Aqueous Ammonia Sensor with Neuromorphic Detection

IF 5.3 2区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Kateryna Vyshniakova, Mohammad Javad Mirshojaeian Hosseini, Huiwen Bai, Masoome Fatahi, Victor Marco Rocha Malacco, Shawn S Donkin, Richard M Voyles, Robert A. Nawrocki
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This makes the sensor capable of detecting ammonia in a range of concentrations between 0.0001 and 0.1 <i>M</i>. A neuromorphic circuit converts the analog change of ammonia concentration expressed as a change of sensor impedance to the digitized frequency of spikes. Detecting such a low ammonia concentration is critical for environmental monitoring and medical diagnosis. 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引用次数: 0

Abstract

A hybrid inorganic–organic neuromorphic sensor utilizing a thin film zinc oxide (ZnO) detector with organic neuromorphic pre-processing is developed to quantify ammonia in aqueous environments, including biological analytes. Impedimetric ZnO sensor, connected to an organic somatic circuit, reliably and accurately detects changes in electrical impedance to measure and quantify variations in the concentration of ammonia. The sensing mechanism of the ZnO thin film sensor is hypothesized to be the cause of the decrease in resistance of a solution with an increase in ammonia concentration. It is found that the surface oxide of the ZnO layer reacts with even very low concentrations of ammonia (NH3$N{H}_{3}$), leading to changes in resistivity. This makes the sensor capable of detecting ammonia in a range of concentrations between 0.0001 and 0.1 M. A neuromorphic circuit converts the analog change of ammonia concentration expressed as a change of sensor impedance to the digitized frequency of spikes. Detecting such a low ammonia concentration is critical for environmental monitoring and medical diagnosis. The digitized nature of neuromorphic signal pre-processing makes it more resilient for signal transmission in the presence of noise and serves as a demonstration of “smart sensing.”

Abstract Image

采用神经形态检测技术的水氨传感器
利用氧化锌(ZnO)薄膜探测器和有机神经形态预处理技术开发了一种无机-有机混合神经形态传感器,用于量化水环境中的氨,包括生物分析物。与有机体感电路相连的阻抗型氧化锌传感器能够可靠、准确地检测电阻抗的变化,从而测量和量化氨浓度的变化。假设氧化锌薄膜传感器的传感机制是溶液电阻随氨浓度增加而降低的原因。研究发现,即使是浓度很低的氨气(NH3$N{H}_{3}$),氧化锌层的表面氧化物也会发生反应,导致电阻率发生变化。神经形态电路将以传感器阻抗变化表示的氨浓度模拟变化转换为数字化的尖峰频率。检测如此低的氨浓度对于环境监测和医疗诊断至关重要。神经形态信号预处理的数字化特性使其在噪声环境下的信号传输更具弹性,是 "智能传感 "的一种体现。
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来源期刊
Advanced Electronic Materials
Advanced Electronic Materials NANOSCIENCE & NANOTECHNOLOGYMATERIALS SCIE-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
11.00
自引率
3.20%
发文量
433
期刊介绍: Advanced Electronic Materials is an interdisciplinary forum for peer-reviewed, high-quality, high-impact research in the fields of materials science, physics, and engineering of electronic and magnetic materials. It includes research on physics and physical properties of electronic and magnetic materials, spintronics, electronics, device physics and engineering, micro- and nano-electromechanical systems, and organic electronics, in addition to fundamental research.
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