손성민 교수
Sungmin Son
KAIST 바이오및뇌공학과 · 공학
연구실 소개
손성민 교수 연구실은 초소형 전자소자 및 고성능 에너지 시스템의 핵심 기술을 연구하고 있습니다. 특히 초저온 웨이퍼 볼드링, 슈퍼크리티컬 CO₂(스-CO₂) 기반 열역학 사이클, 소형 모듈러 Reactor(SMR)의 설계 및 성능 평가에 초점을 맞추고 있으며, 고도화된 재료 표면 처리와 복합 시스템의 신뢰성 분석을 통해 차세대 반도체 및 원자력 기술의 실현 가능성을 탐색하고 있습니다. 특히, 에너지 효율 향상과 환경 친화적 기술 통합을 위한 열역학적·재료적 통합 설계가 핵심 연구 방향입니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15The low-temperature wafer bonding has been studied on two types of dielectric material (SiO, SiCN) as final bonding layers. It is important for the wafer bonding technology to obtain the higher interfacial energy between two bonding wafers, and oxygen and nitrogen (O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) plasma treatments ha
Abstract Due to small footprint and high efficiency, a Supercritical CO2 (S-CO2) power cycle is considered to be one of the promising next-generation power cycles. Although S-CO2 is reported as a powerful cleaning agent, the performance of a power system operating with S-CO2 will also inevitably degrade over time. Previous researchers have shown that turbomachinery deterioration could be a major subject regarding the system performance degradation. Nevertheless, no quantitative evaluation has ye
In recent years, to overcome the challenges of nuclear power plants due to their large scale, numerous types of small modular reactors are being designed worldwide. Small modular reactors are required to have a capability to operate in environmentally challenging regions with long refueling time. Supercritical CO2 (S-CO2)-cooled direct-cycle reactor is one of the candidates that can meet these requirements. In order to evaluate if the design achieves this goal, transport of generated radionuclid
This study investigates the application of supercritical carbon dioxide (S–CO2) direct-cycle micro modular reactors (MMRs) in primary frequency control (PFC), which is a scenario characterized by significant load fluctuations that has received less attention compared to secondary load-following. Using a modified GAMMA + code and a deep neural network–based turbomachinery off-design model, the authors conducted an analysis to assess the behavior of the reactor core and fluid system under differen
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