Fluorescent "turn-off" sensors based on double quantum dots (QDs) has attracted increasing attention in the detection of many materials due to their properties such as more useful information, higher fluorescence efficiency and stability compared with the fluorescent "turn-off" sensors based on single QDs. In this work, highly sensitive and specific method for recognition of 53 different famous green teas was developed based on the fluorescent "turn-off" model with water-soluble ZnCdSe-CdTe double QDs. The fluorescence of the two QDs can be quenched by different teas with varying degrees, which results in the differences in positions and intensities of two peaks. By the combination of classic partial least square discriminant analysis (PLSDA), all the green teas can be discriminated with high sensitivity, specificity and a satisfactory recognition rate of 100% for training set and 100% for prediction set, respectively. The fluorescent "turn-off" sensors based on the single QDs (either ZnCdSe QDs or CdTe QDs) coupled with PLSDA were also employed to recognize the 53 famous green teas with unsatisfactory results. Therefore, the fluorescent "turn-off" sensors based on the double QDs is more appropriate for the large-class-number classification (LCNC) of green teas. Herein, we have demonstrated, for the first time, that so many kinds of famous green teas can be discriminated by the "turn-off" model of double QDs combined with chemometrics, which has largely extended the capability of traditional fluorescence and chemometrics, as well as exhibits great potential to perform LCNC in other practical applications.

中文翻译：

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基于双量子点结合化学计量学的“关断”荧光传感器，对53种著名绿茶进行高灵敏度和特异性识别

基于双量子点（QD）的荧光“关闭”传感器由于与荧光“关闭”传感器相比具有更多有用的信息、更高的荧光效率和稳定性等特性，在许多材料的检测中引起了越来越多的关注。基于单个 QD。在这项工作中，基于水溶性 ZnCdSe-CdTe 双量子点的荧光“关闭”模型，开发了用于识别 53 种不同著名绿茶的高灵敏度和特异性方法。两个量子点的荧光可以被不同的茶不同程度地淬灭，从而导致两个峰的位置和强度不同。通过结合经典的偏最小二乘判别分析（PLSDA），可以高灵敏度地判别所有绿茶，训练集的特异性和令人满意的识别率分别为 100% 和预测集的 100%。基于单量子点（ZnCdSe 量子点或 CdTe 量子点）与 PLSDA 结合的荧光“关闭”传感器也被用于识别 53 种著名的绿茶，但结果并不令人满意。因此，基于双量子点的荧光“关闭”传感器更适合绿茶的大类数分类（LCNC）。在此，我们首次证明了双量子点的“关闭”模型结合化学计量学可以区分这么多种类的名茶，大大扩展了传统荧光和化学计量学的能力，如以及在其他实际应用中显示出执行 LCNC 的巨大潜力。