東華大學圖書館 |

Multiscale Modeling and Optimization of Sintered Polycrystalline-Pore Die Attach System Under Hybrid Physical Fields /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multiscale Modeling and Optimization of Sintered Polycrystalline-Pore Die Attach System Under Hybrid Physical Fields // Zunyu Guan.
作者:	Guan, Zunyu,
面頁冊數:	1 electronic resource (122 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-06, Section: B.
Contained By:	Dissertations Abstracts International86-06B.
標題:	Package design. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31810369
ISBN:	9798346823087

Multiscale Modeling and Optimization of Sintered Polycrystalline-Pore Die Attach System Under Hybrid Physical Fields /
Guan, Zunyu,

Multiscale Modeling and Optimization of Sintered Polycrystalline-Pore Die Attach System Under Hybrid Physical Fields /Zunyu Guan. - 1 electronic resource (122 pages)

Source: Dissertations Abstracts International, Volume: 86-06, Section: B.

Wide bandgap (WBG) semiconductors like GaN and SiC are increasingly utilized in high-power applications due to their superior properties. This advancement presents challenges for electronic packaging technologies, especially under higher temperature and power conditions. Traditional highPb solder die attach materials are inadequate for these applications due to their unreliability and environmental hazards. Ag sintering materials emerge as a promising Pb-free alternative, offering excellent physical properties for high-power applications. The microstructural characteristics of sintered Ag, such as grain size, pore size, and porosity, significantly influence the reliability of the die attach layer.This research addresses the core scientific problem of establishing an upscaling framework that bridges nano-scale material properties to meso-scale microstructure features and their macro-scale reliabilities under hybrid physical fields for Ag sintering material. Through extensive experiments and numerical simulations, correlations between compositions, processing conditions, microstructure, and reliability were established. Using two types of Ag particles with different sizes, the master curves for grain growth and densification were constructed, leading to the development of a microstructural evolution model. Weighted Voronoi Tessellation polygons were employed to create digital models of polycrystalline porous structures, facilitating detailed analysis of mechanical responses and failure under thermal cycling loads. The phase-field simulations provided insights into the stress relief effects of high porosity on the overall packaging structure and the crack propagation within the microstructure, including crack initiation time, propagation rate, and the expected lifespan of the die attach layer. This informed the optimization of polycrystalline porous structures to enhance the reliability of packaging. Additionally, the desired polycrystalline porous structure guided the optimization of raw Ag particle sizes and sintering conditions through the microstructural evolution model.In summary, a multiphysics, multiscale modeling and optimization framework was established, providing a comprehensive approach to material selection and process optimization in Ag sintering technology. This study advances our understanding and capabilities in Ag sintering technology, offering robust foundations for optimizing sintered Ag microstructures in industrial production and product design.Future research will focus on three main directions: (1) Enhancing the representation of microstructures by utilizing techniques like Gaussian random fields to generate more diverse 2D samples. Additionally, 3D sub-models will be employed to better capture complex pore geometries and refine boundary conditions, providing more accurate insights into material behavior and reliability; (2) Extending the applicability of the research methodology beyond Ag sintering technology to various metal sintering processes, encompassing diverse metal types and applications beyond die attach materials; and (3) Enhancing the methodology's utility by employing machine learning techniques to construct models based on extensive simulation data, thereby circumventing the need for exhaustive experimental design and enabling package design and optimization through generative AI technology.

English

ISBN: 9798346823087Subjects--Topical Terms:

3689880
Package design.

Multiscale Modeling and Optimization of Sintered Polycrystalline-Pore Die Attach System Under Hybrid Physical Fields /
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520 $a Wide bandgap (WBG) semiconductors like GaN and SiC are increasingly utilized in high-power applications due to their superior properties. This advancement presents challenges for electronic packaging technologies, especially under higher temperature and power conditions. Traditional highPb solder die attach materials are inadequate for these applications due to their unreliability and environmental hazards. Ag sintering materials emerge as a promising Pb-free alternative, offering excellent physical properties for high-power applications. The microstructural characteristics of sintered Ag, such as grain size, pore size, and porosity, significantly influence the reliability of the die attach layer.This research addresses the core scientific problem of establishing an upscaling framework that bridges nano-scale material properties to meso-scale microstructure features and their macro-scale reliabilities under hybrid physical fields for Ag sintering material. Through extensive experiments and numerical simulations, correlations between compositions, processing conditions, microstructure, and reliability were established. Using two types of Ag particles with different sizes, the master curves for grain growth and densification were constructed, leading to the development of a microstructural evolution model. Weighted Voronoi Tessellation polygons were employed to create digital models of polycrystalline porous structures, facilitating detailed analysis of mechanical responses and failure under thermal cycling loads. The phase-field simulations provided insights into the stress relief effects of high porosity on the overall packaging structure and the crack propagation within the microstructure, including crack initiation time, propagation rate, and the expected lifespan of the die attach layer. This informed the optimization of polycrystalline porous structures to enhance the reliability of packaging. Additionally, the desired polycrystalline porous structure guided the optimization of raw Ag particle sizes and sintering conditions through the microstructural evolution model.In summary, a multiphysics, multiscale modeling and optimization framework was established, providing a comprehensive approach to material selection and process optimization in Ag sintering technology. This study advances our understanding and capabilities in Ag sintering technology, offering robust foundations for optimizing sintered Ag microstructures in industrial production and product design.Future research will focus on three main directions: (1) Enhancing the representation of microstructures by utilizing techniques like Gaussian random fields to generate more diverse 2D samples. Additionally, 3D sub-models will be employed to better capture complex pore geometries and refine boundary conditions, providing more accurate insights into material behavior and reliability; (2) Extending the applicability of the research methodology beyond Ag sintering technology to various metal sintering processes, encompassing diverse metal types and applications beyond die attach materials; and (3) Enhancing the methodology's utility by employing machine learning techniques to construct models based on extensive simulation data, thereby circumventing the need for exhaustive experimental design and enabling package design and optimization through generative AI technology.
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