Abstract
A computational neural network method was used for the prediction of stability constants of simple crown ether complexes. The essence of the method lies in the ability of a computer neural network to recognize the structure-property relationships in these host-guest systems. Testing of the computational method has demonstrated that stability constants of alkali metal cation (Na+, K+, Cs+)-crown ether complexes in methanol at 25 °C can be predicted with an average error of ±0.3 log K units based on the chemical structure of the crown ethers alone. The computer model was then used for the preliminary analysis of trends in the stabilities of the above complexes.
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Gakh, A.A., Sumpter, B.G., Noid, D.W. et al. Prediction of Complexation Properties of Crown Ethers Using Computational Neural Networks. Journal of Inclusion Phenomena 27, 201–213 (1997). https://doi.org/10.1023/A:1007928814162
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DOI: https://doi.org/10.1023/A:1007928814162