利用锡纳米粒子功能化石墨烯传感器实现室温下真实空气中乙醇和氨分子的高灵敏度和选择性检测

IF 5.4 3区 材料科学 Q2 CHEMISTRY, PHYSICAL
Manoharan Muruganathan*, Md. Zahidul Islam*, Afsal Kareekunnan, Yosuke Onda, Masashi Hattori and Hiroshi Mizuta, 
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引用次数: 0

摘要

石墨烯具有高表面积,是一种重要的传感材料,但缺乏选择性。由于氧化锡对乙醇有较高的选择性,我们制作了一种用锡纳米粒子(Sn NPs)功能化的石墨烯场效应晶体管(GFET)传感器,以提高其对乙醇检测的选择性和灵敏度。在 200 nm、500 nm、1 μm 和 2 μm 沟道尺寸中,在 200 nm GFET 传感器上功能化的 1 nm 厚锡纳米粒子在真实空气环境中对五种测试气体中的乙醇和氨气具有高灵敏度和选择性检测能力。此外,它们对乙醇和氨气的灵敏度也很高,在室温下可检测到低至 100 ppb 的浓度。制造后的热退火有利于在较小的 200 nm 石墨烯通道内形成 Sn NP 簇和空隙,从而提高了传感器的灵敏度。此外,在 Sn NPs 的存在下,乙醇和氨分子与氧分子的催化反应会释放出电子,这反映在石墨烯传感器测量的 n 掺杂中。这种石墨烯传感器对乙醇和氨的高灵敏度和选择性检测潜力可与传感器集群中的机器学习技术相结合,用于识别不同的气体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Room Temperature Real Air Highly Sensitive and Selective Detection of Ethanol and Ammonia Molecules Using Tin Nanoparticle-Functionalized Graphene Sensors

Room Temperature Real Air Highly Sensitive and Selective Detection of Ethanol and Ammonia Molecules Using Tin Nanoparticle-Functionalized Graphene Sensors

Graphene, with its high surface area, is an important sensing material but lacks selectivity. As tin oxide has a higher selectivity for ethanol, we fabricated a graphene field-effect transistor (GFET) sensor functionalized with tin nanoparticles (Sn NPs) to enhance its selectivity and sensitivity for ethanol detection. Among 200 nm, 500 nm, 1 μm, and 2 μm channel sizes, 1 nm thickness Sn NPs functionalized on 200 nm GFET sensors exhibited high sensitivity and selective detection of ethanol and ammonia among five tested gases in a real air environment. Moreover, they demonstrated high sensitivity for ethanol and ammonia, detecting concentrations as low as 100 ppb at room temperature. The postfabrication thermal annealing facilitates the formation of Sn NP clusters and voids within the smaller 200 nm graphene channel, contributing to the sensor’s high sensitivity. Furthermore, the catalytic reaction of ethanol and ammonia molecules with oxygen molecules in the presence of Sn NPs releases electrons, which are reflected in n-doping in the graphene sensor measurements. The potential of this highly sensitive and selective ethanol and ammonia detection of graphene sensors can be utilized with machine learning techniques in the sensor cluster to identify different gases.

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来源期刊
ACS Applied Energy Materials
ACS Applied Energy Materials Materials Science-Materials Chemistry
CiteScore
10.30
自引率
6.20%
发文量
1368
期刊介绍: ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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