Crosstalk noise modeling of multiwall carbon nanotube (MWCNT) interconnects using finite-difference time-domain (FDTD) technique

This paper presents an accurate and efficient model for the transient analysis of multiwall carbon nanotubes (MWCNT) using finite-difference time-domain (FDTD) method. The proposed model can be essentially used to analyze the functional and dynamic crosstalk effects of coupled-two MWCNT interconnect lines. Using the proposed model the voltage and current can be accurately estimated at any point on the interconnect line and furthermore, the model can be extended to coupled-n interconnect lines with a low computational cost. Crosstalk induced propagation delay, peak voltage, and its timing instance are measured using the proposed model and validated by comparing it to the HSPICE simulations. Over a random number of test cases it is observed that the average error in estimating the noise peak voltage on a victim line is less than 1%. The proposed model is extremely useful for accurate estimation of crosstalk induced performance parameters of MWCNT interconnects.     

Analytical long-term NBTI recovery model with slowing diffusivity and locking effect of hydrogen considered

The NBTI degradation caused by hole trapping in gate insulator process-related preexisting traps (∆ V_HT) and in generated bulk insulator traps (∆ V_OT) can recover in several seconds (< 10 s), whereas the long-term recovery is dominated by interface trap generation (∆ V_IT). In this paper, various explanations of NBTI recovery have been reviewed and a compact analytical long-term NBTI recovery model in which the slowing down diffusivity and locking effect of H₂ are involved has been derived. The triangular diffusion profile of H₂ is approximated and the fitting coefficient ξ of slowing down diffusivity is related to the stress and recovery time. Our proposed model has been validated by the previous theories and numerical calculation. Moreover, the investigation of NBTI recovery on a 40-nm CMOS process has been experimentally carried out and the results show that our compact NBTI recovery model can describe the long-term recovery well.     

Electrochemical corrosion and electrochemical migration of 64Sn-35Bi-1Ag solder doping with xGe on printed circuit boards

Ge-doped effects on electrochemical corrosion (ECC) and electrochemical migration (ECM) behaviors of 64Sn-35Bi-1Ag (SBA) solder on printed circuit boards (PCBs) in 3 wt% NaCl solutions were discussed. ECC was conducted by potentiodynamic polarization and electrochemical impedance (EIS) tests. Dendrites growth is a result of electrochemical migration (ECM) process, which is another factor affecting soldering reliability for electronic packagings, it was carried out as a designed schematic diagram coupled with a direct current power supply. Microstructures of products were investigated by SEM coupled with EDAX, XRD techniques. ECC results showed that anti-corrosive capacity increased as an increase of Ge addition in SBA solder which was expressed as the percent corrosion prevention (IE%), there was a maximal IE% value (83.74) when Ge addition was 0.5 wt%, this obtainment was consistent to EIS results. The probable reason was that Ge had a “skin collection” effect, that was, it highly enriched and segregated at edge of SBA solder, which protected Sn in SBA solder from being corroded. Microstructure of corrosive products was distinctly different for SBA solder with and without Ge addition. ECM results showed that the dendritic grown rate of pure SBA solder was slower than those of its candidates with Ge dopings. Dendrites of SBA solder with 0.5 wt% Ge addition grew to about 100–150 nm in length and 20–50 nm in width after ECM test for 8 h, they were nanorods arranged trimly into arborization. While dendrites was shorter under the same condition for pure SBA solder without Ge doping. The dendritic growth mechanism was tentatively discussed. It showed the loaded electronic field intensity during ECM process played an important role for dendritic formation owing to its controlling the dendritical crystal anisotropic growth rate. Medium concentrations had an another key effect, which affected by controlling the ion diffusion from anode to cathode. From the point of microelectronic packagings, Ge addition was advantage to improve anti-corrosion capacity of SBA solder, but it also reduced soldering reliability if ECM process took place in surrounding of wet and thermal weather.     

A cloud model-based method for the analysis of accelerated life test data

Various curve fitting models, including the Arrhenius stress model, inverse power law model, and Eyring model have been used to model the load (stress) – life relationship to aid in planning accelerated life tests; that is, the relationship between the mean of the sample lifetimes and the testing stress level. The load-life relationship is a one-to-one relationship: one mean of the sample lifetimes corresponds to one testing stress level. However, due to the random uncertainties existing in the testing stress, the relationship should be a many-to-many relationship rather than one testing stress corresponding one mean lifetime of the tested product. Based on the one-to-one relationship of the mean of the sample lifetimes to the testing stress level, a many-to-many relationship can be derived using the reasoning method presented in this paper. The reasoning method is constructed as ‘If X, then Y.’ X is termed the rule antecedent, and Y is called the rule consequent. They are constructed with the stress values and the sample lifetimes, respectively, based on the cloud model, which represents random uncertainty and fuzzy uncertainty. The reasoning method presented is called the multi-rule-based cloud reasoner, which can refine the one-to-one relationship established by models such as the Arrhenius stress model to a many-to-many relationship. In the case study, the multi-rule-based cloud reasoner was applied to a thermal stress accelerated life test of ammunition fuses. The results from the multi-rule-based cloud reasoner were compared with the estimation results from a normal cloud generator under a stress level of 20 °C. The results showed that the many-to-many relationship between the uncertain stress level and the means of the sample lifetimes was derived by the multi-rule-based cloud reasoner.     

考虑应力松弛和辐照影响的堆内构件压紧弹簧疲劳可靠性评估方法

针对反应堆堆内构件压紧弹簧疲劳失效模式,在考虑应力松弛和辐照影响的条件下基于仿真方法开展可靠性评估。首先结合疲劳模型和平均应力松弛Landgraf模型,考虑辐照对疲劳参数的影响,构建了压紧弹簧疲劳寿命模型。在压紧弹簧疲劳寿命模型基础上,根据广义应力-强度干涉模型定义压紧弹簧可靠度并开展灵敏度分析。以非能动压水堆AP1000压紧弹簧为例进行案例分析,在95%置信度水平下,分别计算了可靠度为95%和50%时对应的疲劳寿命。结果表明,若不考虑应力松弛,压紧弹簧总疲劳寿命下降88.3%;从经济性角度考虑寿命预测结果较为保守。通过灵敏度分析发现对可靠度影响较大的设计变量是弹性模量和疲劳强度系数,在一定可靠度下可以通过调整设计变量对压紧弹簧的疲劳可靠性评估进行优化。     

基于几何特征与流形距离的锂电池健康评估

作为实现电池健康管理的有效途径,精准的荷电状态估计和健康衰退状况评估能够很好的解决锂离子电池在实际使用过程中面临的可靠使用和安全管理问题。 考虑到现有电池健康衰退状况评估方法将监测数据放在欧氏空间进行分析,因而扭曲了数据的本质结构导致工况适用性差,利用流形学习挖掘隐藏在电池监测数据中的健康信息,并在流形空间中对锂离子电池健康状态进行度量。进行实例分析并对该方法的有效性进行了验证。