Computational studies prediction

Computational studies predict a preference for the endo TS.16 There have been several computational efforts to dissect the various factors that contribute to the differences between the exo and endo TS.17 These generally are in agreement with the experimental preference for the endo TS, but there is no consensus on the dominant factors in this preference.18... 

Substituents at the allene in general and methyl groups in particular favor /3-addition of radicals, which leads to the formation of allylic and therefore stabilized intermediates. Results from computational studies predict that CH3 addition to Cp of... 

Computational studies predict that the geometry (chair, half-chair, boat, etc) depends on the nature of Ri, R2, and M. Theory also predicts that Z-enolates prefer a closed chair, but that -enolates may prefer a boat [54-56]. For an empirical rule for predicting aldol topicity, see ref. [57]. For an investigation into the effect of metal and solvent on transition structures, see ref. [58]. 

Computational studies predict that application of anchoring moieties with higher electron-accepting properties should result in DSSC performance higher than that of carboxylic-anchored MPs of the same structure [25]. This prediction found its experimental confirmation [26-28]. 

HMP, and phenol would be left in a cook even as condensation advances. Several computer studies predicting the buildup of resin intermediates have been made. Table 4 highlights some major differences between resoles and novolaks. 

A computational study" predicts that at high pressures, O2 forms an insulating spiral-chain O4 polymer stracture. Figure 25-6 displays (a) the formation of in-creased-valence stracture (2) for the O2 dimer from the O2 monomers of (1) and the O2 dimer Lewis structure (3) (b) types of increased-valence structures for Og ((4) and (5)) and spiral chain O4 polymers ((6), (7) and (8)). 

Polymers can be crystalline, but may not be easy to crystallize. Computational studies can be used to predict whether a polymer is likely to crystallize readily. One reason polymers fail to crystallize is that there may be many conformers with similar energies and thus little thermodynamic driving force toward an ordered conformation. Calculations of possible conformations of a short oligomer can be used to determine the difference in energy between the most stable conformer and other low-energy conformers. 

When using dimensional analysis in computing or predicting performance based on tests performed on smaller-scale units, it is not physically possible to keep all parameters constant. The variation of the final results will depend on the scale-up factor and the difference in the fluid medium. It is important in any type of dimensionless study to understand the limit of the parameters and that the geometrical scale-up of similar parameters must remain constant. 

In one of the very first realistic computational studies of PECD effects, performed for the amino acid alanine [51], it was noted that different results were obtained at each of three fixed geometries corresponding to low lying conformations identified in previous structure investigations [69-71]. A later combined experimental-theoretical study of PECD in 3-hydroxytetrahydrofuran [61] further looked at the influence of presumed conformation and concluded that while the predicted cross-section, a, and p parameters were mildly affected by conformation, the chiral parameters were much more strongly... 

J.R.M. Smits, W.J. Meissen, G.J. Daalmans and G. Kateman, Using molecular representations in combination with neural networks. A case study prediction of the HPLC retention index. Computers Chem., 18 (1994) 157-172. 

As it has been shown in this chapter knowing the concentrations of chemicals in the environment is a key aspect in order to carry out meaningful hazard and risk assessment studies. Predicting concentrations of chemicals can serve as a quick and robust way to produce an acceptable screening level assessment however if further precision is desired, the complexity of real environmental scenarios can make it a cumbersome and unaffordable task. Models improvement requires not only refining their computation algorithms but also and more important, implementing new inputs and processes in order to better describe real scenarios. 

Various secondary sources of safety data are now listing this as an explosive. I can find no primaiy source for this classification, which seems very improbable. Simple minded use of many computational hazard prediction procedures would show thermodynamically that this compound, like most lower amines, could hypothetically convert to alkane, ammonia and nitrogen with sufficient energy (about 3 kJ/g) to count as an explosion hazard. This reaction is not known to happen. (Simple minded thermodynamicists would rate this book, or computer, and its reader as a severe hazard in an air environment.) Like other bases, iminobispropylamine certainly sensitises many nitro-explosives to detonation. It is used experimentally to study the effect, which may have found technical exploitation and, garbled, could have led to description of the amine as itself an explosive. 

After the integration of this synthetic method into a fully compatible protocol, the positions for electronic changes with various substituents were rationally predicted through the deliberation of computational studies the Ri position of the... 

Quantitative assessment of the electrophilic character of various types of phosphenium ions has been attempted using computational studies on hydride and halide exchange reactions, and the results attribute to 1,3,2-diazaphospholenium ions a lower electrophilicity (and thus higher stability) than other types of phosphenium ions [20, 66], The gain in stability due to aromatic -delocalization is predicted to be somewhat larger than inductive stabilization resulting from exhaustive A-alkylation of the parent diaminophosphenium ion, [P(NH2)2]+. 

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