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Highly selective gas sensor arrays based on thermally reduced graphene oxide

机译:基于热的高选择性气体传感器阵列 减少氧化石墨烯

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摘要

The electrical properties of reduced graphene oxide (rGO) have been previously shown to be very sensitive to surface adsorbates, thus making rGO a very promising platform for highly sensitive gas sensors. However, poor selectivity of rGO-based gas sensors remains a major problem for their practical use. In this paper, we address the selectivity problem by employing an array of rGO-based integrated sensors instead of focusing on the performance of a single sensing element. Each rGO-based device in such an array has a unique sensor response due to the irregular structure of rGO films at different levels of organization, ranging from nanoscale to macroscale. The resulting rGO-based gas sensing system could reliably recognize analytes of nearly the same chemical nature. In our experiments rGO-based sensor arrays demonstrated a high selectivity that was sufficient to discriminate between different alcohols, such as methanol, ethanol and isopropanol, at a 100% success rate. We also discuss a possible sensing mechanism that provides the basis for analyte differentiation.
机译:还原氧化石墨烯(rGO)的电性能先前已显示出对表面吸附物非常敏感,因此使rGO成为高度敏感的气体传感器的非常有前途的平台。然而,基于rGO的气体传感器的选择性差仍然是其实际使用的主要问题。在本文中,我们通过采用基于rGO的集成传感器阵列而不是关注单个传感元件的性能来解决选择性问题。这种阵列中的每个基于rGO的设备都具有独特的传感器响应,这是因为rGO膜在从纳米级到宏观级的不同组织级别上的不规则结构。所得的基于rGO的气体传感系统可以可靠地识别出几乎具有相同化学性质的分析物。在我们的实验中,基于rGO的传感器阵列表现出很高的选择性,足以以100%的成功率区分不同的醇,例如甲醇,乙醇和异丙醇。我们还将讨论一种可能的传感机制,该机制为分析物的区分提供了基础。

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