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Models spectral response

The CLS method hinges on accurately modelling the calibration spectra as a weighted sum of the spectral contributions of the individual analytes. For this to work the concentrations of all the constituents in the calibration set have to be known. The implication is that constituents not of direct interest should be modelled as well and their concentrations should be under control in the calibration experiment. Unexpected constituents, physical interferents, non-linearities of the spectral responses or interaction between the various components all invalidate the simple additive, linear model underlying controlled calibration and classical least squares estimation. [Pg.356]

A medically reliable UV sensor should have a spectral responsivity that closely follows the erythemal curve between 390 nm and 290 nm. So far, a photodiode with this specific sensitivity has not been available. Modeling the erythema spectrum with the help of filters also delivered only poor results. In fact, most available sunburn detectors vary in their spectral responsivity and may therefore only be used as an indicator for the actual UV charge. [Pg.171]

Photoinduced electron transfer reactions between surface bound dye molecules and semiconductor electrodes are important for practical as well as fundamental reasons. Absorption of light by the dye can improve the spectral response of the semiconductor and these systems are models for the photographic process (47-511. MDC surfaces are excellent substrates for studying electron injection into the conduction band of the semiconductor. [Pg.448]

For a statistical analysis to adequately characterize the distribution of a component, the data should first be processed to obtain the optimum selectivity for that component. In this application the PLS model produces a score image that effectively separates the spectral response of the API from the excipients. Even though there is very little observable contrast in the images of the well blended samples, the results from the poorly blended samples convey conhdence that the method is effective at tracking the API distribution. [Pg.275]

A host of mathematical techniques for standardizing calibration models to facilitate their transfer is available. These generally focus on the coefficients of the model, the spectral response or the predicted values. ... [Pg.477]

Standardizing the coefficients of the model entails modifying the calibration equation. This procedure is applicable when the original equipment is replaced (situation 1 above). Forina et al. developed a two-step calibration procedure by which a calibration model is constructed for the master (F-X), its spectral response correlated with that of the slave X-X) and, finally, a global model correlating variable Y with both X and X is obtained. The process is optimized in terms of SEP and SEC for both instruments as it allows the number of PLS factors used to be changed. Smith et al. propose a very simple procedure to match two different spectral responses. [Pg.477]

Standardizing the spectral response is mathematically more complex than standardizing the calibration models but provides better results as it allows slight spectral differences - the most common between very similar instruments - to be corrected via simple calculations. More marked differences can be accommodated with more complex and specific algorithms. This approach compares spectra recorded on different instruments, which are used to derive a mathematical equation, allowing their spectral response to be mutually correlated. The equation is then used to correct the new spectra recorded on the slave, which are thus made more similar to those obtained with the master. The simplest methods used in this context are of the univariate type, which correlate each wavelength in two spectra in a direct, simple manner. These methods, however, are only effective with very simple spectral differences. On the other hand, multivariate methods allow the construction of matrices correlating bodies of spectra recorded on different instruments for the above-described purpose. The most frequent choice in this context is piecewise direct standardization... [Pg.477]

Mid-IR has also been demonstrated for real-time concentration monitoring of a fermentation using a standard transmission cell, and the spectral response was similar, regardless of whether the broth was filtered or not.38 A PLS regression was used to perform quantitation of the substrate, the lactic acid bacterium, and the major metabolites. In another article describing quantitative mid-IR for fermentation studies, a model system was investigated under various fermentation conditions.39 The mid-IR provided insight into the relative concentrations of carbohydrates, nucleic acids, proteins and lipids in the host cells. Mid-IR has also been demonstrated for multi-component quantitation... [Pg.337]

This is the mechanism proposed in the model for the transduction of visual spectrum photons by the eye. It has led to a very accurate equation for the perceived spectral response of all eyes in the animal world, including the ultraviolet sensitivity of many animals. This is particularly true for the well-documented sensitivity of (many) insects. [Pg.41]

Fig. 6.6. Spectral response of similar photodiodes ITO/PEDOT/PEOPT/Ceo/Al with different thicknesses of the Ceo layer 31 nm (circles), 72 nm (squares), and 87 nm (solid line), and the best fit to the model (dashed line). Spectra were taken from these devices under short-circuit conditions. Asterisks mark the prediction of the model in Fig. 6.4 at wavelength 460 nm... Fig. 6.6. Spectral response of similar photodiodes ITO/PEDOT/PEOPT/Ceo/Al with different thicknesses of the Ceo layer 31 nm (circles), 72 nm (squares), and 87 nm (solid line), and the best fit to the model (dashed line). Spectra were taken from these devices under short-circuit conditions. Asterisks mark the prediction of the model in Fig. 6.4 at wavelength 460 nm...
Within the framework of the Schottky junction theory, many models have been developed to explain the photovoltaic spectral response of organic materials. Assuming a direct formation of carriers, without diffusion of exciton to the surface but taking into account the charge diffusion length Ln p, the photocurrent density Jsc for light incident on the junction side is [64]... [Pg.812]

At the opposite extreme from the oriented gas model for molecular crystals, the neighbouring molecules do interact with each other resulting in spectral properties of the bulk that differ considerably from those of the individual molecule. Interacting molecules of this type often tend to form aggregates even in solution, a phenomenon that has been exploited by the photographic industry for the tuning of the spectral response of silver halide emulsions (Herz 1974 Smith 1974 Nassau 1983). Aggregate formation can lead to the development of new, and often quite intense absorption bands... [Pg.229]

A numerical simulation of this cell based on a one-dimensional model has been carried out by Ernst (2001), Grasso et al. (2002) and by Burgelman and Grasso (2004). In the work of Ernst and Grasso et al., the spectral response data could be simulated with reasonable accuracy using only a few adjustable parameters. These simulations confirm the electron diffusion length in the p-type CdTe films to be approximately 150 nm. The recombination centre density was found to be lO cm . These data indicate that the nanocrystalline CdTe films are of inferior quality than the material used in the conventional, planar CdTe solar cells, where diffusion lengths of 2 //m and defect densities of lO cm are typical. [Pg.437]

This Hnear dependence has been confirmed by Halls et al. using the same bilayer structure but employing PPV as the electron donor [44]. The authors estimated the exciton diffusion length of PPV to be in the range of 6-8 nm from both the spectral response and the absolute efficiency [44]. Later Roman et al. demonstrated optical modeling to be a useful tool for the optimization of such bilayer solar cells, which in their case was based on a polythiophene derivative and Ceo [89]. The optical modeling was detailed by Petterson et al. [46]. [Pg.18]

Channel-to-channel and pixel—to—pixel response. Variation in channel-to-channel and pixel-to-pixel response was measured using an E G G model 590 calibrated, continuous source lamp system. While changes in response across the target were well within the +/- 10% range specified by PARC within the center 10 mm x 10 mm area (400 channels) of the target, there was a definite dependence of both spectral response and channel-to-channel response precision on spatial position, as seen in Figure 8. [Pg.43]

The photocurrent of the photodiode has a dependence on the wavelength of light. This is referred to as the spectral response. Fig. 7.13.7 and Fig. 7.13.8 show the analysis model and spectral response analysis result... [Pg.465]

Second, the positions and llneshapes of resonances arising from potentially mobile parts of the peptide (e,g, side chains) have revealed dynamical aspects of the solid-state structures of peptides. The analysis of molecular motions is simplified In the solid state by the absence of overall molecular tumbling, which modulates spin interactions and leads to complex frequency -dependent spectral responses. In particular, signals arising from aromatic ring side chains are well separated from other resonances, and may be interpreted in terms of reorientation models of these side chains. Such ring dynamics are of great importance in protein structures, and studies with model peptides can help elucidate fundamental aspects of these processes. [Pg.234]


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See also in sourсe #XX -- [ Pg.109 ]




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