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Course Details

For more details on the courses, please refer to the Course Catalog

교육과정
Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
EAM5707 IT Advanced Materials SeminarⅠ 3 6 Major Master/Doctor 1-4 - No
By changing manufacturing processes, heat treatment schedules of by controlling alloying elements of impurities, various communication material properties can be improved and utilized. This lecture covers the latest informations and knowledges related to the above subjects.
EAM5708 IT Advanced Materials SeminarⅡ 3 6 Major Master/Doctor 1-4 Korean Yes
Up-to-date knowledge and technology for manufacturing and processing of information advanced materilas will be discussed.
EAM5721 Surface, Interface and Other Defects 3 6 Major Master/Doctor 1-4 Korean Yes
Structure of surface and interface in solid materials, analysis of electrical, structural, and chemical properties of them, and phenomena at surface and interface will be introduced and theoretically discussed.
EAM5722 Nano Convergence Technology 3 6 Major Master/Doctor 1-4 Korean Yes
The hybrid technology requires interdisciolinary studies based on NT, IT, CT, BT, and ET. In this course, we investigate core materials for electronic device and material properties. In particular, the lecture will focus on physical and chemical properties, synthesis and process for organic and nano materials.
EAM5723 Master thesis study of advanced materials 1 3 9 Major Master/Doctor 1-4 Korean Yes
This course is "individual study" on the research topics of master degree of advanced materials science and engineering. Theoretical background, principles, experimental procedure, application, and experimental results will be studied/evaluated. Specifically, relationship between processing variable, microstructure, and resultant properties will be correlated in detail.
EAM5724 Master thesis study of advanced materials 2 3 9 Major Master/Doctor 1-4 Korean Yes
This course is "individual study" on the research topics of master degree of advanced materials science and engineering. Theoretical background, principles, experimental procedure, application, and experimental results will be studied/evaluated. Specifically, relationship between processing variable, microstructure, and resultant properties will be correlated in detail.
EAM5725 Biomaterials Science 3 6 Major Master/Doctor 1-4 English Yes
The objective of this class is to provide an overview of recent contribution of science and engineering in biological systems and medicine with emphasis on materials. In the first part of the class, physical and chemical properties of representative biomolecules, cells, and tissues will be introduced. Discussion on the role of materials in various biomedical engineering, including microarray, biosensing, drug delivery, and tissue engineering, will follow.
EAM5726 Design and Drafting in Engineering 3 6 Major Master/Doctor 1-4 - No
This class is aimed to develop material scientists to understand, analyze, and create general mechanical draftings and electrical circuits. Instruction on the basic terminologies, concepts, and fundamentals of both mechanical and electrical draftings, combined with practice will help students to obtain basic knowledge and skills on drawings in engineering.
EAM5729 Physical Metallurgy 3 6 Major Master/Doctor - No
Physical metallurgy is concerned with the physical and mechanical characteristics of metals and alloys. This field studies the properties of metals and alloys as affected by manufacturing, mechanical and heat treatment.
EAM5730 Academic Writing and Research Ethics in Materials Science 3 6 Major Master/Doctor 1-4 - No
This academic writing and research ethics course is designed to teach how to successfully write an academic writing and present the principles and directions of research ethics.
EAM5731 Experimental and Research Methodology in Materials Science 3 6 Major Master/Doctor 1-4 - No
The course aims to introduce the basics of experimental and research methodology related to Advanced Materials Science and Engineering.In this class methodologies related to diverse experiments and research carried out in Materials Science will be instructed.
EAM5732 Special Topics on Advanced Materials and Components 3 6 Major Master/Doctor 1-4 - No
This lecture is an industry-academia collaborative class aimed to strengthen the competitiveness of Materials and Components in Engineering. This lecture is composed of the teaching part and practical training part. The teaching part will be provided during the semester and practical training part will be carried out during the vacation.
EAM5733 Research Trends in Materials Science 3 6 Major Master/Doctor 1-4 Korean Yes
This course is an e-lecture, aimed to introduce the latest research papers of the faculty members in the School of Advanced Materials Science and Engineering. It is a flipped class-based lecture, where students first listen to the recorded lectures before class and discuss related contents with the lecturer during the class.
EAM5734 Electronic Materials for Wearable Electronics 3 6 Major Master/Doctor - No
In this course, the fundamental electrical properties of materials for wearable electronics will be covered. Also we will discuss about the additional feature in wearable electronic materials, such as mechanical, chemical, optical properties. Especially, the lecture start from discussion about basic electronic structure in various materials and extend into synthesis/fabrication of organic and inorganic materials. Finally we will study about the recent trends in wearable electronic materials.
EAM5735 Artificial Intelligence in Materials and Science Engineering 3 6 Major Master/Doctor Korean Yes
In this course, the fundamental theories and methodologies on artificial intelligence (AI) technology, which can be specifically applied to materials science and engineering, are covered. In particular, various AI algorithms such as machine learning and deep learning are covered, and big data analytics including mass data collection, signal processing, and statistical approach is also studied. Finally, case studies for experimental data are given by using above-mentioned AI algorithms and big-data analytics.