Detector characteristics response

In practice, the evaluation of EF is not as simple and straightforward as it seems, because the actual analyte concentration in the concentrate, C, is usually unknown. Therefore, an approximation of EF is usually accepted by defining EF as the ratio of the slopes of the linear section of the calibration curves before and after the preconcentration, all based on the detector responses to Cj. The evaluation is therefore based on response enhancements, and not on the actual concentration increases. Nevertheless, the EF values deduced will be close to the true value if the analytical conditions, including detector response characteristics, remain generally unchanged for the two calibrations. 

In FI preconcentration systems, sometimes the analyte signals are enhanced during the introduction of the concentrate into the detector through mechanisms other than increase in concentration of analyte, such as enhancement through organic solvent effect in flame AAS when organic solvents are used as the concentrate media. The analyte signals may also be influenced by variations in detector response characteristics of the... 

The requirements for an instrumental method of specifying reflected color include a light source, the colored object and a detector. What this means is that all we need is a source, an object and a detector. However, since the response characteristics of these optical components are not linear, nor flat, we need an analogue system in order to be able to measure color. 

Detectors are usually conpued in terns of their operational characteristics defined by the nininvin detectable quantity of standards, the selectivity response ratio between standards of different conpositlon or structure, and the range of the linear portion of the detector-response calibration curve. These terns are wid. y used to neasure the perfomance of different chronatographic detectors and were fomally defined in section 1.8.1. 

Figure 8.6 Positive ion LD TOF mass spectra of P. falciparum parasite sample (upper trace), and a control (uninfected blood) sample (lower trace). Protocol D is used for sample preparation. Both samples—in vitro cultured P. falciparum parasites in whole blood, and the whole blood control—are diluted to 5% hematocrit (10-fold) in PBS buffer. In the infected sample the estimated number of deposited parasites per sample well is approximately 100. A commercial LD TOF system is used, and both spectra are normalized to the same (40 mV) detector response value. Each trace represents the average of one hundred single laser shot spectra obtained from linear scanning of an individual well (no data smoothing). The characteristic fingerprint ions of detected heme in the upper trace are denoted.

Skinner, S.W. and P.C. Nyberg, Method for the Calculation of Radon Response Characteristics of Integrating Detectors, Health Physics 45 544-550 (1983). 

Methods. Absorption spectra were recorded using an Hitachi model 150-20 spectrophotometer/data processor system. Uncorrected steady-state fluorescence emission spectra were recorded using a Perkin-Elmer MPF-44A spectrofluorimeter. These spectra were collected and stored using a dedicated microcomputer and then transferred to a VAX 11/780 computer for analysis. Fluorescence spectra were corrected subsequently for the response characteristics of the detector (21). Values of the fluorescence quantum yield, <) , were determined relative to either quinine bisulfate in IN H2S04 )>f =... 

The basic detection concepts can be presented for the "zerodimensional case where detection decisions and detection limits are established simply from the characteristics of the chemical signal (instrument response), without giving detailed attention to other dimensions such as time, wavelength, analyte concentration, etc. Actually, higher dimensional situations (multiparameter separations or detector responses) reduce to this case either through sequential classification schemes or via algorithms which operate directly on the multidimensional data. 

Figure 42 shows the temperatures measured by two-color pyrometry for step changes in temperature compared with the true temperature and calculated temperatures based on the response characteristics of the detectors (time constant = 0.311 s). The response speed of the detectors in this case was too slow to follow the actual temperature decrease, but the temperature rise is reasonably well detected. Spjut and Bolsaitis reported that two-color temperatures are unreliable when the optical properties of the microparticle change during the experiment, but they showed that single-wavelength temperatures can yield consistent results and, with some caveats, are adequate for particle temperature measurement. 

Fig. 42. The response to a step increase (a) and a step decrease (b) in temperature of a laser-heated particle, from Spjut and Bolsaitis (1987). The data were obtained using two-color pyrometry, and the calculated curves are based on the response characteristics of the detectors.

Two parameters have been demonstrated to be fundamental in calculating the performance characteristics of a continuous analyser, the lag phase and the half-wash time they afford a correlation between the approach to steady state, fraction of steady state reached in a given time and the interaction between samples. The half-wash time (Wy ) is the time for the detector response to change from any value to half that value, the lag phase L is defined in the ensuing discussion. 

The contribution of slow detector response can be ne ected when the base peak width is at least 40 times larger than r [cf. Eq. 3)]. In practice it is difficult to correct for such distortion because the time constant concept is only an approximation. It is not very reproducible and is sensitive to changes in the characteristics of the various elemehts of the electronics. Furthermore, detectors, amplifiers, and record are not first-order systems mid their response is only iippruxinntted by an exponential function (44). The response time is therefore defined by the time neces-... 

The significant intrinsic limitation of SEC is the dependence of retention volumes of polymer species on their molecular sizes in solution and thus only indirectly on their molar masses. As known (Sections 16.2.2 and 16.3.2), the size of macromolecnles dissolved in certain solvent depends not only on their molar masses but also on their chemical structure and physical architecture. Consequently, the Vr values of polymer species directly reflect their molar masses only for linear homopolymers and this holds only in absence of side effects within SEC column (Sections 16.4.1 and 16.4.2). In other words, macromolecnles of different molar masses, compositions and architectures may co-elute and in that case the molar mass values directly calculated from the SEC chromatograms would be wrong. This is schematically depicted in Figure 16.10. The problem of simultaneous effects of two or more molecular characteristics on the retention volumes of complex polymer systems is further amplifled by the detection problems (Section 16.9.1) the detector response may not reflect the actual sample concentration. This is the reason why the molar masses of complex polymers directly determined by SEC are only semi-quantitative, reflecting the tendencies rather than the absolute values. To obtain the quantitative molar mass data of complex polymer systems, the coupled (Section 16.5) and two (or multi-) dimensional (Section 16.7) polymer HPLC techniques must be engaged. 

Before the ruggedness test could be contemplated it was essential to fully validate the method with respect to other method characteristics. Hence the following tests were carried out, specificity, spectral purity of chromatographic peaks, linearity of detector response, and repeatability over 100 injections. Satisfactory results were achieved for all these experiments before we continued to the ruggedness test. 

Figure 15.6 is a plot of the thermal conductivity of mixtures of helium and nitrogen obtained on an apparatus similar to that described in the next section. Characteristically, the thermal conductivity of most mixtures does not vary linearly with concentration. The slope of the curve at any point determines the value of A/c and, therefore, the detector response. Figure 15.6 also illustrates that the greater the difference between thermal conductivities of the adsorbate and carrier gas, the higher will be the slope and therefore the detector response. 

For implementations that rely upon d.c. signal detection, such as the LCTF NIR imaging system, subtraction of the so-called dark response is critical. There are two components of this response, one that is wavelength independent, the detector response when no photons are impinging on the array, a characteristic of the... 

One aspect of CAD detection to be aware of is that analyte response is directly proportional to percentage of organic however, the magnitude of this effect is very similar for all compounds.69 Therefore, a shift in retention time will cause a difference in response. Because of the uniformity of response characteristics outlined above, CAD is a very interesting option as a universal detection system for HPLC. From the author s experience, it is a very simple detector to utilize and can be integrated with laboratory data collection system quite easily with the analog output. 

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