Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	366014	Transport Phenomena in Materials Processing	1	2.0	2	★	CHUNG-KUANG YANG	GCEB	8	0	網路預選限15人

Course Plan：

Instructor	CHUNG-KUANG YANG　Office Hours
Email	ckyang@ntut.edu.tw
Last Updated	2026-08-05 21:39:34
Course Objective	本課程著重在材料製程中所發生的輸送現象為探討目標,並使用《Transport Phenomena in Materials Processing》做為教材，旨在建立研究生對動量、能量與質量傳輸之系統性理解。課程將從基本守恆原理出發，理解並掌握流體動力學方程式、熱傳方程與擴散模型，並深入探討其在金屬凝固、熱處理、半導體擴散及材料加工製程中的工程應用。課程特別強調問題定義、尺度分析與物理意義詮釋，培養學生由理論模型連結至實際製程現象之能力，為後續高階製程模擬、數值分析與研究論文撰寫奠定紮實基礎。 This course studies transport phenomena in materials processing, and the primary textbook for this graduate-level course was selected as “Transport Phenomena in Materials Processing”. The lecture content integrates fluid dynamics, energy transport, and mass transport in materials processing and engineering applications. Rather than treating transport phenomena as abstract mathematical formulations, the lecturer aims to emphasize the derivation of governing equations from fundamental conservation laws and highlight their physical meaning in real processing systems. Topics include laminar and turbulent flow, heat conduction and convection, radiation, diffusion in solids, solidification, and interphase mass transfer, all with strong engineering relevance. The structured development of the Navier–Stokes equations, energy equation, and diffusion models equips students with the analytical tools necessary to interpret and model coupled transport phenomena encountered in casting, heat trea
Course Schedule (Week 1-16)	**Part I: Momentum Transport (Fluid Flow)** * **Week 1: Viscous Properties of Fluids (Chapter 1)** Focus your 2 hours on introducing Newtonian and non-Newtonian fluids, laminar versus turbulent flow, and Newton's law of viscosity. * **Week 2: Laminar Flow and the Momentum Equation (Chapter 2)** Cover momentum balances and the development of the Navier-Stokes equation. Use the 2 hours to walk through classic laminar flow models: falling films, flow between parallel plates, and flow through circular tubes. * **Week 3: Turbulent and Complex Flows (Chapter 3)** Transition into empirical turbulent flow models and friction factors. Dedicate the second hour to complex materials processing flows, such as flow through porous media (Darcy's Law) and fluidized beds. * **Week 4: Energy Balance Applications in Fluid Flow (Chapter 4)** Discuss the macroscopic mechanical energy equation and Bernoulli's equation. Apply these to practical metallurgical operations, such as sudden enlargements/contractions, flow from ladles, and piping networks. * **Week 5: Flow and Vacuum Production (Chapter 5)** Introduce vacuum technology, which is crucial for materials processes like thin-film deposition and melt refinement. Cover the characteristics of pumps, fans, blowers, and molecular/Knudsen flow. **Part II: Energy Transport (Heat Transfer)** * **Week 6: Fourier's Law and Thermal Conductivity (Chapter 6)** Introduce conduction and Fourier's Law. Spend the lecture exploring how thermal conductivity behaves in gases, liquids, and multi-phase solids. * **Week 7: Heat Transfer and the Energy Equation (Chapter 7)** Develop the general energy equation. Focus on heat transfer coupled with laminar forced convection in tubes and over flat plates, as well as natural convection using the Boussinesq approximation. * **Week 8: Correlations and Data for Heat Transfer Coefficients (Chapter 8)** Teach dimensional analysis (Buckingham's pi theorem) to introduce the Nusselt, Prandtl, and Reynolds numbers. Review correlations for forced convection, natural convection, and complex quenching operations. * **Week 9: Conduction of Heat in Solids (Chapter 9)** Cover steady-state and transient heat conduction in infinite, semi-infinite, and finite solids. Spend time on moving heat sources, which are highly relevant for laser processing and welding. * **Week 10: Solidification of Metals (Chapter 10)** Apply heat transfer principles to practical processing: solidification in sand and metal molds (Chvorinov's rule). Dedicate the second hour to continuous casting and Czochralski crystal growth. * **Week 11: Radiation Heat Transfer (Chapter 11)** Lecture on black body radiation, the Stefan-Boltzmann equation, and emissivity. Cover view factors, electric circuit analogs for radiation, and radiation combined with convection in furnace enclosures. **Part III: Mass Transport** * **Week 12: Fick's Law and Diffusivity of Materials (Chapter 12)** Introduce mass transport, Fick's first and second laws, and the definition of fluxes. Explain Darken's equations and the mechanisms of diffusion in solids, liquids, and gases. * **Week 13: Diffusion in Solids (Chapter 13)** Cover steady-state and transient diffusion in solids. Focus on practical applications like the Matano interface, microelectronic diffusion (predeposition and drive-in steps), and homogenization of microsegregation. * **Week 14: Mass Transfer in Fluid Systems (Chapter 14)** Introduce the general equation of diffusion with convection. Teach the Sherwood and Schmidt numbers, and apply mass transfer coefficients to falling films and Chemical Vapor Deposition (CVD) processes. * **Week 15: Interphase Mass Transfer (Chapter 15)** Discuss the two-resistance mass transfer theory for fluids in contact. Apply this to mixed-control gas-solid reactions (like carburization and silicon oxidation) and mass transfer during vaporization. Week 16: Fi
Flexible Learning (Week 17-18)	Category ● AI 輔助學習與工具應用(AI-assisted learning and tool application) Content Students will use AI-assisted tools (e.g., ChatGPT, Microsoft Copilot, Gemini, or other discipline-specific AI platforms) to support literature review, data analysis, problem solving, and theory practice. Students will learn how to use their learning in the classroom and critically evaluate AI-generated results, verify information with reliable scientific evidences, and appropriately cite AI-assisted work in accordance with academic integrity guidelines. Hours 5 Learning Outcomes Through these activities, students will develop AI literacy, critical thinking, research skills, and the ability to apply AI responsibly in engineering and scientific practice. This training together with the classroom lectures is appropriate for graduate courses in engineering, materials science, chemical engineering, semiconductor technology, and related fields. Assessment Percentage Students’ learning achievements will be evaluated through the submission of an AI-assisted project report. Students are expected to demonstrate their ability to apply AI tools appropriately, critically evaluate AI-generated outputs, integrate reliable scientific evidence, and communicate their findings effectively. Assessment will be based on the quality of the final additional report, technical accuracy, critical thinking, and problem-solving skills.
Evaluation and grading policy	Mid term examination 50% Final Examination 50%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Transport Phenomena in Material Processing, D.R. Poirier and G.H. Geiger Published by Springer International Publishers, Switzerland, 2016
The access to curricular consultation	The material naturally divides into three major transport phenomena categories: Momentum Transport (Fluid Flow), Energy Transport (Heat Transfer), and Mass Transport, culminating in Numerical Methods.
Expanding teaching and resources	● 混成學習 (Blended Learning) 課程結合實體授課與線上學習（同步視訊／非同步活動）。 Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities). ● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	SDG1：消除貧窮（No Poverty） SDG4：優質教育（Quality Education） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG12：負責任的消費與生產（Responsible Consumption and Production）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction）
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