journal article·2024-10

A Multifault Testing Method for TSVs Based on GAF-DRSN and Mirror Constant Current Source Structure

Yuling Shang, Longlu Geng, Chunquan Li, Zhuofan Song, Gefei Duan, Jintao Zhang, Junji Li

Publisher page

Abstract

Three-dimensional stacked integration based on through-silicon via (TSV) meets the high-speed development requirements of integrated circuits (ICs). However, TSV is a sensitive unit prone to manufacturing defects, with common faults being void faults and leakage faults. When TSV exhibits multifault, such as simultaneous resistive void fault and current leakage fault, the reliability of 3-D ICs is significantly reduced compared to single faults. To address this, this article proposes a TSV multifault testing method based on a Gramian angular field (GAF), deep residual shrinking network (DRSN), and a mirror constant current source structure. The mirror constant current source circuit is initially designed in the method, with the load structure being TSV and TSV charge/discharge rates are measured as testing parameters. Then, the GAF is employed to transform the acquired charge/discharge signals into 2-D images. Ultimately, the DRSN model should be applied to precisely detect faults in the transformed TSV images representing different fault types. The results demonstrate the effectiveness of the proposed method in classifying TSV fault types, with an average accuracy exceeding 98%. The method exhibits notable advantages, including high accuracy and robust generalization capabilities.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Integrated Circuits and Semiconductor Failure Analysis · Semiconductor materials and devices · 3D IC and TSV technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, China

Department of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, China

Funding

National Natural Science Foundation of China · Innovation Project of Guangxi Graduate Education

References (29)

Show source-provided references
1. 10.1109/ectc.2019.00-2210.1109/ectc.2019.00-22 ↗
2. 10.1109/ipfa.2017.806006010.1109/ipfa.2017.8060060 ↗
3. 10.1016/j.mee.2014.10.01910.1016/j.mee.2014.10.019 ↗
4. 10.1016/j.matlet.2017.02.04110.1016/j.matlet.2017.02.041 ↗
5. 10.1115/1.403839210.1115/1.4038392 ↗
6. 10.1007/s10836-017-5681-x10.1007/s10836-017-5681-x ↗
7. 10.1007/s10836-019-05824-w10.1007/s10836-019-05824-w ↗
8. 10.1007/s12652-021-02964-w10.1007/s12652-021-02964-w ↗
9. 10.1109/TCAD.2018.282155910.1109/TCAD.2018.2821559 ↗
10. 10.1109/VTS50974.2021.944105810.1109/VTS50974.2021.9441058 ↗
11. 10.1109/ITC-Asia53059.2021.980849210.1109/ITC-Asia53059.2021.9808492 ↗
12. 10.1109/TEST.2018.862469110.1109/TEST.2018.8624691 ↗
13. 10.1109/ICSICT.2016.799862610.1109/ICSICT.2016.7998626 ↗
14. 10.1109/ACCESS.2018.287964010.1109/ACCESS.2018.2879640 ↗
15. 10.1109/TCAD.2018.288705110.1109/TCAD.2018.2887051 ↗
16. 10.1109/TCAD.2021.311435710.1109/TCAD.2021.3114357 ↗
17. 10.1038/s41598-022-08179-z10.1038/s41598-022-08179-z ↗
18. 10.1109/TCPMT.2017.278889610.1109/TCPMT.2017.2788896 ↗
19. 10.1007/s10836-020-05916-y10.1007/s10836-020-05916-y ↗
20. 10.1109/ECTC32696.2021.0026210.1109/ECTC32696.2021.00262 ↗
21. 10.1109/ICTA56932.2022.996304010.1109/ICTA56932.2022.9963040 ↗
22. 10.1109/TCAD.2017.266660410.1109/TCAD.2017.2666604 ↗
23. 10.3390/electronics1204090810.3390/electronics12040908 ↗
24. 10.1109/VTS.2015.711626710.1109/VTS.2015.7116267 ↗
25. 10.1109/ICEPT47577.2019.24516310.1109/ICEPT47577.2019.245163 ↗
26. Imaging time-series to improve classification and imputation
27. 10.1109/ACCESS.2023.324136710.1109/ACCESS.2023.3241367 ↗
28. 10.1109/TII.2019.294389810.1109/TII.2019.2943898 ↗
29. 10.1109/AIEA53260.2021.0007710.1109/AIEA53260.2021.00077 ↗