인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots, facilitating energy-efficient CO<sub>2</sub> management in life-support systems of confined space. Here, a micro/nano-reconfigurable robot is constructed from the CO<sub>2</sub> molecular hunters, temperature-sensitive molecular switch, solar photothermal conversion, and magnetically-driven function engines. The molecular hunters within the molecular extension state can capture 6.19 mmol g<sup>-1</sup> of CO<sub>2</sub> to form carbamic acid and ammonium bicarbonate. Interestingly, the molecular switch of the robot activates a molecular curling state that facilitates CO<sub>2</sub> release through nano-reconfiguration, which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption. Nano-reconfiguration of robot alters the amino microenvironment, including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level. This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives, thereby inhibiting the side reactions that generate hard-to-decompose urea structures, achieving the lowest regeneration temperature of 55 °C reported to date. The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating. Notably, the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%, effectively addressing the issue of carbon suffocation in confined spaces. This work significantly enhances life-support systems for deep-space exploration, while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.