High‐sensitive neural network ammonia sensor based on shear horizontal surface acoustic wave devices

Abstract

In this paper, a shear horizontal surface acoustic wave devices coated with L-glutamic acid hydrochloride were applied as ammonia sensors. This sensor has shown high sensitivity and fast responses to ppb-level ammonia. The frequency shift linearly increased as the ammonia concentration increased from 40 to 400 ppb in dry environment. In the humid environment, the frequency shift gradually decreased with ammonia concentration increasing. In order to precisely estimate the ammonia in humid environment, two different neural models, the conventional feedforward neural network and quantum neural network, were used as the identifier and their performances were reported and compared.

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