The effect of silicon anisotropy on the thermal stress of TSV structure of 3D packaging chip under thermal cyclic loads

Liang, Jingyang; Ning, Minjie; Ding, Chao; Liu, Tianhan; Dai, Zongbei; Qin, Hongbo

doi:10.1109/icept52650.2021.9567933

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…Mobility is a function of stress, and even if stress does not have a destructive effect on the structure, it can affect the mobility of the substrate device, which in turn affects the overall performance [20,21,22,23]. Current studies on thermal stresses induced by TSV have focused on the surface of the silicon substrate around the TSV [24,25,26,27]. However, the TSV vertical switching channel direction is along the z-axis, so it is necessary to pay attention to the effect of internal radial thermal stresses from annealing on the TSV vertical switching mobility.…”

Section: Introductionmentioning

confidence: 99%

Effect of annealing residual stress on mobility of TSV vertical switch

Wang,

Ren,

Yin

et al. 2024

IEICE Electron. Express

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The effect of internal radial stress generated during the annealing process on the mobility of through-silicon via (TSV) vertical switch are analyzed in detail, by employing finite element software ANSYS and orthogonal experimental design method. The results show that, the TSV diameter has the largest effect on the mobility of the TSV vertical switch, while the equilateral triangle array produces the smallest effect of stress at the same distance.

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Section: Introductionmentioning

confidence: 99%

Effect of annealing residual stress on mobility of TSV vertical switch

Wang,

Ren,

Yin

et al. 2024

IEICE Electron. Express

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“…In the past, people mostly used some traditional methods to change TSV size structure for optimization such as FEM or ETC models. These traditional methods were too complicated and depended on expert experience [ 19 , 20 ]. The thermal stress coupling optimization problem of 3D microsystems is extremely complex, involving multiple physical fields such as electricity, heat, force, etc.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic Multi-Field Coupling Optimization of Microsystem Based on Artificial Intelligence

Shan

et al. 2023

Micromachines

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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.

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The effect of silicon anisotropy on the thermal stress of TSV structure of 3D packaging chip under thermal cyclic loads

Cited by 2 publications

References 6 publications

Effect of annealing residual stress on mobility of TSV vertical switch

Effect of annealing residual stress on mobility of TSV vertical switch

Thermodynamic Multi-Field Coupling Optimization of Microsystem Based on Artificial Intelligence

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