Sensors response curves

Table 7.1 Mean values (means) and standard errors of the means (SEM) of relaxation time and maxima of exposition-to-relaxation ratio Max/Max of TCNQ sensor response curves obtained with exhaled air of patients with gastric and duodenal inflammation...

This study demonstrates high efficacy and expediency of the TCNQ derivative-based point-contact multistracture as a prospective asset for development of new sensors. The complex character of the sensors response curve and correlation of some response characteristics with different pathological manifestations in human breath, may be further used as a noninvasive diagnostic method alternative to some invasive approaches currently routinely used in clinic. The need for reliable and feasible gas analysis methods functional in presence of atmospheric air, opens opportunities for application of the proposed sensor technique in other spheres of human activity. High sensitivity of the point-contact multistructure enabling analysis of composite gas mixtures, opens up wide possibilities to apply the demonstrated approach for environment and health protection, such as detection of trace amounts... 

Figure 3.22 Sensor response curves of the Sony DXC-930 digital camera. The data was derived by Barnard et al. (2002c).

An attempt was made to correlate the slope of the sensor response curve to the initial diffusible hydrogen concentration in the sample. The steady state portion of the curve could be assumed to be proportional to the flux of hydrogen from the weld metal. To investigate this possibility theoretical curves were generated using an equation derived from the error function erf(x). 

The four sensor interrogation steps of pulse application, conductivity measurement, float period, and open circuit potential measurement are repeated for a user-defined number of cycles to produce a sensor response curve. Each set of four such steps produces a single-datum point of conductivity and open circuit potential data. Several such points obtained over a period of time produces a response curve. The response curve captures the change in conductivity of the transducer as a function of time following initialization. 

For example, a temperature-measuring device, having its sensor placed in a protecting rube, is a system of second order. For such a system no single rime constant exists in the same way as a first-order system. The behavior of such a system is often given by a response time. Another concept is to give the apparent time constant t, which can be constructed by placing a line in the inflection point of the step response curve see Fig. 12.14. 

Figure 9. Clinical test on a patient response curve of the optical fibre sensor and of Tonocap.

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. 

Fig. 6.14 (a) OFRR vapor sensor responses to DNT vapor samples extracted with various sampling time at room temperature, (b) Calibration curve of DNT mass extracted by on SPME fiber under various extraction times at room temperature... 

This chapter will first consider fundamentals of sensor science including a brief discussion on the main terms encountered in practical applications, such as sensor, transducer, response curve, differential sensitivity, noise, resolution and drift. 

The response curve (RC) represents the calibrated output response of a sensor as a function of the measurand/s applied to its input. For instance, in the case of a chemical sensor based on conductivity (G), it is recommended to use one of the following notations [1] for the output response ... 

In view of the future development of sensors driven by increasing demand for accuracy and precision, and by the opening of new fields close to the biological area (which is oriented toward nano-biosensor fabrication), it appears even more important to properly use the most relevant sensor keywords, such as response curve, sensitivity, noise, drift, resolution, and selectivity. 

Figure 20a.5 is a schematic of an 02 sensor based on fluorescence Ru complexes doped in sol-gel. A corresponding response curve of this sensor to oxygen is shown in Fig. 20a.6. 

Fig. 20a. 6. Response curve of a Ru-fluorescence complex based oxygen optical sensor to oxygen in gas mixture. Courtesy of Ocean Optics, Inc.

C, when the gas surface reactions can be expected to occur at a faster rate. Now it is seen that the response has reached a steady-state value after exposure to the ammonia atmosphere. The extra dip in the response curve seen in the oxygen environment might be due to the slow diffusion of ammonia. Some gas molecules might still be left under the sensor surface in this experiment when hit by the oxygen gas outlet. 

In principle, there are two possible ways to measure this effect. First, there is the end-point measurement (steady-state mode), where the difference is calculated between the initial current of the endogenous respiration and the resulting current of the altered respiration, which is influenced by the tested substances. Second, by kinetic measurement the decrease or the acceleration, respectively, of the respiration with time is calculated from the first derivative of the currenttime curve. The first procedure has been most frequently used in microbial sensors. These biosensors with a relatively high concentration of biomass have a longer response time than that of enzyme sensors. Response times of comparable magnitude to those of enzyme sensors are reached only with kinetically controlled sensors. 

Due to their complex non-monotonous structure the obtained response curves of the new type sensors are much more informative than those of traditional and nano-structured chemical sensors. 

Effect of Feed Flow. The effect of feed flow on sensor response for the CO sensor cell is shown in Figure 9. Similar curves were observed for NO and NO2. Generally, there is a marked increase in sensor cell response with increasing flow (10 to 40 cc/min), followed by a slow rising slope as flow exceeds 50 cc/min. A flow of 60 cc/min was selected for practical use based on tradeoff studies of water management and flow dependence. 

The response of a sensor to the primary species (X) is described by the response curve (Fig. 1.2). Besides the analyte (X), many other interfering species (/) also interact with, and competitively bind to, the binding sites in the selective layer. Because such interactions are non-specific, the sites occupied by the interferants are expressed as the sum (XasO- Let us assume that only the occupied sites (ao) in or at the selective layer result in the output signal from the sensor. The total available activity of binding sites ( st) in the layer is... 

The actual solution for both transient and steady-state response of any zero-flux-boundary sensor can be obtained by solving (2.26) through (2.33) for the appropriate boundary and initial conditions. Fitting of the experimental calibration curves (Fig. 2.10) and of the time response curves (Fig. 2.11) to the calculated ones, validates the proposed model. 

Fig. 2.16 Theoretical (full points) and experimental (open points) time response curve for glucose sensors to step change in concentration (from 0 to 1 mM) (adapted from Caras et al., 1985b, p. 1922)...

Sensing performance for H-,. Sensing performance of the amperometric sensor was examined for the detection of H2 in air. Figure 3 shows the response curve for 2000 ppm H2 in air at room temperature. The response was studied by changing the atmosphere of the sensing electrode from an air flow to the sample gas flow. With air the short circuit current between two electrodes was zero. On contact with the sample gas flow, the current increased rapidly. The 90% response time was about 10 seconds and the stationary current value was 10yUA. When the air flow was resumed, the current returned to zero within about 20 seconds. 

---