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Of great significance is knowledge of failure modes of IGBT modules under power cycling test (PCT) in advance. It can not only precisely determine accurate utilization of physics-of-failure lifetime prediction methods but also help optimize IGBT designs. However, establishing an accurate and generic offline failure mode classification method for different IGBT modules remains a challenging problem due to the complex degradation process of IGBT modules. In this article, a data-driven convolutional neural network (CNN) based method is proposed for quad-classification of failure modes for different IGBT modules under different PCT conditions. First, in order to accurately characterize the mapping between the failure modes and the precursor parameters, a framework of precursor parameters is meticulously established. Then, mainly using collected training data from existing publications, the CNN classification model is developed by a newly dynamic tuning-multilevel particle swarm-back propagation optimization algorithm. Finally, experimental PCTs of various IGBT modules are performed. The obtained PCT data and additional testing data from existing publications are used to verify the generalizability and robustness of the proposed classification method. The superiority of the proposed method is well demonstrated through comparison with random CNN, the state-of-the-art particle swarm optimization CNN, and other intelligent algorithms.

Lift-off of aluminum bond wires is one of the main failure mechanisms of insulated gate bipolar transistor (IGBT) modules. Its root cause is the crack propagation, which causes reduction in the contact area of bond wires at the bond-metallization interface. Thus, lifetime prediction based on the classic Paris law is very appealing due to its capability to account for such a failure mechanism. However, Paris law is currently restricted due to its dependency on inaccurate but expensive means to observe the crack rate. In this article, an analytical calculation method for the crack length of bond wires is proposed by the degradation curves of VCE,on measured during normal power cycling tests. The dye-and-pry method has been used to measure crack lengths to further validate the proposed analytical calculation method. The proposed analytical calculation method can avoid time-consuming measurement of crack length, and can economically calibrate the key constants c and m of Paris law, which has been employed to predict the lifetime of bond wires of IGBT modules by finite element method. Finally, the calibrated values of c and m make Paris law have better applicability to predict the lifetime of bond wires comparing c and m values reported in existing papers.

Spatial expression patterns of homeobox (HOX) genes delineate positional identity of primary fibroblasts from different topographic sites. The molecular mechanism underlying the establishing or maintaining of HOXgene expression pattern remains an attractive developmental issue to be addressed. Our previous work suggested a critical role of CTCF/cohesin-mediated higher- order chromatin structure in RA-induced HOXAactivation in human teratocarcinoma NT2/D1 cells. This study investigated the recruitment of CTCF and cohesin, and the higher-order chromatin structure of the HOXAlocus in fetal lung and adult foreskin fibroblasts, which display complementary HOXAgene expression patterns. Chromatin contacts between the CTCF-binding sites were observed with lower frequency in human foreskin fibroblasts. This observation is consistent with the lower level of cohesin recruitment and 5′ HOXAgene expression in the same cells. We also showed that CTCF-binding site A56 (CBSA56) related chromatin structures exhibit the most notable changes in between the two types of cell, and hence may stand for one of the key CTCF-binding sites for cell-type specific chromatin structure organization. Together, these results imply that CTCF/cohesin coordinates HOXAcluster higher-order chromatin structure and expression during development, and provide insight into the relationship between cell-type specific chromatin organization and the spatial collinearity.