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Quantitative structure–conditions–property relationship studies. Neural network modelling of the acid hydrolysis of esters

Nataliya Markovna Halberstam 1
Nataliya Markovna Halberstam
,  , 
Vladimir Alexandrovich Palyulin 1
Vladimir Alexandrovich Palyulin
, 
Nikolai Serafimovich Zefirov 1
Nikolai Serafimovich Zefirov
10.1070/MC2002v012n05ABEH001620
Published 2002-11-15
Communication , Volume 12, Issue 5, 185-186
16
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Halberstam N. M. et al. Quantitative structure–conditions–property relationship studies. Neural network modelling of the acid hydrolysis of esters // Mendeleev Communications. 2002. Vol. 12. No. 5. pp. 185-186.
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Halberstam N. M., Baskin I. I., Palyulin V. A., Zefirov N. S. Quantitative structure–conditions–property relationship studies. Neural network modelling of the acid hydrolysis of esters // Mendeleev Communications. 2002. Vol. 12. No. 5. pp. 185-186.
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TY - JOUR
DO - 10.1070/MC2002v012n05ABEH001620
UR - https://mendcomm.colab.ws/publications/10.1070/MC2002v012n05ABEH001620
TI - Quantitative structure–conditions–property relationship studies. Neural network modelling of the acid hydrolysis of esters
T2 - Mendeleev Communications
AU - Halberstam, Nataliya Markovna
AU - Baskin, Igor Iosifovich
AU - Palyulin, Vladimir Alexandrovich
AU - Zefirov, Nikolai Serafimovich
PY - 2002
DA - 2002/11/15
PB - Mendeleev Communications
SP - 185-186
IS - 5
VL - 12
ER -
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@article{2002_Halberstam,
author = {Nataliya Markovna Halberstam and Igor Iosifovich Baskin and Vladimir Alexandrovich Palyulin and Nikolai Serafimovich Zefirov},
title = {Quantitative structure–conditions–property relationship studies. Neural network modelling of the acid hydrolysis of esters},
journal = {Mendeleev Communications},
year = {2002},
volume = {12},
publisher = {Mendeleev Communications},
month = {Nov},
url = {https://mendcomm.colab.ws/publications/10.1070/MC2002v012n05ABEH001620},
number = {5},
pages = {185--186},
doi = {10.1070/MC2002v012n05ABEH001620}
}
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Halberstam, Nataliya Markovna, et al. “Quantitative structure–conditions–property relationship studies. Neural network modelling of the acid hydrolysis of esters.” Mendeleev Communications, vol. 12, no. 5, Nov. 2002, pp. 185-186. https://mendcomm.colab.ws/publications/10.1070/MC2002v012n05ABEH001620.

Abstract

A new approach to the quantitative description of organic compound reactivity based on the neural network modelling of structure– reaction conditions–rate constant relationships was demonstrated for the acid hydrolysis of esters.

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