Ionic liquid-assisted ultrasonic exfoliation of phosphorene nanocomposite with single walled carbon nanohorn as nanozyme sensor for derivative voltammetric smart analysis of 5-hydroxytryptamine
Ionic liquid-assisted ultrasonic exfoliation of phosphorene nanocomposite with single walled carbon nanohorn as nanozyme sensor for derivative voltammetric smart analysis of 5-hydroxytryptamine
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离子液体辅助超声剥离单壁碳纳米角纳米酶传感器磷烯纳米复合材料用于 5-羟色胺的导数伏安智能分析
DOI：
10.1016/j.microc.2021.106697
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发表时间：
2021-11
影响因子：
4.8
通讯作者：
Yangping Wen
中科院分区：
文献类型：
--
作者：
Yifu Zhu;Ting Xue;Yingying Sheng;Jingkun Xu;Xiaoyu Zhu;Weiqiang Li;Xinyu Lu;Liangmei Rao;Yangping Wen
超声辅助液相剥离是制备二维材料的一种高效方法。本文报道了在离子液体（IL）1-乙基-3-甲基咪唑四氟硼酸盐（[EMIm] BF 4）中，在连续氮气保护下，通过超声辅助液相剥离法，以块状黑磷晶体为原料合成磷烯（BP）的一种简便、绿色方法。为了获得更多的洞察力，所制备的BP的形态和组成进行了表征。所制备的BP在含氧和水的环境条件下显示出令人满意的稳定性。本文选择单壁碳纳米角（SWCNH）作为电极材料，通过增强其电催化能力和赋予其类似氧化酶（nanozyme）的特性，将其应用于5-羟色胺（5-HT）的电化学传感。采用导数技术处理伏安图，使伏安峰更尖、更窄，使不对称峰变为更对称峰，减少背景干扰，消除人为误差，直接读出准确值。与传统的线性回归模型相比，采用基于人工神经网络（ANN）算法的机器学习（ML）模型作为人工智能方法，通过浓度与电流之间的关系建立智能传感系统。BP-IL-SWCNH纳米酶传感器在最佳条件下对0.3 - 115 µM范围内的5-HT表现出良好的电催化二阶导数伏安智能分析能力。
Ultrasonic-assisted liquid-phase exfoliation is one of high-efficiency strategies for preparing two-dimensional (2D) materials. Herein, we report a facile and green synthesis of the phosphorene (BP) obtained from bulk black phosphorus crystal in the ionic liquid (IL) 1-ethyl-3-methylimidazoliumtetrafluoroborate ([EMIm]BF4) through ultrasonic-assisted liquid-phase exfoliation under the continuous nitrogen atmosphere. To gain more insight, the morphology and composition of the as-prepared BP were characterized. The prepared BP showed satisfactory stability in ambient condition containing oxygen and water. In the following, single walled carbon nanohorn (SWCNH) was selected to enhance electrocatalytic capacity and endow oxidase-like (nanozyme) characteristics, which was further applied for electrochemical sensing of 5-hydroxytryptamine (5-HT). Derivative techniques were employed for treating voltammograms to obtain sharper and narrower voltammetric peak, transform asymmetric peak into much more symmetrical peak, reduce background interference, eliminate personal error and directly read the accurate value. Machine learning (ML) model based on artificial neural network (ANN) algorithm as an artificial intelligence approach is adopted to establish smart sensing system via the relationship between concentrations and currents in comparison with traditional linear regression model. The BP-IL-SWCNH nanozyme sensor displayed excellent electrocatalytic ability for second-order derivative voltammetric smart analysis of 5-HT range from 0.3 to 115 µM under optimal conditions.
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