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
Photobleaching severely limits the utility and long-term reliability of fluorescence-based measurements. To address this long-standing limitation, we synthesized a conjugate that covalently links fluorescein isothiocyanate (FITC) to ferrocene (Fc), a redox-active metallocene. Our two-step synthesis involved reduction of ferrocene methylene azide followed by formation of a stable thiourea linkage. Photophysical characterization confirmed highly efficient intramolecular quenching, evidenced by an 81.5% reduction in quantum yield (Φ) and a shortened lifetime (τ = 3.2 ns vs. 4.1 ns for FITC). The Fc-FITC conjugate exhibited an 11-fold increase in photobleaching half-life (693 vs. 63 min for FITC), retaining 94% of its initial fluorescence after 60 min of constant 23 mW/cm<sup>2</sup> irradiation, compared to only 52% for FITC. Direct singlet oxygen (<sup>1</sup>O<sub>2</sub>) quantification using Singlet Oxygen Sensor Green (SOSG) confirmed that Fc conjugation reduces the photosensitization rate to only 28% of that of native FITC. Sodium azide (NaN<sub>3</sub>) quenching assays further validated the suppression of reactive oxygen species (ROS), as the Fc-FITC system exhibited negligible quenching (4.6%) compared to the significant response of native FITC (32.5%). This stabilization arises from a Photoinduced Electron Transfer (PET) mechanism that suppresses formation of the destructive triplet state (T<sup>1</sup>). A quantitative Rehm-Weller analysis (ΔG<sub>PET</sub> ≈ - 0.76 eV) and direct ROS validation establish a robust mechanistic basis for this photoprotective effect. Together, these findings establish a unique intramolecular photostabilization strategy where signal durability and quantitative precision are prioritized over peak brightness, offering a framework for designing robust hybrid redox-fluorophore probes suited for persistent sensing and long-term quantitative analysis.
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.