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    <title>Repository Community: null</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/247</link>
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        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60619" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60613" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60441" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60376" />
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    <dc:date>2026-08-23T22:36:39Z</dc:date>
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  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60619">
    <title>Activation to Deactivation Dynamics of Cu-Embedded TiO2 for Solar CH4 Generation</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60619</link>
    <description>Title: Activation to Deactivation Dynamics of Cu-Embedded TiO2 for Solar CH4 Generation
Author(s): Ali, Shahzad; Kim, Dongyun; Khalid, Muhammad Zeeshan; Gong, Eunhee; Lee, Junho; Slabon, Adam; Yuan, Jiayin; Huttula, Marko; In, Su-Il
Abstract: Photocatalytic CO2 reduction is known to accelerate on surfaces with defects such as oxygen vacancies (Vo), undercoordinatedmetal atoms, and hydroxyl groups (OH − ). This is further boosted while these defects, Vo-coupled undercoordinated metal atoms,and proximal OH − , act synergistically. However, it is challenging to make atomic-level patterns of such structural arrangementsand monitor their activation anddeactivation pathways. Herein, we report single-atom hydroxylated-Cu in the vicinity of Ti atomthat triggers Vo generation owing to specific structural arrangements. It finally activates CO 2 by coordinative activation andeventually transforms CO2 to CH 4 through Cu–*CHO intermediate. Alongside the activation, deactivation of photocatalyst alsoproceeds, accompanied by the change in the binding environment of the Cu, generation of the oxidizing hydroxyl radicals, andphotocatalytically inactive carbonaceous species. This work outlines the efficacious role of Cu in CO2 reduction to CH 4 andprovides valuable insights into the activation and deactivation mechanisms.</description>
    <dc:date>2026-06-30T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60613">
    <title>Experimental and Machine Learning-Assisted Discovery of 2D Materials for Hydrogen Evolution: From Fundamentals to Industrial Applications</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60613</link>
    <description>Title: Experimental and Machine Learning-Assisted Discovery of 2D Materials for Hydrogen Evolution: From Fundamentals to Industrial Applications
Author(s): Gong, Eunhee; Kim, Hwapyong; Hiragond, Chaitanya B.; Lee, Jeonghyeon; Goddard III, William A.; In, Su-Il
Abstract: Water splitting to produce hydrogen is recognized as a green technology with significant potential to replace traditional non-renewable energy sources. Substantial progress has been made in the hydrogen evolution reaction (HER), with two-dimensional (2D) materials for both photocatalytic and electrocatalytic HER due to their unique structural features and favourable properties. Along with experimental materials design, the properties of the 2D materials have been complemented by computational methods such as density functional theory (DFT) over the past decade. However, these computational approaches face limitations in terms of time and cost efficiency. Consequently, data-driven approaches, particularly machine learning (ML), are emerging as powerful tools in materials science for identifying structure-activity relationships by learning from existing experimental and DFT calculation data. This review discusses the progress of 2D materials for hydrogen evolution, encompassing experimental advances, theoretical insights, and ML-assisted discovery. First, the fundamental principles of HER are examined, combining insights from photocatalysis and electrocatalysis. Next, an overview of 2D materials for HER is presented, including key challenges related to kinetics, stability, and scalability. Subsequently, ML strategies for 2D material discovery and screening are explored. Case studies on ML applications for various 2D photocatalysts and electrocatalysts, including graphene, g-C3N4, transition metal chalcogenides, MXenes, etc., are discussed. Finally, factors influencing large-scale applications and challenges associated with integrating materials science and ML approaches for HER are addressed.</description>
    <dc:date>2026-08-31T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60441">
    <title>원자력 발전소 방재 방법 및 이를 수행하는 시스템</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60441</link>
    <description>Title: 원자력 발전소 방재 방법 및 이를 수행하는 시스템
Author(s): 이준호; 인수일; 김태규; 이상훈; 이규정; 손병락
Abstract: 본 발명은 방사능을 측정할 수 있는 방사능 측정 장치를 장착한 드론을 활용하여 원자력 발전소 내부 또는 부지나, 주변부에 대한 국지적 실시간 방사능 수치 정보를 수집하고, 함께 작동하는 풍향풍속계를 통해 현장의 기상 정보를 통합하여 방사능 확산 지도와 대피로를 산출하여, 통신망을 통해 대피로를 안내하기 위한 원자력 발전소 방재 방법 및 이를 수행하는 시스템에 대한 것으로, 원전 재난시 최적의 드론 및 드론 스테이션을 구동할 수 있으며, 다양한 상황별 프로그램을 구상하여 적합한 정보를 확인 및 명령함으로써 시스템을 올바르게 작동하고자 하고, 시뮬레이션을 통해 대피로를 최적화하여 원전재난 대피 시스템을 검증하고, 나아가 빅데이터 생성 및 활용을 수행할 수 있다.</description>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60376">
    <title>베타전지용 탄소전극, 이를 포함하는 베타전지 및 이의 제조방법</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60376</link>
    <description>Title: 베타전지용 탄소전극, 이를 포함하는 베타전지 및 이의 제조방법
Author(s): 황윤주; 인수일; 김홍수; 박영호; 김대희</description>
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