국립부경대학교 | 나노융합반도체공학부 나노융합공학전공

교수진 소개

교수사진

서민호조교수

  • 주소 : 인공지능 그린에너지 소재 연구실 (AI & Green energy Material lab.) 대연캠퍼스 공학1관 (E13) 1308호
  • 이메일 : 메일
  • 전화번호 : 051-629-6393
  • 홈페이지 : https://icms.pknu.ac.kr/agem

● Gwangju Institute of Science and Technology, Ph.D. Materials Science and Engineering, Gwangju, South Korea,

   2007/09 ~ 2012/02, (Advisor: Prof. Won Bae Kim)

 

● Gwangju Institute of Science and Technology, M.S. Materials Science and Engineering, Gwangju, South Korea, 

   2005/09 ~ 2007/08, 

● Sungkyunkwan University, B.S, Advanced Materials Science and Engineering, Seoul, South Korea, 

   1998.03.02~2005.08.25

 

 

● Assistant Professor, Department of Nanotechnology Engineering,

    Pukyong National University, 2022/03 ~ present

 

● Principal Researcher, Korea Institute of Energy Research (KIER), 2020/02 ~ 2022/02

 

● Senior Researcher, Korea Institute of Energy Research (KIER), 2016/03 ~ 2020/02

 

● Postdoctoral fellow, Department of Chemical Engineering, University of Waterloo

   (Advisor: Prof. Zhongwei Chen), 2013/08 ~ 2016/01

 

● Postdoctoral fellow, Department of Energy Systems Engineering, Daegu Gyeongbuk Institute of Science and Technology 

   (Advisor: Prof. Byungchan Han), 2012/02 ~ 2013/5

● The development of advanced precious/non-precious hydrogen/oxygen catalysts in polymer electrolyte fuel cells, anion exchange      membrane water electrolysis and metal-air battery.

 

  - Precious and non-precious catalyst development in various electrochemical energy conversion systems
  - Activity and durability prediction and validation for electrocatalyst on various supports

 

● Microstructure optimization in Fuel Cell/Water electrolysis electrodes using materials design.


  - Developing fuel cell MEA fabrication by controlling nanostructure in PEM fuel cell and AEM water electrolysis.
  - Ionomer control technology in the electrode for minimizing mass transfer resistance in microstructure. Development of ionomer free        catalyst layer in Fuel Cell/Water electrolysis.

 

● Artificial intelligent (AI) multiscale modeling for electrochemical energy conversion system.


  - Machine learning Force Field development for multiscale modeling
  - Ab-initio computational design of energy systems with an experiment
  - Comprehending the mechanism of the interface between catalyst layer and electrolyte.

전기화학

연료전지공학

연료전지공학및실습

열전달

인공지능 그린에너지 소재 연구실 (AI & Green energy Material lab.)

대연캠퍼스 공학1(E13) 1308