【活動簡介】：

114學年度第2學期學術專題講座
時間：115/06/03(五)14:00-16:00
地點：國立臺南大學府城校區格致樓C305
講題：Accelerating the discovery of electronic packaging materials via machine learning frameworks

【講者】
劉禹辰 助理教授 / 國立成功大學機械工程學系

【活動簡介】
Traditional experimental trial-and-error approaches for modulating properties in multi-component systems are increasingly hindered by prohibitive costs and temporal inefficiencies. Recently, machine learning (ML) has emerged as a transformative paradigm for predicting complex material behaviors, ranging from electromigration kinetics and dielectric constants to irradiation embrittlement and machining wear [1-7]. This presentation details the implementation of an ML-based framework to systematically investigate the composition-property relationships in electronic packaging materials. By modeling critical performance metrics—including tensile strength, elongation, wettability, and electromigration resistance—this approach provides a robust predictive toolset. The results demonstrate how data-driven insights enable the accelerated design of next-generation solder chemistries with tailored functional performance.

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