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Enhanced Simulation Accuracy and Design Optimization in Power Semiconductors Through Individual Aluminum Metallization Layer Modeling.

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Title: Enhanced Simulation Accuracy and Design Optimization in Power Semiconductors Through Individual Aluminum Metallization Layer Modeling.
Authors: Choi, Na-Yeon1,2 (AUTHOR), Kim, Sang-Gi2,3 (AUTHOR), Zhang, Sung-Uk1,2,3 (AUTHOR) zsunguk@deu.ac.kr
Source: Energies (19961073). May2025, Vol. 18 Issue 10, p2457. 20p.
Subjects: Power semiconductors, Finite element method, Thermography, Temperature distribution, Aluminum
Abstract: This study investigates the impact of modeling the aluminum (Al) metallization layer as an integrated part of the chip model, versus as an individual component, on the results of electrical–thermal analysis of power semiconductor packages using Finite Element Analysis (FEA), ANSYS 2024 R2. The results showed that modeling the aluminum metallization layer separately exhibited high consistency with actual thermal imaging data. Furthermore, based on these findings, we observed through simulations that the aluminum metallization layer plays a key role in improving the uniformity of current density and temperature distribution within the chip. Using the aluminum metallization layer model, we optimized the thickness, material, and design of the metallization layer, as well as the bonding wire material through the design of experiments (DOE) methodology. Under the optimized conditions, an optimal design is proposed to minimize the voltage–current ratio (VDS/IDS), maximum junction temperature, strain, and von Mises stress. This study systematically examines the influence of aluminum metallization layer modeling on FEA-based power semiconductor package simulations and is expected to serve as a valuable reference for future power device design utilizing finite element analysis. [ABSTRACT FROM AUTHOR]
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Enhanced Simulation Accuracy and Design Optimization in Power Semiconductors Through Individual Aluminum Metallization Layer Modeling.
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  Data: <searchLink fieldCode="AR" term="%22Choi%2C+Na-Yeon%22">Choi, Na-Yeon</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kim%2C+Sang-Gi%22">Kim, Sang-Gi</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Sung-Uk%22">Zhang, Sung-Uk</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> zsunguk@deu.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2025, Vol. 18 Issue 10, p2457. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Power+semiconductors%22">Power semiconductors</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Thermography%22">Thermography</searchLink><br /><searchLink fieldCode="DE" term="%22Temperature+distribution%22">Temperature distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Aluminum%22">Aluminum</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: This study investigates the impact of modeling the aluminum (Al) metallization layer as an integrated part of the chip model, versus as an individual component, on the results of electrical–thermal analysis of power semiconductor packages using Finite Element Analysis (FEA), ANSYS 2024 R2. The results showed that modeling the aluminum metallization layer separately exhibited high consistency with actual thermal imaging data. Furthermore, based on these findings, we observed through simulations that the aluminum metallization layer plays a key role in improving the uniformity of current density and temperature distribution within the chip. Using the aluminum metallization layer model, we optimized the thickness, material, and design of the metallization layer, as well as the bonding wire material through the design of experiments (DOE) methodology. Under the optimized conditions, an optimal design is proposed to minimize the voltage–current ratio (VDS/IDS), maximum junction temperature, strain, and von Mises stress. This study systematically examines the influence of aluminum metallization layer modeling on FEA-based power semiconductor package simulations and is expected to serve as a valuable reference for future power device design utilizing finite element analysis. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/en18102457
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        Text: English
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        PageCount: 20
        StartPage: 2457
    Subjects:
      – SubjectFull: Power semiconductors
        Type: general
      – SubjectFull: Finite element method
        Type: general
      – SubjectFull: Thermography
        Type: general
      – SubjectFull: Temperature distribution
        Type: general
      – SubjectFull: Aluminum
        Type: general
    Titles:
      – TitleFull: Enhanced Simulation Accuracy and Design Optimization in Power Semiconductors Through Individual Aluminum Metallization Layer Modeling.
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            – D: 15
              M: 05
              Text: May2025
              Type: published
              Y: 2025
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            – TitleFull: Energies (19961073)
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