Heterogeneous catalysts design using first-principles and machine-learning methods제1원리 및 기계학습 방법론을 이용한 불균일 촉매 설계

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Recently, as interest in eco-friendly and sustainable energy increases, the need for research on energy conversion catalysts is emerging. Heterogeneous catalysts are economically and environmentally desirable for industrial applications due to their high recycling rates. However, they show low efficiency and typically use expensive noble metals. Therefore, it is necessary to develop an economic and highly efficient heterogeneous catalyst. To develop a catalyst with desired properties, it is necessary to understand the mechanism and identify the factors that determine the activity. In this dissertation, we understand the reaction mechanism of catalyst, activity, and selectivity determining factor using the first principle calculations. And based on this, we discover stable and high-efficiency catalysts using data-based machine learning methods.
Advisors
Jung, Yousungresearcher정유성researcher
Description
한국과학기술원 :생명화학공학과,
Publisher
한국과학기술원
Issue Date
2022
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 생명화학공학과, 2022.8,[vii, 91 p. :]

Keywords

Heterogeneous Catalysts▼aFirst Principle Calculation▼aMachine Learning▼athroughput Screening; 불균일 촉매▼a제일원리계산▼a기계학습▼a대규모스크리닝

URI
http://hdl.handle.net/10203/308533
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1007818&flag=dissertation
Appears in Collection
CBE-Theses_Ph.D.(박사논문)
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