ADVANCED HZ MICRO-SENSOR

Advanced Hz Micro-sensor for Environmental and Industrial Application

Abstract

The selectivity of metal oxide Advanced Hertz sensors can be improved by operating the sensors in a temperature-modulated mode. Although the selection of optimal modulating frequencies deserves accurate attention, this aspect has been generally overlooked. In this paper, a systematic method to determine which are the optimal temperature-modulation frequencies to solve a given gas analysis problem has been introduced, discussed in detail and fully validated for the first time. The optimization method is based on the use of multi-level pseudo-random sequences. These sequences share some properties with white noise and allow for the impulse response of the sensor-gas system to be estimated. Using this strategy, it is shown that the best temperature-modulating frequencies to discriminate and quantify gases using an array of four metal oxide Advanced Hertz sensors are identified. The process is illustrated solving a practical application: the quantitative analysis of acetaldehyde, ethylene, ammonia and their binary mixtures (monitoring climacteric fruit during cold storage). By using a multi-sinusoidal temperature-modulating signal, the frequencies of which are a reduced set of the optimal ones, the gases and gas mixtures were discriminated with a 100% success rate. In gas identification, features from the sensors' dynamic response extracted via the fast Fourier transform (FFT) were used together with a fuzzy ARTMAP neural network. After the identification process, the concentration of the different species was accurately predicted by PLS-based calibration models. These results compare favorably with the ones obtained when the sensor array was operated in a steady-state mode. The optimization method is shown to be consistent and effective, since the process of determining optimal modulation frequencies and the validation process were conducted using different metal oxide Advanced Hertz sensor micro-arrays (of the same type) and different measurement sets.

Table of Contents

Abstract2

Chapter I: Introduction3

Hydrogen sensors3

Microcantilever-based sensors3

Cantilever-based hydrogen sensors3

Aim of the Research3

Chapter II: Literature Review3

Gas/sensor system identification by multi-level pseudo-random sequences3

Fabrication of thin film3

Chapter III: Methodology3

Experimental3

Experimental set-up3

Chapter IV: Results and Discussion3

Spectral analysis of the impulse response estimates3

Selection of the temperature-modulating frequencies3

Optimization for gas identification3

Optimization for quantitative gas analysis3

Gas analysis using multi-sinusoidal temperature modulation3

Analysis using the steady-state response3

Chapter V: Conclusions3

References3

Chapter I: Introduction

It is well known that metal-oxide semiconductor Advanced Hertz sensors still suffer from serious shortcomings. These are mainly related to their low selectivity and response drift . Using response signals resulting from the operation of metal oxide Advanced Hertz sensors in a temperature-modulated mode has been, by far, the most studied dynamic method for improving their sensitivity and selectivity and for counteracting response drift , , , , , , , and . Despite the improvements reported in the last years, semiconductor Advanced Hertz sensors are hardly ever used in quantitative gas analyzers. Their typical applications are found in alarm-level monitors.

The sensitive layers of metal oxide Advanced Hertz sensors are made up of particles (particle size can range from nanometers up to microns) and atmospheric oxygen is adsorbed on their surfaces. Oxygen adsorbates abstract electrons from the conduction band of the sensing material, which results in the ...