半导体红外量子点发展现状与前景

发布时间：2018-03-28 01:25

本文选题：量子点　切入点：红外　出处：《应用光学》2017年05期

【摘要】：半导体量子点具有独特的光学与电学性质,特别是红外量子点良好的光稳定性和生物相容性等优点使其在光电器件、生物医学等领域受到广泛关注。综述了吸收或发射光谱位于红外波段的量子点在激光、能源、光电探测以及生物医学等方面的应用现状与前景,归纳了适用于红外量子点材料的制备方法,并对比了不同方法在应用中的优势。半导体红外量子点材料选择丰富、应用形式多样:InAs量子点被动锁模激光器在1.3μm波长处产生7.3GHz的近衍射极限脉冲输出;InAs/GaAs量子点双波长激光器可泵浦产生0.6nW的THz波;PbS量子点掺杂光纤放大器可在1.53μm中心波长处实现10.5dB光增益,带宽160nm;CdSeTe量子点敏化太阳能电池、异质结Si基量子点太阳能电池的总转换效率可达8%和14.8%;胶质HgTe量子点制成的量子点红外探测器(QDIP)可实现3μm~5μm中波红外探测,Ge/Si量子点可实现3μm~7μm红外探测;CdTe/ZnSe核壳量子点可用于检测DNA序列的损伤与突变。半导体红外量子点上述应用形式的发展,将进一步促进红外光电系统向高效、快速、大规模集成的方向演进,也将极大地促进临床医学中活体成像检测的应用推广。
[Abstract]:Semiconductor quantum dots have unique optical and electrical properties, especially the excellent optical stability and biocompatibility of infrared quantum dots. In this paper, the applications and prospects of infrared quantum dots with absorption or emission spectrum in the fields of laser, energy, photoelectric detection and biomedicine are reviewed. The preparation methods suitable for infrared quantum dot materials are summarized, and the advantages of different methods in application are compared. Using multiple forms of passive mode-locked quantum dots to generate 7.3GHz at 1.3 渭 m wavelength, InAs-GaAs quantum dot double wavelength laser can pump THz wave and PBS quantum dot-doped fiber amplifier at 1.53 渭 m center. 10.5dB optical gain is realized at the wavelength, The bandwidth is 160 nm and CdSeTe quantum dots sensitized solar cells, The total conversion efficiency of heterojunction Si-based quantum dots solar cells can reach 8% and 14.8.The quantum dot infrared detector made of colloidal HgTe quantum dots can realize 3 渭 m ~ 5 渭 m ~ (5 渭 m) medium-wave infrared detection and 3 渭 m ~ (7) 渭 m ~ (7 渭 m) infrared detection of CdTe / ZnSe core / shell quantum dots. It can be used to detect the damage and mutation of DNA sequence. It will further promote the development of infrared photovoltaic system to the direction of high efficiency, fast and large-scale integration, and will greatly promote the application of in vivo imaging detection in clinical medicine.
【作者单位】：北京信息科技大学;
【分类号】：TB383.1;TN304

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