Jing Lyu 1,2Xinyu Zhang 1Lei Cai 3Li Tao 1,4[ ... ]Ruibin Liu 1,*
Author Affiliations
Abstract
1 Beijing Key Laboratory of Nano-photonics and Ultrafine Optoelectronic Systems, School of Physics, Beijing Institute of Technologyhttps://ror.org/01skt4w74, Beijing 100081, China
2 Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314000, China
3 Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University, Suzhou 215123, China
4 e-mail: litao@bit.edu.cn
The random lasing in quantum dot systems is in anticipation for widespread applications in biomedical therapy and image recognition, especially in random laser devices with high brightness and high monochromaticity. Herein, low-threshold, narrowband emission, and stable random lasing is realized in carbon quantum dot (CQD)/DCM nanowire composite-doped TiN nanoparticles, which are fabricated by the mixture of carbon quantum dots and self-assembly DCM dye molecules. The Förster resonance energy transfer process results in a high luminescence efficiency for the composite of carbon dots and DCM nanowires, allowing significant random lasing actions to emerge in CQD/DCM composite as TiN particles are doped that greatly enhance the emission efficiency through the plasmon resonance and random scattering. Thus, sharp and low-threshold random lasing is finally realized and even strong single-mode lasing occurs under higher pumping energy in the TiN-doped CQD/DCM composite. This work provides a promising way in high monochromaticity random laser applications.
Photonics Research
2022, 10(9): 2239
作者单位
摘要
1 北京理工大学物理学院, 北京 100081
2 宝瑞激光科技(常州)有限公司, 江苏 常州 213000
采用激光诱导击穿光谱(LIBS)技术对复合肥样品中氮(N)、磷(P)和钾(K)等营养元素进行定量分析。实验中一共选取20个样品,由于样品量较少,为了提高预测精度,采取一种新的数据提取方式来建立训练集和预测集。利用PLS结合主成分分析(PCA)为训练集的光谱数据建立定标模型,定标过程中选取12个主成分。N、P、K三种元素定标模型的决定系数分别为0.99、0.98、0.99;20个样品中 N、P、K元素含量(质量分数,下同)预测的平均相对误差分别为2.33%、0.70%、3.00%。之后对定标模型的鲁棒性进行检验,其中N、P的平均相对误差大多维持在12%以下。采用基于统计学原理的数据抽取方式扩充样本光谱数据后,与未扩充时相比,被测元素含量的平均相对误差降幅均在10%以上。实验结果表明,当样本数量较少时,利用所提的数据提取方法结合PLS定量分析可以提高检测的准确度,实现复合肥样品中N、P、K等营养元素的快速检测。
光谱学 激光诱导击穿光谱 复合肥 偏最小二乘法 小样本量 
中国激光
2021, 48(23): 2311003
作者单位
摘要
1 北京理工大学物理学院, 北京 100081
2 宝瑞激光科技(常州)有限公司, 江苏 常州 213000
基于激光诱导击穿光谱(LIBS)对铁矿石、锰矿石和铬矿石中的Fe元素进行定量分析。由于矿石成分复杂,采取一系列的光谱预处理来降低由激光能量波动及样品不稳定烧蚀所造成的光谱波动。本文将分类和定量分析方法结合,首先通过支持向量机对光谱进行分类以避免不同类矿石间的基体效应。然后通过相关性变量筛选偏最小二乘回归分析(R-PLS)改进算法进行分析,发现三类矿石的预测集方均根误差分别降至0.975%、0.418%、0.123%,平均相对误差分别降至1.46%、6.72%和1.09%。实验结果表明,矿石分类后再进行相关性变量筛选偏最小二乘回归分析的方法可以有效提升预测准确度,为矿石成分在线检测的应用提供了可靠依据。
光谱学 激光诱导击穿光谱 矿石 定量分析 偏最小二乘回归 主成分分析 支持向量机 
中国激光
2021, 48(16): 1611002
Author Affiliations
Abstract
1 Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems, School of Physics, Beijing Institute of Technology, Beijing 100081, China
2 Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
3 AICFVE of Beijing Film Academy, Beijing 100088, China
4 e-mail: liusir@bit.edu.cn
Lead halide perovskites have drawn extensive attention over recent decades owing to their outstanding photoelectric performances. However, their toxicity and instability are big issues that need to be solved for further commercialization. Herein, we adopt a facile dry ball milling method to synthesize lead-free Cs3Cu2X5 (X=I, Cl) perovskites with photoluminescence (PL) quantum yield up to 60%. The optical features including broad emission spectrum, large Stokes shift, and long PL lifetime can be attributed to self-trapped exciton recombination. The as-synthesized blue emissive Cs3Cu2I5 and green emissive Cs3Cu2Cl5 lead-free perovskite powders have good thermal stability and photostability. Furthermore, UV-pumped phosphor-converted light-emitting diodes were obtained by using Cs3Cu2I5 and Cs3Cu2Cl5 as phosphors.
Photonics Research
2020, 8(6): 06000768
作者单位
摘要
1 北京理工大学物理学院, 北京 100081
2 宝瑞激光科技(常州)有限公司, 江苏 常州 213000
在提取激光诱导击穿光谱(LIBS)全部特征峰的基础上,利用支持向量机建立了有效的茶叶分类模型。采集了15种茶叶样品的有效LIBS光谱数据(190~720 nm),运用窗口平移平滑和峰位漂移函数修正对光谱进行了预处理,再结合主成分分析降维,对绿茶、红茶、白茶实现了98.3%的识别率;对同一种类中不同品种的茶叶也实现了较好的识别。研究结果表明,LIBS在茶叶品种快速识别应用中具有较好的前景。
光谱学 激光诱导击穿光谱 茶叶品种 快速分类 光谱预处理 主成分分析 支持向量机 
中国激光
2019, 46(3): 0311003

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