KEYWORDS: Sensors, Molecules, Gas sensors, Diffusion, Biological and chemical sensing, Resistance, Stochastic processes, Statistical analysis, Thermometry, Chemical analysis
We present a short survey on fluctuation-enhanced gas sensing. We compare some of its main characteristics with those
of classical sensing. We address the problem of linear response, information channel capacity, missed alarms and false
alarms.
We propose a new way of pattern recognition which can distinguish different stochastic processes even if they have the same power density spectrum. Known crosscorrelation techniques recognize only the same realizations of a stochastic process in the two signal channels. However, crosscorrelation techniques do not work for recognizing independent realizations of the same stochastic process because their crosscorrelation function and cross spectrum are zero. A method able to do that would have the potential to revolutionize identification and pattern recognition, techniques, including sensing and security applications. The new method we are proposing is able to identify independent realizations of the same process, and at the same time, does not give false alarm for different processes which are very similar in nature. We demonstrate the method by using different realizations of two different types of random telegram signals, which are indistinguishable with respect to power density spectra (PDS). We call this method bispectrum correlation coefficient (BCC) technique.
KEYWORDS: Molecules, Sensors, Diffusion, Field effect transistors, Calibration, Statistical analysis, Chemical analysis, Signal processing, Biological and chemical sensing, Nose
A new method for the detection and identification of gas molecules and the analysis of their mixtures is proposed. The new process is based on the analysis of the amplitude density function of surface acoustic wave resonator (SAWR) or MOSFET signal(s). The proposed method has the potential to detect and identify very small numbers of molecules, even a single one. When the number of adsorbed molecules is small, the exact number and type can be determined from first principles of combinatorics.
KEYWORDS: Sensors, Molecules, Gases, Biological and chemical sensing, Chemical analysis, Gas sensors, Diffusion, Calibration, Stochastic processes, Resistance
Both selectivity and sensitivity of chemical sensors can be significantly improved by exploiting the information contained in microfluctuations present in the sensor system. We call our collection of methods to extract information from these microfluctuations Fluctuation-Enhanced Chemical Sensing. In this review paper we summarize our recent experimental and theoretical results using commercial Taguchi sensors, Surface Acoustic Wave (SAW) Devices and MOS-FET based sensors.
The stochastic component of chemical sensor signal contains valuable information that can be visualized not only by spectral analysis but also by using nonlinear characteristic components. The analysis of nonlinear stochastic components enables the extraction of physically interesting and useful features and may lead to significant improvements in selectivity and sensitivity. Various measures of nonlinearity are presented and estimated for sample sensor data obtained from commercial chemical sensors. Particular attention was paid to the bispectrum function that detects nonlinear and non-stationary components in the analyzed noise. The results suggest that bispectrum measurements provide valuable information about the nature of noise generation in chemical sensors. Moreover, we have found, by analyzing skewness and kurtosis distributions, that the measured time series were stationary.
Conference Committee Involvement (7)
Nanosensors and Microsensors for Bio-Systems
11 March 2008 | San Diego, California, United States
Nano-, Micro- and Bio-Sensors and Systems
21 March 2007 | San Diego, California, United States
Smart Electronics, MEMS, BioMEMS, and Nanotechnology
27 February 2006 | San Diego, California, United States
Smart Electronics, MEMS, BioMEMS, and Nanotechnology
7 March 2005 | San Diego, California, United States
Smart Electronics, MEMS, BioMEMS, and Nanotechnology
15 March 2004 | San Diego, CA, United States
Noise and Information in Nanoelectronics, Sensors, and Standards
2 June 2003 | Santa Fe, New Mexico, United States
Smart Electronics, MEMS, BioMEMS, and Nanotechnology
3 March 2003 | San Diego, California, United States
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