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Offsets between detectors

The effect of varying this offset between detectors has been examined (I). The molecular weight averages and bulk intrinsic viscosity of samples... [Pg.79]

It is possible to calculate the offsets between detectors from the independent calibration curves. This was done and the results are shown in Figure 6. The calculated offset between the DRI and UV detectors is constant within experimental uncertainty. In contrast, the calculated offset between the viscometer and DRI detectors shows deviations at its extremes. The cause of these deviations is unclear, but they may be a manifestation of flow effects such as those observed in systems with single capillary viscometers (7). [Pg.88]

As described in the Section 3.3, two supposedly identical detectors are arranged to sample the signal simultaneously along x and y. However, the two detectors are usually not quite identical, and the reference signals to the detectors may not differ by precisely 90°. Also, the sample-and-hold circuits that follow the detectors may have slightly different characteristics. Three types of artifacts result (1) a DC offset between quadrature channels, (2) a gain difference between channels, and (3) a phase difference between channels. In terms of Eq. 3.5, artifact (1) means that there are constant terms of different magnitude added to the sine and cosine terms, while (2) and (3) imply different values of C and 4 rf respectively, for the sine and cosine terms. [Pg.58]

The computer models described provide a functional simulation of SEC-viscometry-LS analysis of linear polymers. The results for the Flory-Schulz MWD are in qualitative agreement with previous results for the Wesslau MWD. Both models emphasize the importance of determining the correct volume offset between the concentration detector and molecular weight-sensitive detectors. For the Flory-Schulz model, the peak shape, as well as the peak elution volume, can provide information about molecular weight polydispersity. Future work will extend the model to incorporate peak skew and polymer branching. [Pg.76]

In the preceding procedure, there is in effect an offset between the detector signals (the difference between the elution volumes Vi and V2 at a given hydrodynamic volume). However, there is no need to estimate this offset because this information is contained in the independent calibration curves. Because the signals are matched through their independent calibration curves, the offset is not necessarily static and, depending on the calibration curves, the offset may vary across the chromatogram. [Pg.88]

Although performance varies with the isotopes for which they are intended, and with the balance in the design between resolution and efficiency, the overall sensitivity of a y-camera collimator is on the order of 5000 counts/(MBqmin) (several hundred counts/(/iCi-min)). In terms of photons detected per photon emitted, this is equivalent to about 2 x lO ". In other words, about two photons out of 10,000 emitted arrives at the crystal. This necessitates exposure times that range from several minutes to the better part of an hour. Fortunately, the large number of photons available from a modest injected radioactive dose more than offsets the poor detector sensitivity. The camera s abiUty to resolve small objects, however, is ultimately limited by the collimator inefficiency. [Pg.481]

Fig. 1. Model Spectra re-binned to CRIRES Resolution To demonstrate the potential for precise isotopic abundance determination two representative sample absorption spectra, normalized to unity, are shown. They result from a radiative transfer calculation using a hydrostatic MARCS model atmosphere for 3400 K. MARCS stands for Model Atmosphere in a Radiative Convective Scheme the methodology is described in detail e.g. in [1] and references therein. The models are calculated with a spectral bin size corresponding to a Doppler velocity of 1 They are re-binned to the nominal CRIRES resolution (3 p), which even for the slowest rotators is sufficient to resolve absorption lines. The spectral range covers ss of the CRIRES detector-array and has been centered at the band-head of a 29 Si16 O overtone transition at 4029 nm. In both spectra the band-head is clearly visible between the forest of well-separated low- and high-j transitions of the common isotope. The lower spectrum is based on the telluric ratio of the isotopes 28Si/29Si/30Si (92.23 4.67 3.10) whereas the upper spectrum, offset by 0.4 in y-direction, has been calculated for a ratio of 96.00 2.00 2.00. Fig. 1. Model Spectra re-binned to CRIRES Resolution To demonstrate the potential for precise isotopic abundance determination two representative sample absorption spectra, normalized to unity, are shown. They result from a radiative transfer calculation using a hydrostatic MARCS model atmosphere for 3400 K. MARCS stands for Model Atmosphere in a Radiative Convective Scheme the methodology is described in detail e.g. in [1] and references therein. The models are calculated with a spectral bin size corresponding to a Doppler velocity of 1 They are re-binned to the nominal CRIRES resolution (3 p), which even for the slowest rotators is sufficient to resolve absorption lines. The spectral range covers ss of the CRIRES detector-array and has been centered at the band-head of a 29 Si16 O overtone transition at 4029 nm. In both spectra the band-head is clearly visible between the forest of well-separated low- and high-j transitions of the common isotope. The lower spectrum is based on the telluric ratio of the isotopes 28Si/29Si/30Si (92.23 4.67 3.10) whereas the upper spectrum, offset by 0.4 in y-direction, has been calculated for a ratio of 96.00 2.00 2.00.
The combination of Fellgett s and Jacquinot s advantage coupled with the inherent speed differential should lead to an enormous difference between FT-IR and dispersive instruments. However, in practice, part of this advantage is offset by the difference in the performance of the triglycine sulfate (TGS) and thermocouple detectors. At low modulation frequencies, the thermocouple detector is about an order of magnitude more sensitive than TGS. [Pg.96]

Being able to control u>0 and uir is not sufficient if we don t know their values. The repetition rate u>r is simply measured by a photo detector at the output of either the laser or the fiber. To measure the offset frequency oj0, a mode nu>r + u>0 on the red side of the comb is frequency doubled to 2(nu>r + oj0). If the comb contains more than an optical octave there will be a mode with the mode number 2n oscillating at 2nu>r+u>0. As sketched in Fig. 3 we take advantage of the fact that the offset frequency is common to all modes3 by creating the beat frequency (=difference frequency) between the frequency doubled red mode and the blue mode to obtain u>0. This method allowed the construction of a very simple frequency chain [14,15,16,17,18,19] that eventually operated with a single laser. It occupies only 1 square meter on our optical table with considerable potential for further miniaturization. At the same time it supplies us with a reference frequency grid across much of the visible and infrared spectrum. [Pg.134]

We now consider quantitatively a few representative ways in which QD can be implemented. Suppose we want to record a 500 Hz wide spectrum. In a non-QD experiment, the ADC should operate at 1 kHz and the carrier is offset from the center of the spectrum by 250 Hz as shown in the figure below. This system can be converted to a QD system by running the ADC at the same 1 kHz rate, alternating the input between the two phase detectors whose references are in quadrature, and setting the carrier in the center of the spectrum. Then each FID is recorded at 500 Hz and the complex FT yields a 500 Hz wide spectrum with identical... [Pg.71]


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See also in sourсe #XX -- [ Pg.79 , Pg.88 ]




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