A miniature electronic nose system based on an MWNT–polymer microsensor array and a low-power signal-processing chip

Abstract

This article introduces a power-efficient, miniature electronic nose (e-nose) system. The e-nose system primarily comprises two self-developed chips, a multiple-walled carbon nanotube (MWNT)-polymer based microsensor array, and a low-power signal-processing chip. The microsensor array was fabricated on a silicon wafer by using standard photolithography technology. The microsensor array comprised eight interdigitated electrodes surrounded by SU-8 "walls," which restrained the material-solvent liquid in a defined area of 650 × 760 μm(2). To achieve a reliable sensor-manufacturing process, we used a two-layer deposition method, coating the MWNTs and polymer film as the first and second layers, respectively. The low-power signal-processing chip included array data acquisition circuits and a signal-processing core. The MWNT-polymer microsensor array can directly connect with array data acquisition circuits, which comprise sensor interface circuitry and an analog-to-digital converter; the signal-processing core consists of memory and a microprocessor. The core executes the program, classifying the odor data received from the array data acquisition circuits. The low-power signal-processing chip was designed and fabricated using the Taiwan Semiconductor Manufacturing Company 0.18-μm 1P6M standard complementary metal oxide semiconductor process. The chip consumes only 1.05 mW of power at supply voltages of 1 and 1.8 V for the array data acquisition circuits and the signal-processing core, respectively. The miniature e-nose system, which used a microsensor array, a low-power signal-processing chip, and an embedded k-nearest-neighbor-based pattern recognition algorithm, was developed as a prototype that successfully recognized the complex odors of tincture, sorghum wine, sake, whisky, and vodka.

Carbon Nanotube Chemical Sensors

“…Wei et al developed CNT- and graphene-based electrochemical sensors using Ni and Cu foams as the selectors to differentiate Chinese rice wines by age and manufacturer . Similarly, Tang and co-workers developed a MWCNT/polymer composite sensor array comprising eight different sensing channels to differentiate between several complex alcohol vapors (sake, sorghum liquor, medical liquor, and whiskey), Figure . , The signals here were attributed to differential swelling behaviors of the composites. Interestingly, Kachoosangi et al.…”

Artificial Olfactory Neuron for an In‐Sensor Neuromorphic Nose

“…This power consumption for the olfactory neuron module was much lower compared to the power consumption for the conversion circuits to transfer data from the sensor to the processors in an E‐nose chip. [ 55–57 ] Note that P peak (not P avg ) is similar to the power consumption of interface circuits and ADCs in the conventional E‐nose chip, although P peak includes the power consumed in the sensor part, indicating a large power reduction (Table S2, Supporting Information). However, further development of ultralow power gas sensors will help the reduction of power consumption of the entire gas sensing module, because the major power consumption occurs in the microheater for the SMO gas sensor.…”

A Low-Power Integrated Humidity CMOS Sensor by Printing-on-Chip Technology

“…Among different kinds of sensing quantities, gas sensing, e.g., e-nose systems, are a big topic for applications in indoor-air-quality (IAQ) monitoring [ 3 ] and medical care [ 4 ]. A numbers of technologies have been exploited to develop novel gas sensors which can offer miniaturized and low-power consumption characteristics [ 5 – 9 ]. However, most gas sensor systems are limited by the dimensions of discrete sensor devices, or the power consumption is still too large to combine with batteries or self-sustaining power harvesters for long-term usage [ 10 ].…”