Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Quantitative. . . Relationship

To understand how to derive a quantitative relationship between properly and structure... [Pg.487]

Two approaches to quantify/fQ, i.e., to establish a quantitative relationship between the structural features of a compoimd and its properties, are described in this section quantitative structure-property relationships (QSPR) and linear free energy relationships (LFER) cf. Section 3.4.2.2). The LFER approach is important for historical reasons because it contributed the first attempt to predict the property of a compound from an analysis of its structure. LFERs can be established only for congeneric series of compounds, i.e., sets of compounds that share the same skeleton and only have variations in the substituents attached to this skeleton. As examples of a QSPR approach, currently available methods for the prediction of the octanol/water partition coefficient, log P, and of aqueous solubility, log S, of organic compoimds are described in Section 10.1.4 and Section 10.15, respectively. [Pg.488]

A balanced chemical reaction indicates the quantitative relationships between the moles of reactants and products. These stoichiometric relationships provide the basis for many analytical calculations. Consider, for example, the problem of determining the amount of oxalic acid, H2C2O4, in rhubarb. One method for this analysis uses the following reaction in which we oxidize oxalic acid to CO2. [Pg.20]

Quantitative Calculations In acid-base titrimetry the quantitative relationship between the analyte and the titrant is determined by the stoichiometry of the relevant reactions. As outlined in Section 2C, stoichiometric calculations may be simplified by focusing on appropriate conservation principles. In an acid-base reaction the number of protons transferred between the acid and base is conserved thus... [Pg.304]

To develop a more quantitative relationship between particle size and T j, suppose we consider the melting behavior of the cylindrical crystal sketched in Fig. 4.4. Of particular interest in this model is the role played by surface effects. The illustration is used to define a model and should not be taken too literally, especially with respect to the following points ... [Pg.212]

To develop this model into a quantitative relationship between T j, and the thickness of the crystal, we begin by realizing that for the transition crystal liquid, AG is the sum of two contributions. One of these is AG , which applies to the case of a crystal of infinite (superscript °o) size the other AG arises specifically from surface (superscript s) effects which reflect the finite size of the crystal ... [Pg.213]

What we seek next is a quantitative relationship between the extent of the polymerization reaction, the composition of the monomer mixture, and the point of gelation. We shall base our discussion on the system described by reaction (5.U) other cases are derived by similar methods. To further specify the system we assume that A groups limit the reaction and that B groups are present in excess. Two parameters are necessary to characterize the reaction mixture ... [Pg.315]

Melting and recrystallization behavior of virgin PTEE has been studied by dsc (64). A quantitative relationship was found between and the heat of crystallization (A/T) in the molecular weight range of 5.2 x 10 to 4.5 X 1 0, where is heat of crystallization in J/g, which is independent of cooling... [Pg.350]

The quantitative relationship between the degree of adsorption at a solution iaterface (7), G—L or L—L, and the lowering of the free-surface energy can be deduced by usiag an approximate form of the Gibbs adsorption isotherm (eq. 9), which is appHcable to dilute biaary solutions where the activity coefficient is unity and the radius of curvature of the surface is not too great ... [Pg.236]

Dose—response evaluation is used in describing the quantitative relationship between the amount of exposure to a substance and the extent of toxic injury or disease. Data may be derived from animal studies or from studies in exposed human populations. Dose—response toxicity relationship for a substance varies under different exposure conditions. The risk of a substance can not be ascertained with any degree of confidence unless... [Pg.226]

Quantitative Relationship of Conductivity and Antistatic Action. Assuming that an antistatic finish forms a continuous layer, the conductance it contributes to the fiber is proportional to the volume or weight and specific conductance of the finish. As long as the assumption of continuity is fulfilled it does not matter whether the finish surrounds fine or coarse fibers. Assuming a cylindrical filament of length 1 cm and radius r, denoting the thickness of the finish layer as Ar and the specific conductance of the finish k, the conductance R of the finish layer is given by the equation (84) ... [Pg.292]

Mote quantitative relationships of the CSD obtained from batch operations can be developed through formulation of a population balance. Using a population density defined in terms of the total crystallizer volume rather than on a specific basis (n = nU), the general population balance given by equation 42 can be modified in recognition of there being no feed or product streams ... [Pg.355]

Many different approaches to QSAR have been developed since Hansch s seminal work. These include both two-dimensional (2D) and 3D QSAR methods. The major differences among these methods can be analyzed from two viewpoints (1) the strucmral parameters that are used to characterize molecular identities and (2) the mathematical procedure that is employed to obtain the quantitative relationship between a biological activity and the structural parameters. [Pg.359]

The goal of a kinetic study is to establish the quantitative relationship between the concentration of reactants and catalysts and the rate of the reaction. Typically, such a study involves rate measurements at enough different concentrations of each reactant so that the kinetic order with respect to each reactant can be assessed. A complete investigation allows the reaction to be described by a rate law, which is an algebraic expression containing one or more rate constants as well as the concentrations of all reactants that are involved in the rate-determining step and steps prior to the rate-determining step. Each concentration has an exponent, which is the order of the reaction with respect to that component. The overall kinetic order of the reaction is the sum of all the exponents in the... [Pg.192]

Dispersion equations, typically the van Deemter equation (2), have been often applied to the TLC plate. Qualitatively, this use of dispersion equations derived for GC and LC can be useful, but any quantitative relationship between such equations and the actual thin layer plate are likely to be fraught with en or. In general, there will be the three similar dispersion terms representing the main sources of spot dispersion, namely, multipath dispersion, longitudinal diffusion and dispersion due to resistance to mass transfer between the two phases. [Pg.452]

Assuming the work of adhesion to be measurable, one must next ask if it can be related to practical adhesion. If so, it may be a useful predictor of adhesion. The prospect at first looks bleak. The perfect disjoining of phases contemplated by Eq. 1 almost never occurs, and it takes no account of the existence of an interphase , as discussed earlier. Nonetheless, modeling the complex real interphase as a true mathematical interface has led to quantitative relationships between mechanical quantities and the work of adhesion. For example, Cox [22] suggested a linear relationship between Wa and the interfacial shear strength, r, in a fiber-matrix composite as follows ... [Pg.10]

Dose-Response Cune A graphical representation of the quantitative relationship between the administered, applied, or internal dose of a chemical or agent, and a specific biological response to that chemical or agent. [Pg.317]

Of all the heteroaromatic compounds that have been examined qualitatively and quantitatively for covalent hydration, the pteridines constitute the largest series. Most of the quantitative relationships which were used in earlier discussions were first derived for the hydroxypteridines. Also most of the known examples of hydration in anions were found in this series. [Pg.25]

Composition of the liquid environment The ionic composition, arising from dissolved salts and gases, has a considerable influence on the performance of inhibitors. In near-neutral aqueous systems the presence of certain ions tends to oppose the action of inhibitors. Chlorides and sulphates are the most common examples of these aggressive ions, but other ions, e.g. halides, sulphides, nitrates, etc. exert similar effects. The concentration of inhibitor required for protection will depend on the concentrations of these aggressive ions. Laboratory tests " have given some quantitative relationships... [Pg.782]

Although there is no simple quantitative relationship between the stability of a carbocation intermediate and the rate of its formation, there is an intuitive relationship. It s generally true when comparing two similar reactions that the more stable intermediate forms faster than the less stable one. The situation is shown graphically in Figure 6.13, where the reaction energy profile in part (a) represents the typical situation rather than the profile in part (b). That is, the curves for two similar reactions don t cross one another. [Pg.197]

One of the most important parameters that defines the structure and stability of inorganic crystals is their stoichiometry - the quantitative relationship between the anions and the cations [134]. Oxygen and fluorine ions, O2 and F, have very similar ionic radii of 1.36 and 1.33 A, respectively. The steric similarity enables isomorphic substitution of oxygen and fluorine ions in the anionic sub-lattice as well as the combination of complex fluoride, oxyfluoride and some oxide compounds in the same system. On the other hand, tantalum or niobium, which are the central atoms in the fluoride and oxyfluoride complexes, have identical ionic radii equal to 0.66 A. Several other cations of transition metals are also sterically similar or even identical to tantalum and niobium, which allows for certain isomorphic substitutions in the cation sublattice. [Pg.59]

Chemistry is a quantitative science. This means that a chemist wishes to know more than the qualitative fact that a reaction occurs. He must answer questions beginning How much. . . The quantities may be expressed in grams, volumes, concentrations, percentage composition, or a host of other practical units. Ultimately, however, the understanding of chemistry requires that amounts be related quantitatively to balanced chemical reactions. The study of the quantitative relationships implied by a chemical reaction is called stoichiometry. [Pg.224]

We have all of this familiar experience to build upon, but it is all qualitative. We need a quantitative relationship. How much energy is carried by light The answer is simple in form, but not in concept. Light, too, comes in packages. Each package, called a photon, contains an amount of energy determined by the frequency. This statement is contained in the famous equation... [Pg.254]

A. Precipitation of sulphides. In order to understand fully the separations dependent upon the sulphide ion, we shall consider first the quantitative relationships involved in a saturated solution of hydrogen sulphide. The following equilibria are present ... [Pg.434]


See other pages where Quantitative. . . Relationship is mentioned: [Pg.214]    [Pg.798]    [Pg.264]    [Pg.2]    [Pg.116]    [Pg.232]    [Pg.2546]    [Pg.220]    [Pg.358]    [Pg.117]    [Pg.117]    [Pg.53]    [Pg.798]    [Pg.114]    [Pg.784]    [Pg.496]    [Pg.686]    [Pg.102]    [Pg.162]    [Pg.36]   
See also in sourсe #XX -- [ Pg.26 ]

See also in sourсe #XX -- [ Pg.563 ]




SEARCH



2D quantitative structure-activity relationships

3D quantitative structure-activity relationship

3D quantitative structure-metabolism relationship

Absorption, measurement quantitative relationship

Acidity quantitative relationships

Application of quantitative structure-activity relationships

Approaches to Three-Dimensional Quantitative Structure—Activity Relationships

Comparative quantitative structure-activity relationships

Comparative quantitative structure-activity relationships database development

Computational Modeling of Silicate Glasses A Quantitative Structure-Property Relationship Perspective

Copolymers quantitative structure-property relationships

D Quantitative Structure-Activity Relationship

Design and Quantitative Structure-Activity Relationships

Dielectrics, quantitative relationships

Drug design quantitative structure-activity relationships

Drugs quantitative structure-activity relationship

Expert systems quantitative structure-activity relationships

Fluorescence quantitative relationship

H-bonding Parameterization in Quantitative Structure-Activity Relationships and Drug Design

Lead optimization quantitative structure-activity relationships

Lipophilicity Fields An Enhancement of Three-Dimensional Quantitative Structure-Activity Relationships

Mechanism quantitative compositional relationships

Model modeling quantitative structure-activity relationship

Model quantitative structure-activity relationships

Molecular docking quantitative structure-activity relationship

Monte quantitative structure-activity relationships

P Values in Two-Dimensional Quantitative Structure-Activity Relationships

Phenols, quantitative structure-activity relationship

Properties of Metals and Metal Ions as Tools in Quantitative Structure-Activity Relationship (QSAR) Studies

Quantitative Approaches to Structure-Activity Relationships

Quantitative Relationships Involving Carboxylic Acids

Quantitative Structure - Activity Relationships (QSAR) for Bioconcentration

Quantitative Structure Activity Relationship screening

Quantitative Structure Activity Relationships , common

Quantitative Structure Permeability Relationship models

Quantitative Structure- Activity Relationships equation

Quantitative Structure- Activity Relationships studies, initial

Quantitative Structure-Activity Relationships

Quantitative Structure-Activity Relationships QSAR)

Quantitative Structure-Property Relationship Analysis

Quantitative Structure-Property Relationships

Quantitative Structure-Property Relationships QSPR)

Quantitative Structure-Property Relationships and Statistics

Quantitative Structure-Retention Relationships in Reversed-phase Liquid Chromatography

Quantitative cationic activity relationships

Quantitative cationic activity relationships QCARs)

Quantitative property-activity relationships

Quantitative property-solubility relationship

Quantitative property-water solubility relationships

Quantitative reactivity-activity relationships

Quantitative reactivity-activity relationships QRAR)

Quantitative relationship between

Quantitative relationships between structure

Quantitative relationships between structure complexation

Quantitative relationships between structure empirical correlations

Quantitative relationships between structure extraction

Quantitative retention-activity relationship

Quantitative similarity-activity relationship method

Quantitative structur-activity relationships

Quantitative structure - function relationships

Quantitative structure - property relationship models

Quantitative structure activity relationship QSAR) models

Quantitative structure activity relationship methods

Quantitative structure behavior relationship

Quantitative structure observable relationship

Quantitative structure permeability relationships

Quantitative structure retention relationships

Quantitative structure-activity correlation/relationship

Quantitative structure-activity relationship Hansch analysis

Quantitative structure-activity relationship Hansch equations

Quantitative structure-activity relationship QSAR) methodology

Quantitative structure-activity relationship QSAR) tool

Quantitative structure-activity relationship Taft steric parameter

Quantitative structure-activity relationship analysis

Quantitative structure-activity relationship applications

Quantitative structure-activity relationship calculation

Quantitative structure-activity relationship chemical reactivity

Quantitative structure-activity relationship chirality

Quantitative structure-activity relationship chromatography

Quantitative structure-activity relationship development

Quantitative structure-activity relationship electronic effects

Quantitative structure-activity relationship estrogen receptor binding affinity

Quantitative structure-activity relationship geometry optimization

Quantitative structure-activity relationship hierarchical

Quantitative structure-activity relationship hierarchical QSAR

Quantitative structure-activity relationship history

Quantitative structure-activity relationship indices

Quantitative structure-activity relationship ligands

Quantitative structure-activity relationship limitations

Quantitative structure-activity relationship linear regression methods

Quantitative structure-activity relationship lipophilicity

Quantitative structure-activity relationship machine learning

Quantitative structure-activity relationship machine learning methods

Quantitative structure-activity relationship modeling

Quantitative structure-activity relationship molar refractivity

Quantitative structure-activity relationship molecular descriptors

Quantitative structure-activity relationship molecular modeling

Quantitative structure-activity relationship nonlinear

Quantitative structure-activity relationship partial least square method

Quantitative structure-activity relationship partition constants

Quantitative structure-activity relationship pharmacological activities

Quantitative structure-activity relationship physical organic models

Quantitative structure-activity relationship physicochemical, environmental

Quantitative structure-activity relationship prediction

Quantitative structure-activity relationship properties

Quantitative structure-activity relationship quantum chemical descriptors

Quantitative structure-activity relationship regression constant

Quantitative structure-activity relationship safety modeling

Quantitative structure-activity relationship similarity principle

Quantitative structure-activity relationship stages

Quantitative structure-activity relationship standard deviation

Quantitative structure-activity relationship statistical methods

Quantitative structure-activity relationship steric effects

Quantitative structure-activity relationship structural descriptors

Quantitative structure-activity relationship techniques

Quantitative structure-activity relationship three-dimensional descriptors

Quantitative structure-activity relationship topological indices

Quantitative structure-activity relationship validation

Quantitative structure-activity relationship vapor pressure

Quantitative structure-activity relationships (QSARs) for hypoxic cell radiosensitizers

Quantitative structure-activity relationships , applied

Quantitative structure-activity relationships 3-D QSAR)

Quantitative structure-activity relationships OECD principles

Quantitative structure-activity relationships QSARs) models

Quantitative structure-activity relationships bioavailability

Quantitative structure-activity relationships combinatorial libraries

Quantitative structure-activity relationships correlation weights

Quantitative structure-activity relationships density functional theory

Quantitative structure-activity relationships descriptors

Quantitative structure-activity relationships drug design optimization

Quantitative structure-activity relationships experimental data

Quantitative structure-activity relationships experimental design

Quantitative structure-activity relationships experimental results

Quantitative structure-activity relationships generating QSARs

Quantitative structure-activity relationships global models

Quantitative structure-activity relationships heterocycles

Quantitative structure-activity relationships hydrophobicity descriptor

Quantitative structure-activity relationships inductive analysis

Quantitative structure-activity relationships inverse QSAR

Quantitative structure-activity relationships lead compounds

Quantitative structure-activity relationships lipophilicity descriptor

Quantitative structure-activity relationships local models

Quantitative structure-activity relationships mechanistic interpretations

Quantitative structure-activity relationships metal ions

Quantitative structure-activity relationships methodology

Quantitative structure-activity relationships model building

Quantitative structure-activity relationships molecular/quantum mechanics computer

Quantitative structure-activity relationships overview

Quantitative structure-activity relationships potentially applicable

Quantitative structure-activity relationships predicting with QSARs

Quantitative structure-activity relationships predictive models

Quantitative structure-activity relationships quantum-mechanical theory

Quantitative structure-activity relationships refinement

Quantitative structure-activity relationships selective drug design

Quantitative structure-activity relationships three-dimensional

Quantitative structure-activity relationships validity assessments

Quantitative structure-activity relationships —See

Quantitative structure-analysis relationships

Quantitative structure-analysis relationships QSARs)

Quantitative structure-bioactivity relationships

Quantitative structure-bioactivity relationships QSAR)

Quantitative structure-chemical property relationships

Quantitative structure-chemical reactivity relationships

Quantitative structure-degradation relationships

Quantitative structure-enantioselectivity relationships

Quantitative structure-metabolism relationships

Quantitative structure-mobility relationships

Quantitative structure-pharmacokinetic relationships

Quantitative structure-pharmacokinetics relationships

Quantitative structure-physical property relationships

Quantitative structure-property relationship pharmacological activity

Quantitative structure-property relationships glass transition temperature

Quantitative structure-property relationships interactions

Quantitative structure-property relationships molecular weight

Quantitative structure-retention relationships , predicting

Quantitative structure-retention relationships QSRR)

Quantitative structure-selectivity relationship

Quantitative structure-selectivity relationship QSAR)

Quantitative structure-solubility relationship

Quantitative structure-toxicity relationships

Quantitative structure-toxicity relationships QSTR)

Quantitative structure-water solubility relationships

Quantitative structure—activity relationship mechanism

Quantitative-structure-activity relationships QSARs)

Quantitative-structure-property relationships QSPRs)

Quantum quantitative structure activity relationships equation

Some Quantitative Relationships of Dielectrics

Stoichiometry Description of the quantitative relationships among elements

Structure-property quantitative relationship SPQR)

Structure-property quantitative relationships nature

Surface analysis quantitative relationships

Test of Quantitative Relationships

Theoretical and Practical Aspects of Three-Dimensional Quantitative Structure-Activity Relationships

Three-dimensional quantitative structure activity relationships conformation

Three-dimensional quantitative structure activity relationships superposition

Three-dimensional quantitative structure-activity relationship drug design

Three-dimensional quantitative structure-activity relationship example

Three-dimensional quantitative structure-activity relationship methods

Three-dimensional quantitative structure-activity relationship models

Why look for quantitative relationships

© 2024 chempedia.info