low density. There is seldom data reported on lithium ion batteries with LiFePO4 as cathode and graphite as anode. According to our experimental results, the capacity fading on cycling is surprisingly negligible at 1664 cycles for the cell type 042040. It delivers a capacity of 1170 mAh for 18650 cell type at 4.5C discharge rate. It is confirmed that lithium ion batteries with LiFePO4 as cathode are suitable for electric vehicle application. (c) 2007 Elsevier B.V. All rights reserved.

Comparative observation of Ar, Ar-H-2 and Ar-N-2 DC arc plasma jets and their arc root behaviour at reduced pressure

Results observed experimentally are presented, about the DC arc plasma jets and their arc-root behaviour generated at reduced gas pressure without or with an applied magnetic field. Pure argon, argon-hydrogen or argon- nitrogen mixture was used as the plasma-forming gas. A specially designed copper mirror was used for a better observation of the arc-root behaviour on the anode surface of the DC non-transferred arc plasma torch. It was found that in the cases without an applied magnetic field, the laminar plasma jets were stable and approximately axisymmetrical. The arc-root attachment on the anode surface was completely diffusive when argon was used as the plasma-forming gas, while the arc-root attachment often became constrictive when hydrogen or nitrogen was added into the argon. As an external magnetic field was applied, the arc root tended to rotate along the anode surface of the non-transferred arc plasma torch.

Auxiliary particle implementation of the probability hypothesis density filter

Optimal Bayesian multi-target filtering is, in general, computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), we present a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency. Numerical examples are presented for two scenarios, including a challenging nonlinear observation model.

Experimental and theoretical study on numerical density evolution of short fatigue cracks

Fatigue testing was performed using a kind of triangular shaped specimen to obtain the characteristics of numerical density evolution for short cracks at the primary stage of fatigue damage. The material concerned is a structural alloy steel. The experimental results show that the numerical density of short cracks reaches the maximum value when crack length is slightly less than the average grain diameter, indicating grain boundary is the main barrier for short crack extension. Based on the experimental observations and related theory, the expressions for growth velocity and nucleation rate of short cracks have been proposed. With the solution to phase space conservation equation, the theoretical results of numerical density evolution for short cracks were obtained, which were in agreement with our experimental measurements.

Behavior of ar plasma formed in a high-density plasma source - an ecr reactor

In order to develop the ultra-large scale integration(ULSI), low pressure and high density plasma apparatus are required for etching and deposit of thin films. To understand critical parameters such as the pressure, temperature, electrostatic potential and energy distribution of ions impacting on the wafer, it is necessary to understand how these parameters are influenced by the power input and neutral gas pressure. In the present work, a 2-D hybrid electron fluid-particle ion model has been developed to simulate one of the high density plasma sources-an Electron Cyclotron Resonance (ECR) plasma system with various pressures and power inputs in a non-uniform magnetic field. By means of numerical simulation, the energy distributions of argon ion impacting on the wafer are obtained and the plasma density, electron temperature and plasma electrostatic potential are plotted in 3-D. It is concluded that the plasma density depends mainly on both the power input and neutral gas pressure. However, the plasma potential and electron temperature can hardly be affected by the power input, they seem to be primarily dependent on the neutral gas pressure. The comparison shows that the simulation results are qualitatively in good agreement with the experiment measurements.