Gas Sensors Based on Ceramic p-n Heterocontacts

Aygün, Seymen

doi:10.2172/837264

Cited by 1 publication

(1 citation statement)

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“…The adsorption of gas molecules to the surface changes the potential barrier height at the interface as well as the carrier transport inside the straight semiconductor. Such semiconductor junction sensors based on nanowires and nanoparticles have been successfully demonstrated. − Recently, sensors based on p-type semiconductors (such as CuO) also has demonstrated considerable potential for the detection of various gases, such as C 2 H 5 OH, H 2 S, H 2 , CO, and NH 3. − Unlike n–n and p–n junctions, the holes in p–p junction flow through the surface accumulation layer, formed near the surface because of the oxygen adsorption when kept in the air …”

Section: Introductionmentioning

confidence: 99%

Self-Assembled and Highly Selective Sensors Based on Air-Bridge-Structured Nanowire Junction Arrays

Park

Choi

Kim

et al. 2013

ACS Appl. Mater. Interfaces

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We describe a strategy for creating an air-bridge-structured nanowire junction array platform that capable of reliably discriminating between three gases (hydrogen, carbon monoxide, and nitrogen dioxide) in air. Alternatively driven dual nanowire species of ZnO and CuO with the average diameter of ∼30 nm on a single substrate are used and decorated with metallic nanoparticles to form two-dimensional microarray, which do not need to consider the post fabrications. Each individual nanowires in the array form n-n, p-p, and p-n junctions at the micro/nanoscale on single substrate and the junctions act as electrical conducting path for carriers. The adsorption of gas molecules to the surface changes the potential barrier height formed at the junctions and the carrier transport inside the straight semiconductors, which provide the ability of a given sensor array to differentiate among the junctions. The sensors were tested for their ability to distinguish three gases (H2, CO, and NO2), which they were able to do unequivocally when the data was classified using linear discriminant analysis.

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