闪烁体
发光
闪烁
光致发光
控制重构
量子产额
光电子学
材料科学
卤化物
光子
晶体结构
限制
激子
荧光粉
格子(音乐)
Crystal(编程语言)
光学
光发射
产量(工程)
物理
纳米技术
化学
辐射传输
单晶
晶系
激活剂(遗传学)
结晶学
自发辐射
作者
Lulu Li,Tiao Feng,Yi'ni An,Lichan Mai,Ran Jia,Zhimei Sun,Zi'an Zhou,Shuyun Zhou,Chenghua Sun,Jinxiao Zheng
摘要
ABSTRACT Developing intelligent x‐ray scintillators requires precise regulation of scintillation emission. However, the complex structural factors governing luminescence in organic–inorganic hybrid metal halides (OIMHs, A m BX n ) remain elusive, limiting their rational design. Here, guided by condensed‐matter structural chemistry, we develop an environment‐regulated crystal‐structure reconfiguration strategy that directs the same precursor system to generate three structurally distinct zero‐dimensional (0D) scintillators: (C 9 H 13 N 2 O) 4 In 2 Cl 10 :Sb 3+ (Crystal 1, dimeric), (C 9 H 13 N 2 O) 2 (H 5 O 2 )InCl 6 :Sb 3+ (Crystal 2, octahedral), and (C 9 H 13 N 2 O) 4 (InCl 6 )[InCl 4 (H 2 O) 2 ]:Sb 3+ (Crystal 3, mixed‐ligand octahedral). Mechanistic studies reveal that [BX n ] configurations determine lattice distortion and electron–phonon coupling, A–[BX n ] interactions regulate lattice rigidity, and X‐site coordination environments further modulate excited‐state redistribution and radiative relaxation, establishing clear structure–scintillation relationships. The three crystals exhibit tunable green‐to‐red self‐trapped exciton (STE) emission and complementary x‐ray scintillation properties, with Crystal 2 achieving a photoluminescence quantum yield of 95.2% and an x‐ray light yield of 27 522 photons MeV −1 , while highly transparent Crystal 1 enables a spatial resolution of 24 lp mm −1 at a thickness of 0.85 mm. Furthermore, reversible stimulus‐responsive luminescence switching among these scintillators enables environmental sensing and programmable x‐ray imaging. This work provides a structural chemistry strategy for understanding STE emission in 0D OIMHs and designing reconfigurable scintillators toward intelligent x‐ray imaging.
科研通智能强力驱动
Strongly Powered by AbleSci AI