Lifetime Of Electronic Components Research Articles

Rational design of graphene/polymer composites with excellent electromagnetic interference shielding effectiveness and high thermal conductivity: a mini review

• This review concludes the works of composites using graphene as filler loadings to improve the thermal conductivity enhancement and EMI shielding performance • It was found that the graphene frameworks with the anisotropic orientation can achieve higher thermal conductivity enhancement efficiency and EMI SE at lower filler loading • This review also makes prospect for the development trend of graphene/polymer composites with high thermal conductivity and EMI shielding performance in the future The integration and miniaturization of chips lead to inevitable overheating and increasing electromagnetic interference (EMI) problems, which threaten the performance, stability, and lifetime of electronic components. Therefore, it is important to improve the heat dissipation and EMI shielding performance in device packaging for the steady operation of electronic products. In recent years, due to its intrinsic superior thermal conductivity, proper electrical conductivity, light-weight, and structural adjustability, graphene has been widely used as high thermal and conductive fillers incorporated in the polymer matrix to improve the thermal conductivity and electrical conductivity of composites. This review concludes the recent development of graphene/polymer composites by using graphene as fillers to improve the thermal conductivity and EMI shielding effectiveness (EMI SE). The structure of graphene embedded in the composites varies from zero-dimension (0D), one-dimension (1D) to two-dimensions (2D). Moreover, highly thermally and electrically conductive fillers with different dimensions were also modified on the graphene to improve the composite performance. Finally, this review also makes prospects for the development trend of graphene/polymer composites with high thermal conductivity and EMI SE in the future.

Application of machine learning in rapid analysis of solder joint geometry and type on thermomechanical useful lifetime of electronic components

Rapid reliability analysis of the solder joints in the electronic devices identifies as an appeared gap in the design stage. This paper demonstrates the feasibility of employing the neural network in the solder joint useful lifetime estimation. A dataset is prepared for training a deep neural network under different conditions using finite element simulations. The contributory parameters including thermal specifications, solder joint geometry and solder joint type are considered in 420 finite element simulations. While the proposed approach has a remarkably quick reliability assessment, the predicted results showed a maximum root mean square error of 3.2%. The results reveal that there exists an optimum solder joint volume in which the maximum useful lifetime under the certain thermal loading. Also, it is found that the hourglass type solder interconnection has better performance in comparison with barrel type solder interconnection as the reliability perspective owing to the more gentle triaxiality factor. Ability of rapid reliability analysis and effects consideration of key parameters on the solder joint reliability make this proposed method attractive in the design stage of electronic devices.

ASSESSING THE LIFETIME PERFORMANCE OF ELECTRONIC COMPONENTS BY CONFIDENCE INTERVAL

ABSTRACT The electronics industry has heavily prioritized enhancing the quality, lifetime and conforming rate(conforming to specifications) of electronic components, thus maximizing profitability. Various methods have been developed for assessing quality performance. In practice, process capability indices (PCIs) are used as a means of measuring process potential and performance. Moreover, most PCIs have been developed or investigated under assumption that electronic components have a lifetime with a normal distribution. However, PCIs for non-normal distributions have seldom been discussed. Nevertheless, the lifetime of electronic components generally possesses an exponential distribution. Under an exponential distribution, some properties of the PCIs and their estimators differ from those in a normal distribution. To more reasonably and accurately utilize the PCIs in assessing the lifetime performance of electronic components, this study constructs an UMVU estimator of their lifetime performance index under an exponential distribution. The UMVU estimator of the lifetime performance index is then utilized to develop the confidence interval. The purchasers can then employ the confidence interval to determine whether the lifetime of the electronic components adheres to the required level. Manufacturers can also utilize this procedure to enhance process capability.