Spectral colors, pure

Figure 3. The three pure spectral colors, the prime-colors, uniquely related to normal human vision. Combined, as shown here, they form a white-light mixture the color of sunlight.

Newton also discovered that the blending of pure spectral colors produced new composite colors. He found that blending only spectral red, green and blue light in various proportions produced essentially all other colors. Thus, these three colors are commonly called the primary colors. 

Third Law Every color except pure spectral colors can be made from any of a large number of combinations of color sources, and those composite colors produced will appear indistinguishable to an observer. 

FIGURE 13.6 Chromaticity diagram containing the CIE chromaticity triangle associated with pure spectral colors. 

Fio. la. Maxwell triangles (triangular co-ordinates). The color triangle obtained by use of primaries red, blue, and green (B, 0, and B) chosen for convenience or availability. They do not have to form an equilateral triangle, nor is white necessarily at the precise center. Even if pure spectral colors had been selected, the plot of the spectrum locus shows that no three real primaries can be selected which will match all possible colors. 

Chroma The deviation of the color from gray. Pure spectral colors such as red and violet have high saturation. Saturation refers strength of the dominant wavelength or hue. Pink and red have the same hue but differing saturation. 

Although the studies on OLEDs have achieved considerable success, it is still difficult to obtain pure emission colors from small organic molecules or conjugated polymers, because their emission spectra typically have a half peak width of about 100 nm. Lanthanide ions can exhibit spectrally narrow emission due to intra-atomic transitions within the 4f shell. Consequently, luminescent lanthanide complexes are good candidates as emitting materials in OLEDs. 

All of the composite colors that can be made by combining various spectral colors, lie inside the tongue-shaped perimeter. The more pure composite colors lie near the perimeter and white lies in the middle. 

The line of purples lies across the bottom of the diagram. These are the only pure, non-spectral colors. 

Pure carbon disulfide is a clear, colorless Hquid with a deHcate etherHke odor. A faint yellow color slowly develops upon exposure to sunlight. Low-grade commercial carbon disulfide may display some color and may have a strong, foul odor because of sulfurous impurities. Carbon disulfide is slightly miscible with water, but it is a good solvent for many organic compounds. Thermodynamic constants (1), vapor pressure (1,2), spectral transmission (3,4), and other properties (1,2,5—7) of carbon disulfide have been deterrnined. Principal properties are Hsted in Table 1. 

In the preceding section, we presented principles of spectroscopy over the entire electromagnetic spectrum. The most important spectroscopic methods are those in the visible spectral region where food colorants can be perceived by the human eye. Human perception and the physical analysis of food colorants operate differently. The human perception with which we shall deal in Section 1.5 is difficult to normalize. However, the intention to standardize human color perception based on the abilities of most individuals led to a variety of protocols that regulate in detail how, with physical methods, human color perception can be simulated. In any case, a sophisticated instrumental set up is required. We present certain details related to optical spectroscopy here. For practical purposes, one must discriminate between measurements in the absorbance mode and those in the reflection mode. The latter mode is more important for direct measurement of colorants in food samples. To characterize pure or extracted food colorants the absorption mode should be used. 

Absorption spectra have also been used in the reexamination of pH-dependent color and structural transformations in aqueous solutions of some nonacylated anthocyanins and synthetic flavylium salts." ° In a recent study, the UV-Vis spectra of flower extracts of Hibiscus rosasinensis have been measured between 240 and 748 nm at pH values ranging from 1.1 to 13.0." Deconvolution of these spectra using the parallel factor analysis (PARAFAC) model permitted the study of anthocyanin systems without isolation and purification of the individual species (Figure 2.21). The model allowed identification of seven anthocyanin equilibrium forms, namely the flavylium cation, carbinol, quinoidal base, and E- and Z-chalcone and their ionized forms, as well as their relative concentrations as a function of pH. The spectral profiles recovered were in agreement with previous models of equilibrium forms reported in literature, based on studies of pure pigments. 

Copolymers 10 derived from 3,6-dibenzosilole and 2,7-fluorene are blue electroluminescent SCPs.27 When the copolymers are used as the emissive layer in EL devices, highly efficient pure blue emissions with CIE coordinates of (x = 0.16, y = 0.07), a 7EL of 3.34%, and a luminance efficiency of 2.02 cd/A at 326 cd/m2 are achieved from the copolymer with 90% fluorene content. The blue color matches the NTSC blue standard (x = 0.14, y = 0.08) quite well. The EL spectral stability of the devices is quite good, even under operation at elevated temperatures. Copolymer 9 derived from 3,6- and 2,7-dibenzosiloles also exhibits high performance with a jyEE of 1.95%, a luminous efficiency of 1.69 cd/A, and a maximal brightness of 6000 cd/m2, with the CIE coordinates of (x = 0.162, y = 0.084).26... 

Purely mathematical approaches using the PSF of the system and/or a priori object information rarely exceeded a factor of two [17,22,23] and were prone to producing artifacts. They can be augmented through additional a priori constraints, such as the objects featuring different absorption or emission spectra [24]. In this case, the resolution problem can become almost trivial, because objects with different spectra can be separated with suitable spectral filters. However, because of the difficulty to mark all features in a sample with different labels, reducing the resolution problem to a color separation... 

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