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钙钛矿量子点优异的光学特性使其成为太阳能电池、发光二极管、激光器、探测器等常规光电器件以及单光子源、纠缠光子源等非经典量子光源的理想材料. 对于单个钙钛矿量子点荧光闪烁特性的研究可以为微纳光电器件的制备提供技术支撑. 针对如何有效分析钙钛矿单量子点的荧光闪烁机制这一关键问题, 本文基于荧光轨迹进行亮、暗态的幂律分析发现: 弱光激发下钙钛矿单量子点荧光的亮、暗态概率密度服从幂律统计, 量子点的荧光闪烁是表面俘获态的活化和非活化造成的; 强光激发下, 单量子点荧光的亮态概率密度服从指数截断的幂律统计, 量子点的荧光闪烁是量子点充、放电和表面俘获共同作用的结果.Owing to their excellent optical properties, perovskite quantum dots become ideal materials for conventional optoelectronic devices such as solar cells, light-emitting diodes, lasers, detectors, and non-classical quantum light sources such as single photon sources and entangled photon sources. The research on the photoluminescence blinking dynamics of single perovskite quantum dots can provide technical support for the preparation of nano-optoelectronic devices. In recent years, some achievements have been made based on the photoluminescence lifetime and photoluminescence intensity of single perovskite quantum dots. In this paper, the bright (on) state probability density and the dark (off) state probability density are extracted from photoluminescence intensity trajectories of single quantum dots and fitted by the (truncated) power-law function. It is found that the on-state probability density of single perovskite quantum dot under weak excitation condition can be fitted by a power-law function, which indicate that the photoluminescence blinking originates from the activation and deactivation of surface trap states. Under strong excitation condition, the on-state probability density of single perovskite quantum dot obeys exponential truncated power-law statistics, which indicate that the photoluminescence blinking is affected not only by the surface trap state, but also by the charging and discharging process.
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Keywords:
- perovskite /
- single quantum dot /
- photoluminescence blinking /
- power law distribution
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图 1 (a) CsPbBr3钙钛矿量子点的吸收光谱(蓝色曲线)、发射光谱(绿色曲线)和透射电镜成像(内置图); (b) X射线衍射谱; (c)单量子点光谱测量系统; (d)玻片上CsPbBr3钙钛矿量子点的共聚焦扫描成像, 十字叉丝位置为单个的量子点
Fig. 1. (a) Absorption spectroscopy (blue trace), emission spectroscopy (green trace) and TEM imaging (inset) of CsPbBr3 perovskite quantum dots; (b) X-ray diffraction spectrum; (c) single quantum dot spectrum measurement system; (d) confocal scanning photoluminescence image of CsPbBr3 perovskite quantum dots on glass substrate. The position of the cross wire is a single quantum dot.
图 2 (a)左侧为不同激发功率下单个CsPbBr3钙钛矿量子点的荧光强度随时间变化轨迹图, 右侧为相应的荧光强度分布图; (b)图(a)中各方框区域内荧光相应的衰减曲线(颜色一一对应)及相应的单指数拟合曲线(绿色), 灰色曲线为仪器响应函数; (c)绿色曲线为相应的二阶关联函数, 粉色曲线为门控二阶关联函数
Fig. 2. (a) Typical photoluminescence intensity time trajectories and corresponding intensity distributions of a single CsPbBr3 QD under different excitation powers; (b) photoluminescence decay curves obtained from the corresponding square in Figure (a); the green and gray curves are single exponential fitted curves and instrument response function, respectively; (c) corresponding second-order correlation function curves (green) and time-gated second-order correlation function curves (pink).
图 3 (a)−(c)不同功率激发下单个CsPbBr3钙钛矿量子点的亮、暗态概率密度分布及相应的拟合曲线. On-state代表亮态, Off-state代表暗态; (d)不同功率激发下亮态到暗态以及暗态到亮态的转换速率
Fig. 3. (a)−(c) The probability density distributions and fitted curves of the bright (on) and dark (off) states of a single CsPbBr3 perovskite quantum dot under different power excitations; (d) conversion rate from bright state to dark state and dark state to bright state under different power excitations.
图 4 CsPbBr3钙钛矿单量子点的荧光闪烁原理图. 蓝色能级为导带, 橙色能级为价带, 实心和空心圆分别代表电子和空穴
Fig. 4. Photoluminescence blinking mechanisms of single CsPbBr3 perovskite quantum dots. The blue and orange levels are conduction band and valence band, respectively. The solid and hollos circles represent electrons and holes, respectively.
表 1 不同功率激发下单个CsPbBr3钙钛矿量子点的亮、暗态概率密度分布的拟合参数
Table 1. Fitted parameters for the probability density distributions of the bright and dark states of a single CsPbBr3 perovskite quantum dot under different power excitations.
激发光强度
(每脉冲平均吸收光子数)亮态 暗态 αon τon/s αoff τoff/s 弱光激发($ \langle N\rangle = 0.02 $) 1.22 — 1.45 — 中等强度光激发($ \langle N\rangle = 0.2 $) 1.09 0.46 1.48 0.76 强光激发($ \langle N\rangle = 2 $) 0.81 0.04 1.42 0.92 -
[1] Becker M A, Vaxenburg R, Nedelcu G, et al. 2018 Nature 553 189Google Scholar
[2] Akkerman Q A, Raino G, Kovalenko M V, Manna L 2018 Nat. Mater. 17 394Google Scholar
[3] Dai G, Wang L, Cheng S, Chen Y, Liu X, Deng L, Zhong H 2020 ACS Photonics 7 2390Google Scholar
[4] Utzat H, Sun W, Kaplan A E K, et al. 2019 Science 363 1068Google Scholar
[5] Senellart P, Solomon G, White A 2017 Nat. Nanotechnol. 12 1026Google Scholar
[6] Yin C Y, Chen L Y, Song N, Lv Y, Hu F R, Sun C, Yu W W, Zhang C F, Wang X Y, Zhang Y, Xiao M 2017 Phys. Rev. Lett. 119 026401Google Scholar
[7] Zhou J, Chizhik A I, Chu S, Jin D 2020 Nature 579 41Google Scholar
[8] Nirmal M, Dabbousi B O, Bawendi M G, Macklin J J, Trautman J K, Harris T D, Brus L E 1996 Nature 383 802Google Scholar
[9] Qin H Y, Meng R Y, Wang N, Peng X G 2017 Adv. Mater. 29 160692316Google Scholar
[10] Rust M J, Bates M, Zhuang X 2006 Nat. Methods 3 793Google Scholar
[11] Han X, Zhang G, Li B, Yang C, Guo W, Bai X, Huang P, Chen R, Qin C, Hu J, Ma Y, Zhong H, Xiao L, Jia S 2020 Small 16 2005435Google Scholar
[12] Chouhan L, Ito S, Thomas E M, Takano Y, Ghimire S, Miyasaka H, Biju V 2021 ACS Nano 15 2831Google Scholar
[13] Yuan G, Ritchie C, Ritter M, Murphy S, Gómez D E, Mulvaney P 2018 J. Phys. Chem. C 122 13407Google Scholar
[14] Trinh C T, Minh D N, Nguyen V L, Ahn K J, Kang Y, Lee K G 2020 APL Mater. 8 031102Google Scholar
[15] Li B, Huang H, Zhang G, Yang C, Guo W, Chen R, Qin C, Gao Y, Biju V P, Rogach A L, Xiao L, Jia S 2018 J. Phys. Chem. Lett. 9 6934Google Scholar
[16] Li B, Chen R, Qin C, Yang C, Guo W, Han X, Gao Y, Zhang G, Xiao L, Jia S 2019 Appl. Phys. Express 12 112003Google Scholar
[17] Cordones A A, Leone S R 2013 Chem. Soc. Rev. 42 3209Google Scholar
[18] Efros A L, Rosen M 1997 Phys. Rev. Lett. 78 1110Google Scholar
[19] Li B, Zhang G, Wang Z, Li Z, Chen R, Qin C, Gao Y, Xiao L, Jia S 2016 Sci. Rep. 6 32662Google Scholar
[20] Li B, Zhang G, Yang C, Li Z, Chen R, Qin C, Gao Y, Huang H, Xiao L, Jia S 2018 Opt. Express 26 4674Google Scholar
[21] Li B, Zhang G, Zhang Y, Yang C, Guo W, Peng Y, Chen R, Qin C, Gao Y, Hu J, Wu R, Ma J, Zhong H, Zheng Y, Xiao L, Jia S 2020 J. Phys. Chem. Lett. 11 10425Google Scholar
[22] Huang H, Bodnarchuk M I, Kershaw S V, Kovalenko M V, Rogach A L 2017 ACS Energy Lett. 2 2071Google Scholar
[23] Hu F R, Lv B H, Yin C Y, Zhang C F, Wang X Y, Lounis B, Xiao M 2016 Phys. Rev. Lett. 116 106404Google Scholar
[24] Yuan G, Gómez D E, Kirkwood N, Boldt K, Mulvaney P 2018 ACS Nano 12 3397Google Scholar
[25] Dong S L, Huang T, Liu Y, Wang J, Zhang G F, Xiao L T, Jia S T 2007 Phys. Rev. A 76 063820Google Scholar
[26] Hiroshige N, Ihara T, Kanemitsu Y 2017 Phys. Rev. B 95 245307Google Scholar
[27] Feng S W, Cheng C Y, Wei C Y, Yang J H, Chen Y R, Chuang Y W, Fan Y H, Chuu C S 2017 Phys. Rev. Lett. 119 143601Google Scholar
[28] 李斌, 张国峰, 景明勇, 陈瑞云, 秦成兵, 高岩, 肖连团, 贾锁堂 2016 物理学报 65 218201Google Scholar
Li B, Zhang G F, Jing M Y, Chen R Y, Qin C B, Gao Y, Xiao L T, Jia S T 2016 Acta Phys. Sin. 65 218201Google Scholar
[29] 王早, 张国峰, 李斌, 陈瑞云, 秦成兵, 肖连团, 贾锁堂 2016 物理学报 64 247803Google Scholar
Wang Z, Zhang G F, Li B, Chen R Y, Qin C B, Xiao L T, Jia S T 2016 Acta Phys. Sin. 64 247803Google Scholar
[30] Jin S, Song N, Lian T 2010 ACS Nano 4 1545Google Scholar
[31] Galland C, Ghosh Y, Steinbrück A, Sykora M, Hollingsworth J A, Klimov V I, Htoon H 2011 Nature 479 203Google Scholar
[32] Meng R Y, Qin H Y, Niu Y, Fang W, Yang S, Lin X, Cao H J, Ma J L, Ling W Z, Tong L M, Peng X G 2016 J. Phys. Chem. Lett. 7 5176Google Scholar
[33] Frantsuzov P A, Volkan-Kacso S, Janko B 2009 Phys. Rev. Lett. 103 207402Google Scholar
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