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Energy

Materials

- SOFC, PEMFC

- Li-ion Battery

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Recent News 

- 석사과정 유효민 학생 삼성 SDI 입사를 축하합니다.

- CDCE연구실 국방과 연구소 과제에 선정되었습니다.

- CO2 응용 촉매개발 (GS칼텍스), 전고체전지 용매개발 (SK On)
  고체산화물 연료전지 & 태양전지 소재개발 (국가과제
  에 관심있는 대학원생 및 박사후연
구원을 모집합니다. (1명)

- 윤영준 2023 BK21 G3 Program 대상 수상

- 유효민 & 황성연 2023 BK21 연구제안경진대회 최우수상 수상

- 김경학 교수, 2023 한국과학기술단체총연합회 & WISET 미래세대 위원 위촉

Computational Material Design

Over the past few decades, density functional theory (DFT) calculations have been widely used to find and develop materials for various purposes such as low price, high activity, and durability on diverse reaction conditions. Understanding the nature at atomic level makes possible to provide fundamental information from the bottom-up approaches for designing new types of materials.

Until now, many experimental approaches have used to “trial and error” method to identify and develop new materials. Owing to the high cost for experiments and the limitation of instrument, experimental approaches have experienced difficulties in massive material screening.

Recently, the time and cost for massive material screening with high accuracy have been sharply decreased due to the advances in performance of computer in accordance with Moore’s law. Therefore, there has been a great demand to “shorten the time for discovery and development of specialized materials in various research and industry fields” by using computational approaches.

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