For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ESC5122 | Energy Optics | 3 | 6 | Major | Master/Doctor | 1-8 | Energy Science | - | No |
| This course lectures about modern optics for application in energy industry and science. This course covers basic physics (propagation, diffraction, interference, and interaction with materials) and applications (hologram, spectrum, and laser) of optics. | |||||||||
| IFT5002 | Intelligence semiconductor fabrication process | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course deals with the basic processes of semiconductor device manufacturing and discuss about technologies for intelligence. Students will learn the theory of processes and equipment for CMP, wet and dry etching, oxidation, ion implantation, and thin film manufacturing for devices. | |||||||||
| IFT5003 | Advanced intelligence Materials Process Engineering | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course introduces various fabrication and working processes for the intelligence materials/parts made of mainly metals, ceramics, and polymers. Efforts will be devoted to understand the relations between the processes, microstructures, and resultant properties of materials. Consequently, designing the process method for intelligence materials/parts with desired properties will be introduced. | |||||||||
| IFT5004 | Carbon Nanomaterials | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course introduces fundamental understanding of the physical/chemical structures and properties of carbon nanomaterials such as carbon nanotubes, graphene, and carbon nanofibers. In addition, the course deals with the state-of-the-art composite materials and devices using the carbon nanomaterials. | |||||||||
| IFT5006 | Introduction to material for processing equipment | 3 | 6 | Major | Master/Doctor | - | No | ||
| Introduction to Materials for process equipment -The course will teach some basics on the materials issues used for process equipment | |||||||||
| IFT5008 | multiphysics mechanics & computational analysis | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class introduces the theory of multiphysics mechanics (electromagnetic-thermal-material-mechanical), and practices computational anlaysis for engieering problems based on the multiphysics mechanics. Students also learn data-driven simulation using articicial inteligence (AI). | |||||||||
| IFT5009 | Plasma diagnostics | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course deals with current techniques of plasma disgnostics for the investigation of plasmas produced at low and high pressures. They include langmuir probe, optical emission spectroscopy, and absorption spectroscopy. The course explains how these techniques work and teaches theoretical backgrounds such as discrete energy states of atoms and molecules and their population distribution for the techniques. | |||||||||
| IFT5012 | Applied heat transfer with machine learning method | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course introduces heat transfer analysis technique on a surface of a semiconductor wafer and explains real-time and precise measurement of temperature distribution. Students study application of machine learning technique to use required variables for heat transfer analysis of semiconductor manufacturing equipment. | |||||||||
| IFT5013 | Intelligent Nano-Transistor Device and Circuit Design | 3 | 6 | Major | Master/Doctor | - | No | ||
| The areas in which integrated circuits are used are diversified, and the power generation rate is also increasing due to scaling of transistors. Devices with different channel lengths and structures are used depending on the purpose for which the designed circuit will be used. In this course, students learn how to optimize each device by understanding the operation principle of various devices and applying intelligent algorithms. | |||||||||
| IFT5014 | Design of Low Power Sensor Node Design Technology | 3 | 6 | Major | Master/Doctor | - | No | ||
| In this course, students learn hardware knowledge of sensor, its related circuit technology, power distribution network design, and package technology in designing sensor nodes. It will be possible to broaden the knowledge of the students of convergence by handling a wide range of knowledge in different fields. | |||||||||
| IFT5016 | Digital system control engineering | 3 | 6 | Major | Master/Doctor | - | No | ||
| This class offers the controller design method for digital control system and state/output prediction using digital sensor. By applying the control theories coverd in analog systems, the controller design using digital sensor will be covered. For the digital sensors, many current industrial types will be studied. | |||||||||
| IFT5017 | Semiconductor fabrication equipment technology | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course introduces the basic knowledge and emerging trends of Semiconductor equipment technology. The class is open to the member ship companies in I-Cluster. | |||||||||
| IFT5018 | Introduction to Smart Fab.Tech.I | 3 | 6 | Major | Master/Doctor | English | Yes | ||
| This course introduces basic knowledge of both mechanical and material engineerings to understand the smart Fab. technology. First, the course deals with the laws of energy conversion and the entropy and the dependance of energy, strain, and stress in materials on applied energy/force. Second, types and structures of materials, phase diagrams and transformations, and relation between microstructure and properties are studied. | |||||||||
| IFT5019 | Introduction to smart Fab. Tech.II | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This course introduces basic knowledge on the device, process, and equipments for semiconductor wafer-level processing. First, the basics of semiconductor devies such as PN diodes and MOSFET are discussed and then the unit processes are studied, followed by discussion on equipments used for the processes for the device fabrication. | |||||||||
| IFT5020 | Advanced Smart Fab. Tech. Convergence | 3 | 6 | Major | Master/Doctor | 1-3 | - | No | |
| It is very important to understand how AI and IoT sensor technology is changing the conventional Fab. technology in order to nurture talents suitable for the Fab. industry, where innovation in the manufacturing process is underway in the era of the 4th industrial revolution. To this end, in this course, we first establish an understanding of display technology, and learn about AI and IoT sensor technology applied to the display Fab technology. Based on this, the concept of the recently progressed smart display Fab. technology is established, and the next-generation display industry that this will change can be drawn. Through this course, interdisciplinary curriculum convergence and practical education are provided. | |||||||||