Sensors response

In order to obtain the output of a sensor, we need to integrate the response over all possible wavelengths. Let E(X, x/) be the irradiance of wavelength /. falling onto an infinitesimal small patch on the sensor array located at position x/. Let S(/.) be a vector of the sensor s response function. That is, if we have three different types of sensors, one 

In Section 3.3 we have seen that the irradiance at the sensor array is proportional to the radiance given off by the corresponding object patch. In the following equation, we assume a scaling factor of one for simplicity, i.e. E(X,xj) = L(X, Xobj) where xobj is the position of the object patch that is projected onto x/ on the sensor array. Then we obtain the following expression for the intensity measured by the sensor. 

The sensor s response characteristics can often be approximated by delta functions (Finlayson and Hordley 2001b). Even though each sensor responds to a range of wavelengths, in practice they are either close enough to delta functions or they can be sharpened (Barnard et al. 2001 Finlayson and Funt 1996 Finlayson et al. 1994a,b) such that this assumption is approximately correct. Assuming that the sensor s response characteristics can be described by delta functions, we have 

At each image point, we only measure three values. We obtain the intensities from the sensor in the red, green, and blue part of the spectrum. This leads to the RGB color 

Similarly, the amount of reduced mediator in the biological layer, given by  

The time-dependent accumulation of reduced mediator is given by the difference between its biological turnover and the fluxes to the electrode and into the membrane  

The turnover number, kT, reflects the redox activity of the immobilized cells. The resulting electrode current is given by Faraday s law  

Equations (7.12)-(7.24) apply to both the transient and steady-states. 

The method of Laplace transforms can be used to solve equations (7.17)-(7.24), Appendix 1. Re-arrangement of (7.A14) yields  

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The performance characteristics of ceramic sensors are defined by one or more of the foUowing material properties bulk, grain boundary, interface, or surface. Sensor response arises from the nonelectrical input because the environmental variable effects charge generation and transport in the sensor material. 

The accuracy of C depends on the choice of sensors. As det(R) increases, the agreement between the calculated C and the tme C gets better. To improve accuracy, it is recommended where possible to have more sensors than analytes. In some cases, such as when one sensor s response is a linear combination of the other sensor responses, the number of sensors must be greater than the number of analytes. If the number of sensors is greater than the numbers of analytes, Ris not a square matrix and the sensitivity becomes... 

Given that one sample is to be analy2ed for r analytes usings sensors (p > r) by making a series of n standard additions in > r) to the sample and recording the sensor responses after each addition, the equation becomes... 

Aromatic solvents or polycyclic aromatic hydrocarbons (PAFI) in water, e.g. can be detected by QCM coated with bulk-imprinted polymer layers. Flere, the interaction sites are not confined to the surface of the sensitive material but are distributed within the entire bulk leading to very appreciable sensor responses. Additionally, these materials show high selectivity aromatic solvents e.g. can be distinguished both by the number of methyl groups on the ring (toluene vs. xylene, etc.) and by their respective position. Selectivity factors in this case reach values of up to 100. 

The complex obtained when L = 2,2 -bipyridine was used in the development of an optical fiber sensor that works in the reflection mode [138]. The sensor response for three different VOCs with four different concentrations each was studied and it was shown that the sensor responded to the three VOCs and that it was possible to distinguish between the different concentrations. 

The strategy depends on the situation and how we measure the concentration. If we can rely on pH or absorbance (UV, visible, or Infrared spectrometer), the sensor response time can be reasonably fast, and we can make our decision based on the actual process dynamics. Most likely we would be thinking along the lines of PI or PID controllers. If we can only use gas chromatography (GC) or other slow analytical methods to measure concentration, we must consider discrete data sampling control. Indeed, prevalent time delay makes chemical process control unique and, in a sense, more difficult than many mechanical or electrical systems. 

Another approach, developed in our laboratory, consists of the compartmentalization of the sensing layer25"27. This concept, only applicable for multi-enzyme based sensors, consist in immobilizing the luminescence enzymes and the auxiliary enzymes on different membranes and then in stacking these membranes at the sensing tip of the optical fibre sensor. This configuration results in an enhancement of the sensor response, compared with the case where all the enzymes are co-immobilized on the same membrane. This was due to an hyperconcentration of the common intermediate, i.e. the final product of the auxiliary enzymatic system, which is also the substrate of the luminescence reaction, in the microcompartment existing between the two stacked membranes. 

Over the last several years, the number of studies on application of artificial neural network for solving modeling problems in analytical chemistry and especially in optical fibre chemical sensor technology, has increase substantially69. The constructed sensors (e.g. the optical fibre pH sensor based on bromophenol blue immobilized in silica sol-gel film) are evaluated with respect to prediction of error of the artificial neural network, reproducibility, repeatability, photostability, response time and effect of ionic strength of the buffer solution on the sensor response. 

McDonagh C., Bowe P., Mongey K., MacCraith B., Characterisation of porosity and sensor response times of sol-gel-derived thin films for oxygen sensor applications, J. Non-Cryst. Solids 2002 306 138-148. 

A special nonspecific sensor response might be due to the cross-reactivity of immobilized antibodies. Besides the analyte, an antibody can bind also other entities bearing a similar antigenic epitope, e.g. the detection of some pathogenic bacteria can be interfered by the binding of non-pathogenic bacteria with the same surface antigen. 

A major disadvantage is that the direct sensor detection cannot distinguish between the sensor response to the specific analyte binding from the response to a possible nonspecific adsorption of other compounds. The nonspecific fouling from blood or blood serum seems to be one of the main barriers for practical application of immunosensors in medical diagnostics. 

The sensor response depends not only on the polarity of the analyte, but also on the flow environment. In the mammalian olfactory system, the nasal cavity structure plays an extremely important role in odor discrimination13. 

In contrast to other analytical methods, ion-selective electrodes respond to an ion activity, not concentration, which makes them especially attractive for clinical applications as health disorders are usually correlated to ion activity. While most ISEs are used in vitro, the possibility to perform measurements in vivo and continuously with implanted sensors could arm a physician with a valuable diagnostic tool. In-vivo detection is still a challenge, as sensors must meet two strict requirements first, minimally perturb the in-vivo environment, which could be problematic due to injuries and inflammation often created by an implanted sensor and also due to leaching of sensing materials second, the sensor must not be susceptible to this environment, and effects of protein adsorption, cell adhesion, and extraction of lipophilic species on a sensor response must be diminished [13], Nevertheless, direct electrolyte measurements in situ in rabbit muscles and in a porcine beating heart were successfully performed with microfabricated sensor arrays [18],... 

FIGURE 4.5 Typical ISE response curves to monovalent cations (solid circles) with a response slope of 59.2mV decade-1 and to divalent cations (open circles) with a Nemstian slope of 29.6mV decade-1. Intercepts of the linear ranges of sensor responses define the lower and higher detection limits. 

Another problem that is common for all membrane-based solid-state sensors is the ill-defined membrane-metal interface. A large exchange current density is required to produce a reversible interface for a stable potentiometric sensor response. One approach to improving this interface is to use conducting polymers. Conducting polymers are electroactive n-conjugated polymers with mixed ionic and electronic conductivity. They... 

Further improvement of the Prussian blue-based transducer presents two principal problems. First, Prussian blue layers are not mechanically stable, especially on smooth electrode surfaces because of their poly crystalline nature. Second, despite the low electrode potential used, the most powerful reductants like ascorbic acid still interfere with sensor response if present in excessive concentrations. 

Hence, non-conducting polymers deposited on the top surface of Prussian blue-modified electrodes only slightly decrease sensor response, but dramatically improve both stability and selectivity of the transducer. 

Huges, R.C., Schubert, W.K. and Buss, R.J., Solid-state hydrogen sensors using palladium-nickel alloys Effect of alloy composition on sensor response, Journal of Electrochemical Society, 142, 249,1995. 

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