Advisor

(Version: August 2025)

本人現任國立臺灣大學材料科學與工程學系副教授，專長為金屬材料製程中的微觀機制解析與介觀尺度模擬技術開發，特別聚焦於「金屬凝固行為」與「顆粒材料流動行為」兩大關鍵領域。我所帶領的「凝固製程與流變實驗室」，致力於以科學方法理解材料微結構的形成機制，並且支持高性能、優異製程與永續性兼備之新世代金屬材料製程設計。

首先，金屬凝固是材料製程科學的核心基礎，涵蓋晶體成核、生長、偏析、界面遷移與微觀流動等耦合機制，不僅決定最初的微觀組織，也深刻影響後續加工行為與功能展現。為了深入掌握此一關鍵過程，我們整合相場模擬、計算相圖熱力學、同步輻射X光斷層掃描與顯微分析，發展可預測、可視化之多尺度模擬工具。

另一方面，針對材料中顆粒的流動與相互作用，我們結合離散元素法與計算流體力學耦合模擬，重現顆粒衝擊與堆積等現象。目前顆粒流變模擬技術應用於鋼鐵產線中的高溫風徑區反應行為模擬與數據化輸出，以及半固態鋁合金於模具填充與高固相區壓縮變形過程中的晶粒遷移與接觸行為分析。相場方法與離散元素法皆屬於介觀尺度計算材料學的關鍵工具，其特色即在於連結微觀機制與巨觀行為之間的橋樑，適用於複雜製程條件下的輸送、界面與組織演化分析。

目前實驗室的研究聚焦於下列四類金屬材料之製程設計與模擬：

1. 鋁合金與再生鋁材：針對凝固缺陷與晶出相控制議題，結合熱力學模擬、流變模擬、凝固曲線預測與熱處理優化技術，提升鋁材料之穩定性與應用潛力。

2. 鋼鐵材料與爐內行為模擬：發展顆粒流模擬技術與AI建模流程，用以分析高爐風徑區內流場變化。此外，亦針對鋼鐵熱機處理製程參數特性進行研究，並釐清其對微觀組織與力學性質的影響，有助於高強鋼材的製程優化。

3. 先進鎂合金製程設計：透過合金設計與熱處理製程優化，探討第二相析出行為與微觀結構穩定性之關聯，結合計算相圖模擬與實驗驗證，建立兼具機械性能與物化性質的高效製程設計原則。

4. 高熵與中熵合金凝固製程優化：使用相場模擬與計算相圖探討高性能高/中熵合金凝固偏析、初生相穩定性與均質化策略，建構製程-微結構之關聯模型，作為未來應用開發的基礎。

本人博士期間於英國倫敦帝國學院材料系從事半固態鋁合金之流變模擬研究，有幸回母系任教後則逐步推進凝固與相變機制的跨尺度模擬暨顯微結構分析技術。「凝固製程與流變實驗室」將持續聚焦於材料製程凝固與流變現象的數值預測、可視化以及實驗驗證，推動我國金屬材料製程與永續發展的接軌。

I am currently an Associate Professor in the Department of Materials Science and Engineering at National Taiwan University. My research expertise centers on deciphering microstructural mechanisms in metal processing and developing mesoscale simulation techniques, with a particular focus on two key areas: metal solidification behavior and granular material flow dynamics. I lead the Solidification Processing and Rheology Laboratory, which is dedicated to using scientific approaches to understand microstructural formation mechanisms and support the design of next-generation metal manufacturing processes that integrate high performance, processability, and sustainability.

Metal solidification lies at the heart of materials processing science, involving coupled phenomena such as nucleation, crystal growth, solute segregation, interface migration, and microscale fluid flow. These mechanisms not only determine the initial microstructure but also significantly influence subsequent forming behavior and functional performance. To investigate these critical processes, we integrate phase-field modeling, CALPHAD-based thermodynamic simulations, synchrotron X-ray tomography, and advanced microscopy to develop predictive and visualizable multiscale simulation tools.

On the other hand, regarding the flow and interaction of particulate phases within materials, we couple the Discrete Element Method (DEM) with Computational Fluid Dynamics (CFD) to simulate phenomena such as particle impact and accumulation. Our granular flow modeling framework has been applied to simulate high-temperature blast furnace tuyere zone reactions and data-driven outputs in steelmaking processes, as well as to analyze grain migration and contact mechanics during mold filling and compression in high solid fraction semi-solid aluminum alloys. Both the phase-field and DEM approaches are key mesoscale tools in computational materials science, uniquely suited to bridging micro-mechanisms and macroscopic behavior under complex processing conditions, such as transport, interfacial dynamics, and microstructural evolution.

At present, our laboratory focuses on process design and simulation for four categories of metallic materials:

1. Aluminum alloys and recycled aluminum: Addressing issues related to solidification defects and second-phase control by integrating thermodynamic modeling, rheological simulation, solidification path prediction, and heat treatment optimization to enhance the stability and application potential of aluminum materials.

2. Steel and in-furnace behavior modeling: Developing particle flow simulations and AI-driven modeling workflows to analyze flow field variations in blast furnace tuyere regions. We also investigate thermal-mechanical processing parameters and their effects on microstructure and mechanical properties, contributing to the process optimization of high-strength steels.

3. Advanced magnesium alloy processing: Exploring the relationships between alloy design, heat treatment parameters, and second-phase precipitation behavior. By combining CALPHAD simulations and experimental validation, we aim to establish efficient processing design strategies that meet stringent mechanical and physicochemical property requirements.

4. Solidification process optimization for high- and medium-entropy alloys: Utilizing phase-field modeling and phase diagram calculations to investigate segregation, primary phase stability, and homogenization strategies in high-performance HEAs/MEAs, constructing processing–microstructure relationship models as a foundation for future applications.

During my doctoral studies at Imperial College London, I conducted rheological modeling research on semi-solid aluminum alloys. Since returning to my alma mater, I have gradually advanced cross-scale simulation and microstructural characterization techniques related to solidification and phase transformation. The Solidification Processing and Rheology Laboratory will continue to focus on numerical prediction, visualization, and experimental validation of solidification and rheological phenomena in materials processing, contributing to the advancement and sustainability of metal manufacturing technologies in Taiwan.