1998
DOI: 10.1002/(sici)1099-0682(199806)1998:6<693::aid-ejic693>3.0.co;2-m
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How to Derive Force Field Parameters by Genetic Algorithms: Modellingtripod-Mo(CO)3 Compounds as an Example

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Cited by 41 publications

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“…Since, with the molecules analysed, the interactions between their organic parts dominate it is expected that the force constants derived for the ‘inorganic’ part of the molecules by GA‐optimisation will adapt to the major forces exerted by their organic part such that the scale of relative energies as calculated by the force field as a whole will be on scale with the observations. These expectations have been born out by similar analyses in related cases 14−16. If the energies are on scale with the observations it must be possible to calculate conformationally relevant energies and to compare these with experimental values wherever available.…”
Section: Results
mentioning
confidence: 79%
“…It appears that the approach taken in deriving a force field model is a very promising one. The optimisation of the force field parameters on the basis of as many solid state structures as available for a class of compound had already been shown to lead to models of high predictive power 14−16. The case studied here is the most complicated one of the ones analysed by this method so far and at the same time the one for which pathways and energies have been experimentally determined to the maximum possible extent 8.…”
Section: Results
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confidence: 97%
“…If a large number of a family of crystal structures is known the question of whether these structures are by and large uninfluenced by crystal forces can be addressed by statistical analysis. In the first report on the use of Genetic Algorithms in the refinement of force field parameters which dealt with modelling the behaviour of tripod ‐Mo(CO 3 ) compounds14 statistical analysis by a variety of methods including Neural Network analysis had shown that these premises are met in this case 11. Refinement of the force field parameters on the basis of solid state structures has been highly successful in this case 14.…”
Section: Results
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confidence: 99%
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