Thermodynamic Multi-Field Coupling Optimization of Microsystem Based on Artificial Intelligence
-
Published:2023-02-09
Issue:2
Volume:14
Page:411
-
ISSN:2072-666X
-
Container-title:Micromachines
-
language:en
-
Short-container-title:Micromachines
Author:
Shan Guangbao1ORCID, Wu Xudong1ORCID, Li Guoliang1, Xing Chaoyang2, Zhang Shengchang1, Fu Yu3
Affiliation:
1. School of Microelectronics, Xidian University, Xi’an 710071, China 2. Beijing Institute of Aerospace Control Devices, Beijing 100039, China 3. China Academy of Aerospace Standardization and Product Assurance, Beijing 100071, China
Abstract
An efficient multi-objective optimization method of temperature and stress for a microsystem based on particle swarm optimization (PSO) was established, which is used to map the relationship between through-silicon via (TSV) structural design parameters and performance objectives in the microsystem, and complete optimization temperature, stress and thermal expansion deformation efficiently. The relationship between the design and performance parameters is obtained by a finite element method (FEM) simulation model. The neural network is built and trained in order to understand the mapping relationship. Then, the design parameters are iteratively optimized using the PSO algorithm, and the FEM results are used to verify the efficiency and reliability of the optimization methods. When the optimization target of peak temperature, bump temperature, TSV temperature, maximum stress and maximum thermal deformation are set as 100 °C, 55 °C, 35 °C, 180 Mpa and 12 μm, the optimization results are as follows: the peak temperature is 97.90 °C, the bump temperature is 56.01 °C, the TSV temperature is 31.52 °C, the maximum stress is 247.4 Mpa and the maximum expansion deformation is 11.14 μm. The corresponding TSV structure design parameters are as follows: the radius of TSV is 10.28 μm, the pitch is 65 μm and the thickness of SiO2 is 0.83 μm. The error between the optimization result and the target temperature is 2.1%, 1.8%, 9.9%, 37.4% and 7.2% respectively. The PSO method has been verified by regression analysis, and the difference between the temperature and deformation optimization results of the FEM method is not more than 3%. The stress error has been analyzed, and the reliability of the developed method has been verified. While ensuring the accuracy of the results, the proposed optimization method reduces the time consumption of a single simulation from 2 h to 70 s, saves a lot of time and human resources, greatly improves the efficiency of the optimization design of microsystems, and has great significance for the development of microsystems.
Funder
National Key Research and Development Program of China Science Fund for Creative Research Groups of the National Natural Science Foundation of China State Key Program of National Natural Science of China
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering
Reference33 articles.
1. Wu, X., Shan, G., Xing, C., Zhang, S., and Li, G. (2022, January 21–23). Microsystem Thermal Intelligent Optimization Based on Particle Swarm Algorithm. Proceedings of the 4th International Conference on Microelectronic Devices and Technologies, Corfu, Greece. 2. Through-Silicon Capacitor Interconnection for High-Frequency 3-D Microsystem;Shan;IEEE Trans. Compon. Packag. Manuf. Technol.,2019 3. Wang, M., Ma, S., Jin, Y., Wang, W., Chen, J., Hu, L., and He, S. (2021). A RF Redundant TSV Interconnection for High Resistance Si Interposer. Micromachines, 12. 4. Li, H., Zhu, K., Xu, T., Lei, K., and Xia, J. (2022). Design and Manufacture of Millimeter-Scale 3D Transformers for RF-IC. Micromachines, 13. 5. Pi, Y., Wang, W., and Jin, Y. (December, January 30). An accurate calculation method on thermal effectiveness of TSV and wire. Proceedings of the 2016 IEEE 18th Electronics Packaging Technology Conference (EPTC), Singapore.
|
|