A Novel Artificial Neuron-Like Gas Sensor Constructed from CuS Quantum Dots/Bi(2)S(3) Nanosheets.
A Novel Artificial Neuron-Like Gas Sensor Constructed from CuS Quantum Dots/Bi(2)S(3) Nanosheets.
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由CUS量子点/BI（2）S（3）纳米片构建的新型人工神经元样气体传感器。
DOI：
10.1007/s40820-021-00740-1
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发表时间：
2021-12-02
影响因子：
26.6
通讯作者：
Zhang Y
中科院分区：
文献类型：
--
作者：
Chen X;Wang T;Shi J;Lv W;Han Y;Zeng M;Yang J;Hu N;Su Y;Wei H;Zhou Z;Yang Z;Zhang Y
通过构建基于CuS量子点（QDs）/Bi 2S 3纳米片（NSs）的人工神经元气敏结构模型，实现了对NO2分子的超灵敏捕获和快速电荷收集与转移.模拟分析表明，CuS量子点和Bi 2S 3 NSs可分别作为NO2的主要吸附位点和电荷传输途径，从而大大增强了NO2的气体捕获能力和电荷传导性能。在线版本包含补充材料，可通过10.1007/s40820-021-00740-1获得。在室温下实时快速检测有毒气体对公共卫生和环境监测尤为重要。基于传统块状材料的气体传感器通常遭受其差的表面敏感位点，导致非常低的气体吸附能力。此外，电荷传输效率通常受到表面敏感区比内部低的缺陷密度的抑制。在这项工作中，基于人工神经网络的启发，构建了一个气体传感结构模型的CuS量子点/Bi 2S 3纳米片（CuS量子点/Bi 2S 3纳米片）。密度泛函模拟分析表明，CuS量子点和Bi 2S 3纳米粒子分别可以作为主要的吸附位点和电荷传输途径.因此，可以通过设计人工神经元类传感器来实现NO2的高灵敏度传感。实验结果表明，CuS量子点的尺寸约为8 nm，具有很好的吸附性，由于量子尺寸效应和丰富的敏感位点，可以提高NO2的灵敏度。Bi 2S 3 NS可以用作电荷转移网络通道以实现有效的电荷收集和传输。模拟生物气味的神经元传感器显示出显著增强的响应值（3.4）、优异的响应性（18 s）和恢复率（338 s）、78 ppb的低理论检测限和优异的NO2选择性。此外，开发的可穿戴设备还可以通过实时信号变化实现NO2的视觉检测。 在线版本包含补充材料，可通过10.1007/s40820-021-00740-1获得。
An ultra-sensitive capture of NO2 molecules and fast charge collection and transfer has been realized by constructing the model of artificial neuron-likegas sensing structure based on CuS quantum dots (QDs)/Bi2S3 nanosheets (NSs)realizes. Simulation analysis revealed that CuS QDs and Bi2S3NSs can be used, respectively, as the main adsorption sites and charge transport pathways, thus leading to a greatly enhanced gas capture ability and charge conduction performance of NO2. The online version contains supplementary material available at 10.1007/s40820-021-00740-1. Real-time rapid detection of toxic gases at room temperature is particularly important for public health and environmental monitoring. Gas sensors based on conventional bulk materials often suffer from their poor surface-sensitive sites, leading to a very low gas adsorption ability. Moreover, the charge transportation efficiency is usually inhibited by the low defect density of surface-sensitive area than that in the interior. In this work, a gas sensing structure model based on CuS quantum dots/Bi2S3 nanosheets (CuS QDs/Bi2S3 NSs) inspired by artificial neuron network is constructed. Simulation analysis by density functional calculation revealed that CuS QDs and Bi2S3 NSs can be used as the main adsorption sites and charge transport pathways, respectively. Thus, the high-sensitivity sensing of NO2 can be realized by designing the artificial neuron-like sensor. The experimental results showed that the CuS QDs with a size of about 8 nm are highly adsorbable, which can enhance the NO2 sensitivity due to the rich sensitive sites and quantum size effect. The Bi2S3 NSs can be used as a charge transfer network channel to achieve efficient charge collection and transmission. The neuron-like sensor that simulates biological smell shows a significantly enhanced response value (3.4), excellent responsiveness (18 s) and recovery rate (338 s), low theoretical detection limit of 78 ppb, and excellent selectivity for NO2. Furthermore, the developed wearable device can also realize the visual detection of NO2 through real-time signal changes. The online version contains supplementary material available at 10.1007/s40820-021-00740-1.
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