Clark T, Rauhut G, Breindl A (1995)
Publication Status: Published
Publication Type: Journal article
Publication year: 1995
Publisher: Springer Verlag (Germany)
Book Volume: 1
Pages Range: 22-35
Journal Issue: 1
A back-propagation artificial neural net has been trained to estimate C-13 chemical shifts from the results of AM1 and PM3 semiempirical MO calculations. The input descriptors include the atom-centered monopole, dipole and quadrupole moments derived from the natural atomic orbital/point charge (NAO/PC) model, the four highest bond orders to the carbon atom being considered and the elements to which these bonds are made. The resulting net estimates the chemical shifts of a test set of 156 chemical shifts with a standard deviation of less than 7 ppm from the experimental values for AMI and slightly more for PM3.
APA:
Clark, T., Rauhut, G., & Breindl, A. (1995). A combined semiempirical MO neural net technique for estimating C-13 chemical shifts. Journal of Molecular Modeling, 1(1), 22-35. https://dx.doi.org/10.1007/s008940050004
MLA:
Clark, Timothy, Guntram Rauhut, and Andreas Breindl. "A combined semiempirical MO neural net technique for estimating C-13 chemical shifts." Journal of Molecular Modeling 1.1 (1995): 22-35.
BibTeX: Download