For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ECH5131 | Introduction of Energy Conversions | 3 | 6 | Major | Master/Doctor | 1-4 | Korean | Yes | |
| Photo-electro-chemical energy conversion is motivated by the engineering of energy conversion which is one of the core research field in chemical engineering. In this class, its fundamental background and mechanism will be introduced and the engineering of optoelectric property, photocatalytic activity, energy structure, charge conductance, and chemical reaction pathway will be provided. Especially, the fundamental of photoelectrochemical/photocatalytic/electrochemical reactions and materials for achieving the hydrogen economy and the production of clean hydrogen will be discussed. | |||||||||
| ECH5132 | Principle of CCUS technology | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| Managing carbon dioxide emissions resulting from the use of fossil fuels is a major concern for the development of sustainable energy infrastructures in the future. It is a transdisciplinary challenge involving engineering, physical and social science as well as policy and legal issues. Carbon capture and storage has been widely recognized as an important set of technologies for managing carbon. This class will introduce major new technologies to capture carbon dioxide, from other emissions occurring in industrial processes, and ultimately the capture of carbon dioxide from ambient air, to deal with emissions that have no other solution. In addition to basic science and engineering challenges of each technology, the full spectrum of economic, environmental, regulatory, and political/policy aspects, and their implication for regional and global carbon management strategies of the future will be discussed. | |||||||||
| ECH5133 | Fundamentals for Bioelectronics | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course is a convergence course that deals with the basic concepts and recent trends of biosignal and its interface related to bio-electronic devices as well as basic characteristics of biosensors and electronic devices, and bio-electronic devices using them. It also deals with the basic principles of the recently developed smart medical devices, electronic drugs, and electronic devices for therapeutic diagnostics along with the fundamentals of bio and semiconductor devices. Bio-signal bio-interface learns about the types of bio-signals used for disease diagnosis, and acquires convergence knowledge from semiconductor technology to bio-technology by learning the principles, design, and bio-materials of electronic devices that can acquire related signals. | |||||||||
| ECH5134 | Advanced Computational Materials Engineering | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| Research & development using first principles-based computer simulation and big data-based machine learning methodologies is actively underway in various research fields. The use of computational simulation explains the thermodynamic, kinetic, and electrochemical behavior of material properties and chemical reactions by understanding experimental phenomena at the electronic/atomic level. Based on the knowledge of the computational materials engineering in the undergraduate course, students will learn how to apply computer simulation tools to several research topics. To this end, we enable simplification of very complex real systems into simple model systems and computer simulation using first-principle-based software. In addition, students will learn big data-based machine learning methodology that can predict material properties by developing machine learning models using various open databases. To this end, students will learn machine learning theory and directly develop machine learning models to predict various material properties using machine learning programs such as RDKit, Anaconda, and ChemProp. The target audience includes graduate students at the master's and doctoral level, and can be opened to CL for students from other related majors if necessary. | |||||||||
| ECH6001 | Research on Doctoral Thesis 1 | 3 | 6 | Major | Doctor | Korean | Yes | ||
| The course is related with the individual researches of Doctoral degree candidates by carrying out the reference searching, experimental data treatments and preparation of Master thesis in English and Assessment are sumiited and presented to main professor at the end of term. | |||||||||
| ECH6002 | Research on Doctoral Thesis 2 | 3 | 6 | Major | Doctor | Korean | Yes | ||
| The course is related with the individual researches of Doctoral degree candidates by carrying out the reference searching, experimental data treatments and preparation of Master thesis in English and Assessment are sumiited and presented to main professor at the end of term. | |||||||||
| ECH7001 | Optimization of Chemical and Biological Processes | 3 | 6 | Major | Bachelor/Master/Doctor | English | Yes | ||
| This class will teach about technology development and commercialization in the biotechnology field and how to commercialize new medicines and technologies. Students will learn about cutting-edge biotechnology applications and different stages of the technology development and commercialization process, including scientific and business aspects. Case study examples will be included as part of lectures and students will also learn about basic analysis tools to evaluate the commercialization potential of scientific businesses. | |||||||||
| ECH7001 | Optimization of Chemical and Biological Processes | 3 | 6 | Major | Bachelor/Master/Doctor | Chemical Engineering | English | Yes | |
| This class will teach about technology development and commercialization in the biotechnology field and how to commercialize new medicines and technologies. Students will learn about cutting-edge biotechnology applications and different stages of the technology development and commercialization process, including scientific and business aspects. Case study examples will be included as part of lectures and students will also learn about basic analysis tools to evaluate the commercialization potential of scientific businesses. | |||||||||
| ECH7002 | Instrumental Surface Analysis | 3 | 6 | Major | Bachelor/Master/Doctor | Korean | Yes | ||
| The basic principles and the practical application of the analytical chemistry will be introduced. The instrumental analysis of the inorganic surfaces using electron microscope, XPS, AES, RBS, etc. will be lectured. Micro- and nano-structures of the materials will be investigated, and the classification of the surface analysis will be also addressed. | |||||||||
| ECH7002 | Instrumental Surface Analysis | 3 | 6 | Major | Bachelor/Master/Doctor | Chemical Engineering | Korean | Yes | |
| The basic principles and the practical application of the analytical chemistry will be introduced. The instrumental analysis of the inorganic surfaces using electron microscope, XPS, AES, RBS, etc. will be lectured. Micro- and nano-structures of the materials will be investigated, and the classification of the surface analysis will be also addressed. | |||||||||
| ECH7003 | Polymer Rheology | 3 | 6 | Major | Bachelor/Master/Doctor | - | No | ||
| Flow and deformation characteristics of polymer melt, solution, and solid polymer materials are studied. Rheological difference between Newtonian and non-Newtonian fluid, elementary constituve equations of the Generalized Newtonian and the general viscoelastic fluids are introduced. Fluid dynamics problems are solved using them. | |||||||||
| ECH7003 | Polymer Rheology | 3 | 6 | Major | Bachelor/Master/Doctor | Chemical Engineering | - | No | |
| Flow and deformation characteristics of polymer melt, solution, and solid polymer materials are studied. Rheological difference between Newtonian and non-Newtonian fluid, elementary constituve equations of the Generalized Newtonian and the general viscoelastic fluids are introduced. Fluid dynamics problems are solved using them. | |||||||||
| ECH7005 | Machine learning for Chemical Engineering | 3 | 6 | Major | Bachelor/Master/Doctor | - | No | ||
| In this course, students are expected to learn basic theories and algorithms for machine learning including deep learning, auto-encoder, KPCA, random forest, and so on targeting for the wide range of chemical engineering subjects. Students are expected to learn how to apply the machine learning algorithms to study and solve various problems of chemical engineering practice. | |||||||||
| ECH7005 | Machine learning for Chemical Engineering | 3 | 6 | Major | Bachelor/Master/Doctor | Chemical Engineering | - | No | |
| In this course, students are expected to learn basic theories and algorithms for machine learning including deep learning, auto-encoder, KPCA, random forest, and so on targeting for the wide range of chemical engineering subjects. Students are expected to learn how to apply the machine learning algorithms to study and solve various problems of chemical engineering practice. | |||||||||
| ECH7006 | Biotechnology Research Trends and Applications | 3 | 6 | Major | Bachelor/Master/Doctor | Korean | Yes | ||
| This course will teach about research and commercialization trends in the biotechnology sector. Cutting-edge applications from the healthcare, biosensing, sustainability, and energy fields will be covered to illustrate how biotechnology research is critical to future innovation. Industry case studies and recent research publication examples will be included as part of lectures and assignments. There will also be occasional guest lectures by international experts from the academic, government, and private industry sectors. Students will also learn how to read scientific research publications and to conduct basic analysis about the commercialization potential of scientific businesses. | |||||||||