백세인 교수
Seoin Back
고려대학교 융합에너지공학과 · 에너지
연구실 소개
백세인 교수의 연구실은 전기화학적 반응, 특히 이산화탄소와 질소의 효율적 전환을 위한 고성능 촉매 설계를 핵심으로 합니다. 밀도함수이론과 기계학습 기반의 고속 스크리닝을 활용해 촉매의 활성 및 선택성을 정량적으로 예측하고, 전자구조와 결합 에너지 간의 척도관계를 도전적으로 분석합니다. 특히 단일원자 촉매와 금속 카바이드/질라이드 등 혼합형 재료를 통해 기존의 전자구조 제약을 초월한 새로운 촉매 메커니즘을 규명하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15High Resolution Image Download MS PowerPoint Slide Highly active and selective CO 2 conversion into useful chemicals is desirable to generate valuable products out of greenhouse gases. To date, various metal-based heterogeneous catalysts have shown promising electrochemical catalytic activities for CO 2 reduction, yet there have been no systematic studies of the active sites of these metal catalysts that can guide further experiments. In this study, we use first-principles calculations to identi
OH production compared to any existing catalysts, synthesized or predicted. To understand the origin of the activity enhancement of SACs, we find that the lack of an atomic ensemble for adsorbate binding and the unique electronic structure of the single atom catalysts as well as orbital interaction play an important role, contributing to binding energies of SACs that deviate considerably from the conventional scaling relation of bulk transition metals.
High-throughput screening of catalysts can be performed using density functional theory calculations to predict catalytic properties, often correlated with adsorbate binding energies. However, more complete investigations would require an order of 2 more calculations compared to the current approach, making the computational cost a bottleneck. Recently developed machine-learning methods have been demonstrated to predict these properties from hand-crafted features but have struggled to scale to l
CO 2 electrochemical catalysis is limited by scaling relations due to a d-band theory of transition metals. As a means of breaking the scaling relation, it has recently been reported that hybridizing the d-orbitals of transition metal with p-orbitals of main group elements or using naturally hybridized materials such as metal carbides and nitrides is a promising strategy. In this Letter, by means of density functional theory calculations, we investigate the catalytic properties of TiC, TiN, and
Catalytic electroreduction of carbon dioxide to useful chemical feedstocks is an environmentally and technologically important process, yet the low energy efficiency and difficulty in controlling product selectivity are great challenges. The reason for part of the latter is that there are presently no catalyst design principles to selectively control CO 2 electroreduction toward a desired product. In this work, as a first attempt, we suggest combining a few criteria (CO binding energy, OH bindin
We theoretically investigate the electrochemical N2 reduction reaction (NRR) mechanism to produce NH3 on the Ru catalyst. All possible N-N dissociation steps during the reduction processes were evaluated along with the conventional associative and dissociative pathways. Based on the calculated free energy diagrams, it is revealed that the kinetically facile intermediate dissociative pathways during the NRR require a thermodynamic limiting potential (-0.71 V) similar to the associative pathway (-
Developing active and stable oxygen evolution catalysts is a key to enabling various future energy technologies, and the state of the art catalysts are Ir-containing oxide materials. Understanding oxygen chemistry on oxide materials is significantly more complicated than studying transition-metal catalysts for two reasons: the most stable surface coverage under reaction conditions is extremely important but difficult to understand without many detailed calculations, and there are many possible a
Abstract The electrochemical carbon dioxide reduction reaction (CO 2 RR) is an attractive approach for mitigating CO 2 emissions and generating value-added products. Consequently, discovery of promising CO 2 RR catalysts has become a crucial task, and machine learning (ML) has been utilized to accelerate catalyst discovery. However, current ML approaches are limited to exploring narrow chemical spaces and provide only fragmentary catalytic activity, even though CO 2 RR produces various chemicals
Gold is known currently as the most active single-element electrocatalyst for CO2 electroreduction reaction to CO. In this work, we combine Au with a second metal element, Cu, to reduce the amount of precious metal content by increasing the surface-to-mass ratio and to achieve comparable activity to Au-based catalysts. In particular, we demonstrate that the introduction of a Au-Cu bifunctional "interface" is more beneficial than a simple and conventional homogeneous alloying of Au and Cu in stab
Abstract Single‐atom M‒N‒C catalysts have attracted tremendous attention for their application to electrocatalysis. Nitrogen‐coordinated mononuclear metal moieties (MN x moities) are bio‐inspired active sites that are analogous to various metal‐porphyrin cofactors. Given that the functions of metal‐porphyrin cofactors are highly dependent on the local coordination environments around the mononuclear active site, engineering MN x active sites in heterogeneous M‒N‒C catalysts would provide an addi
Abstract The success of proton exchange membrane water electrolysis (PEMWE) depends on active and robust electrocatalysts to facilitate oxygen evolution reaction (OER). Heteroatom-doped-RuO x has emerged as a promising electrocatalysts because heteroatoms suppress lattice oxygen participation in the OER, thereby preventing the destabilization of surface Ru and catalyst degradation. However, identifying suitable heteroatoms and achieving their atomic-scale coupling with Ru atoms are nontrivial ta
In light of the pressing need for practical materials and molecular solutions to renewable energy and health problems, to name just two examples, one wonders how to accelerate research and development in the chemical sciences, so as to address the time it takes to bring materials from initial discovery to commercialization. Artificial intelligence (AI)-based techniques, in particular, are having a transformative and accelerating impact on many if not most, technological domains. To shed light on
Abstract Multi‐metal oxide (MMO) materials have significant potential to facilitate various demanding reactions by providing additional degrees of freedom in catalyst design. However, a fundamental understanding of the (electro)catalytic activity of MMOs is limited because of the intrinsic complexity of their multi‐element nature. Additional complexities arise when MMO catalysts have crystalline structures with two different metal site occupancies, such as the spinel structure, which makes it mo
Se-based nanoalloys as an emerging class of metal chalcogenide with tunable crystalline structure, component distribution, and electronic structure have attracted considerable interest in renewable energy conversion and utilization. In this Letter, we report a series of nanosized M-Se catalysts (M = Cu, Ni, Co) as prepared from laser ablation method and screen their electrocatalytic performance for onsite H<sub>2</sub>O<sub>2</sub> generation from selective oxygen reduction reaction (ORR) in alk
대표 연구 분야
백세인 교수의 연구를 Nubint에서 더 깊이 살펴보세요
이 연구실의 논문을 앱에서 열어 AI와 함께 읽고, 핵심을 요약하고, 내 글에 인용하세요.