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Combination of Models

The oxidation of cobalt metal to inactive cobalt oxide by product water has long been postulated to be a major cause of deactivation of supported cobalt FTS catalysts.6 10 Recent work has shown that the oxidation of cobalt metal to the inactive cobalt oxide phase can be prevented by the correct tailoring of the ratio Ph2cJPh2 and the cobalt crystallite size.11 Using a combination of model systems, industrial catalyst, and thermodynamic calculations, it was concluded that Co crystallites > 6 nm will not undergo any oxidation during realistic FTS, i.e., Pi[,()/I)i,2 = 1-1.5.11-14 Deactivation may also result from the formation of inactive cobalt support compounds (e.g., aluminate). Cobalt aluminate formation, which likely proceeds via the reaction of CoO with the support, is thermodynamically favorable but kinetically restricted under typical FTS conditions.6... [Pg.51]

We therefore conclude that, for a combination of model, numerical and conceptual reasons the OHAO basis is well-adapted to a theory of valence. The hybrid orbital basis (for simple molecules) has a distinctive symmetry property it carries a permutation representation of the molecular symmetry group the equivalent orbitals are always sent into each other, never into linear combinations of each other. This simple fact enables the hybrid orbital basis to be studied in a way which is physically more transparent than the conventional AO basis. [Pg.64]

A more practical approach is the hybrid approach where a combination of models (where applicable) and experiments (where models are not applicable) are employed. For hybrid approaches, development of a systematic method of solution based on a decomposition of the overall design problem into a hierarchy of tasks and sub-tasks is necessary. [Pg.18]

Both of these models show contributions from the viscosity and the elasticity, and so both these models show viscoelastic behaviour. You can visualise a more complex combination of models possessing more complex constitutive equations and thus able to describe more complex rheological profiles. [Pg.103]

A probabilistic model will typically require distributions for multiple inputs. Therefore, it is necessary to consider the joint distribution of multiple variables as well as the individual distributions, i.e., we must address possible dependencies among variables. At least, we want to avoid combinations of model inputs that are unreasonable on scientific grounds, such as the basal metabolic rate of a hummingbird combined with the body weight of a duck. [Pg.32]

QM/MM boundary through space in such a way that the sterically bulky groups fall on the MM side and the interesting part of the molecule falls on the QM side. Finally, to avoid the question of how to deal with a cut bond, one may assume that the electronic structure of the QM region will be of similar quality with either the non-polar, bulky group as a cap, or with simply hydrogen atoms as caps. With such a philosophy, the energy of the system as a whole may be expressed as a linear combination of model compounds of different size and at different levels of theory. In simplest form... [Pg.468]

Receptor models are widely used tools for apportioning concentrations of pollutants to different sources. They can be factor analytical methods (PMF, PCA, UNMIX, etc.) or chemical mass balance (CMB). On the one hand, these methods revealed to be very valuable to identify the main sources/categories of PM pollution (road traffic, secondary particles, fuel oil combustion, sea salt, etc.) but on the other hand they experienced difficulties in separating the contributions of collinear sources such as mineral dust (natural resuspension) and road dust (anthropogenic) or co-variant sources such as vehicle exhaust and road dust [34, 44, 45, 49, 55, 58, 110-113]). Significant improvements were made with the use of combination of models or constrained models such as the Multilinear Engine (ME-2). [Pg.178]

The distribution of stressors in the environment can be described using measurements, models, or a combination of the two. If stressors have already been released, direct measurements of environmental media or a combination of modeling and measurement is preferred. However, a modeling approach may be necessary if the assessment is intended to predict future scenarios or if measurements are not possible or practicable. [Pg.509]

Obtaining a good quality QSAR model depends heavily on many factors in the approach, particularly on the quality of biological data, descriptor selection, and statistical methods (see Chapter 19 for more details). Given the fact that any QSAR approach has strengths and weaknesses, the careful selection of a specific model, or a combination of models, also needs to be emphasized, and is often specific to the particular application in question. [Pg.293]

All four models influence each other considerably, as shown in Fig. 17.1. It depends on the question asked which model or which combination of models is needed to answer a specific question. The models can be further differentiated with regard to the complexity with which they reflect the biological system (from empirical to fully mechanistic models), which are described in detail in the following sections. [Pg.449]

CD spectroscopy is not limited to the study of small molecules, and has become extremely important in the characterization of biomolecules. The secondary structure of proteins can be characterized through studies of the CD associated with the amide chromophores. Using a combination of models and calibration spectra, it is possible to deduce the relative contributions to the overall secondary structure made by a-helix, antiparallel B-sheet, B-turn, and random coil portions of the polypeptide [11]. With the increasing use being made of such agents in the pharmaceutical industry, it... [Pg.11]

In our studies, solvent effects were included in three different ways (i) by explicit inclusion of water molecules, (ii) by using a continuum solvation model and (iii) by the combination of models (i) and (ii). The first approach is called microsolvation,... [Pg.323]

Note Values are percent composition of different Mn oxidation states. Standard deviations (in parentheses) are for all combinations of models with the indicated oxidation states. For reduced samples, the Mn(II)-Mn(III) and Mn(II)-Mn(IV) models cannot be distinguished the true percent of Mn(II) is likely between the two extremes. [Pg.247]

Deciding which model is most appropriate has to do with selection however, a combination of models that capture the key elements of nursing in a disaster situation may be adapted and applied. Empirical investigation is then required to determine if the model matches reality. When selecting appropriate models or grand theories it is possible to select any theory and apply it to... [Pg.583]

The coefficient of thermal expansion obtained at 300 K with a 5.40 A cutoff is 0.74 X 10 K Since the corresponding value at 1000 K is 1.6 x 10" K" it is seen that the present model of copper does reproduce the experimentally-observed increase of a with temperature [45]. To our knowledge, this is the first simulation of copper that correctly predicts the qualitative variation of a with temperature. This provides important support for the combination of model and simulation conditions that we have used in this work. [Pg.729]

To improve the performance of adaptive optimization, it may be useful to combine specific features of the various methods. For example, the combination of model adaptation (which ensures fast convergence for the first few iterations and detects changes in the active set) with direct-input adaptation (which provides the necessary gradients in the neighborhood of the plant optimum) has been demonstrated in [24]. Another interesting combination would be to use a modifier-adaptation approach at one time scale and perform model adaptation at a slower rate, thus giving rise to a two-time-scale adaptation strategy. [Pg.15]

Finally, it should be emphasized that the successful use of a bi-Langmuir isotherm model (as of any other combination of models that multiplies the number of model parameters) to account for a set of experimental adsorption data requires that these data are acquired in a wide concentration range [55]. This is even more... [Pg.92]


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