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Pl<a values

Tab. 2.5. Shift in pl Tab. 2.5. Shift in pl<a values with increasing methanol content in water/methanol mixtures (all solutions 0.15 M in KCI).
Double bonds are not freely rotatable (see p.4). If double-bonded atoms have different substituents, there are two possible orientations for these groups. In fumaric acid, an intermediate of the tricarboxylic acid cycle (see p. 136), the carboxy groups lie on different sides of the double bond (trans or E position). In its isomer maleic acid, which is not produced in metabolic processes, the carboxy groups lie on the same side of the bond (cis or Z position). Cis-trans isomers (geometric isomers) have different chemical and physical properties—e.g., their melting points (Fp.) and pl[Pg.8]

The stronger an acid is, the lower its placetic acid, CH3COOH) can protonate (green arrow) the base of the pair with the higher plammonium acetate (NH4 and CH3COO ) only forms very little CH3COOH and NH3. [Pg.18]

Water enhances the acidic or basic properties of dissolved substances, as water itself can act as either an acid or a base. For example, when hydrogen chloride (HCl) is in aqueous solution, it donates protons to the solvent (1). This results in the formation of chloride ions (Cr) and protonated water molecules (hydronium ions, H3O+, usually simply referred to as H" ). The proton exchange between HCl and water is virtually quantitative in water, HCl behaves as a very strong acid with a negative pl[Pg.30]

All amino acids have at least two ionizable groups, and their net charge therefore depends on the pH value. The COOH groups at the a-C atom have plmonocarboxylic acids. The basicity of the a-amino function also varies, with pKa values of between 8.8 and 10.6, depending on the amino acid. Acidic and basic amino acids have additional ionizable groups in their side chain. The plside chains are listed on p.60. The electrical charges of peptides and proteins are mainly determined by groups in the side chains, as most a-car-boxyl and a-amino functions are linked to peptide bonds (see p. 66). [Pg.58]

In addition, the polarity of the side chains is indicated by color. It increases from yellow, through light and dark green, to bluish green. For ionizing side chains, the corresponding pl[Pg.60]

The pl a values are approximately additive and a linear relationship of the type p aic Isolds for the whole set (pK is the pK of pyreizole itself and... [Pg.223]

By measuring the position of the equilibrium, the relative strengths of acids and bases can be determined and a sequence of acid-base strengths can be established. Such measurements give the so-called thermodynamic acidity. Acid strengths (relative to water) of some important acids are presented in Table 1 with their pl a values listing the acids in decreasing order of acidity (7). [Pg.6]

As an example, PL can be used to precisely measure the alloy composition xof a number of direct-gap III-V semiconductor compounds such as Alj Gai j, Inj Gai jfAs, and GaAsjfPj j(, since the band gap is directly related to x. This is possible in extremely thin layers that would be difficult to measure by other techniques. A calibration curve of composition versus band gap is used for quantification. Cooling the sample to cryogenic temperatures can narrow the peaks and enhance the precision. A precision of 1 meV in bandgap peak position corresponds to a value of 0.001 for xin AljfGai j, which may be usefiil for comparative purposes even if it exceeds the accuracy of the x-versus-bandgap calibration. [Pg.378]

We now have both the data matrix A and the concentration vector c required to calculate PLS S VD. Both A and c are necessary to calculate the special case of PLS singular value decomposition (PLSSVD). The operation performed in PLSSVD is sometimes referred to as the PLS form of eigenanalysis, or factor analysis. If we perform PLSSVD on the A matrix and the c vector, the result is three matrices, termed the left singular values (LSV) matrix or the V matrix the singular values matrix (SVM) or the S matrix and the right singular values matrix (RSV) or the V matrix. [Pg.114]

The PL lifetime values r obtained by fitting a stretched exponential function decrease with increasing PL peak energy PPL. For micro PS dried in a vacuum, for which the PL energies range from 1.5 to 3.5 eV, this dependence can roughly be fitted to the empirical relation ... [Pg.146]

Figure 1.13. Crystal structure of solution-grown pentacene along (a) the c-axis and (b) the fe-axis. Pl,a = 0.790 nm, b = 0.606 nm, c = 1.601 nm, a = 101.9°, P = 112.6°, y = 85.8°. Crystallographic data from Campbell et al, 1961. See Table 1.10 for comments on the values of the lattice parameters. Crystal structure of p-6P (c) c-planes along their long molecular axis and (d) along the fe-axis. P2i /c, a = 2.624 nm, b = 0.557 nm, c = 0.809 nm, p = 98.17°. Crystallographic data from Baker et al, 1993. Crystal stmcture of o -6T (e) fee-plane and (f) projection along the c-axis. P2ifn,a = 4.471 nm,fe = 0.785 nm,c = 0.603 nm,jS = 90.76°. Crystallographic data from Horowitz et al, 1995. Figure 1.13. Crystal structure of solution-grown pentacene along (a) the c-axis and (b) the fe-axis. Pl,a = 0.790 nm, b = 0.606 nm, c = 1.601 nm, a = 101.9°, P = 112.6°, y = 85.8°. Crystallographic data from Campbell et al, 1961. See Table 1.10 for comments on the values of the lattice parameters. Crystal structure of p-6P (c) c-planes along their long molecular axis and (d) along the fe-axis. P2i /c, a = 2.624 nm, b = 0.557 nm, c = 0.809 nm, p = 98.17°. Crystallographic data from Baker et al, 1993. Crystal stmcture of o -6T (e) fee-plane and (f) projection along the c-axis. P2ifn,a = 4.471 nm,fe = 0.785 nm,c = 0.603 nm,jS = 90.76°. Crystallographic data from Horowitz et al, 1995.
PLS falls in the category of multivariate data analysis whereby the X-matrix containing the independent variables is related to the Y-matrix, containing the dependent variables, through a process where the variance in the Y-matrix influences the calculation of the components (latent variables) of the X-block and vice versa. It is important that the number of latent variables is correct so that overfitting of the model is avoided this can be achieved by cross-validation. The relevance of each variable in the PLS-metfiod is judged by the modelling power, which indicates how much the variable participates in the model. A value close to zero indicates an irrelevant variable which may be deleted. [Pg.103]


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See also in sourсe #XX -- [ Pg.18 ]




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