Method for adopting quantitative structure-activity relation model to predict reaction rate constant of chlorine free radical of organic chemicals

A technology of reaction rate constants and organic chemicals, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as poor interpretation of model mechanism, narrow application domain, and neglect

Active Publication Date: 2018-01-09
DALIAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

But it is only applicable to a single H extraction reaction pathway, ignoring the Cl addition reaction pathway
[0006] In general, all existing Cl models have the problem o

Method used

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  • Method for adopting quantitative structure-activity relation model to predict reaction rate constant of chlorine free radical of organic chemicals
  • Method for adopting quantitative structure-activity relation model to predict reaction rate constant of chlorine free radical of organic chemicals
  • Method for adopting quantitative structure-activity relation model to predict reaction rate constant of chlorine free radical of organic chemicals

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Embodiment 1

[0050] A method for predicting the reaction rate constant of chlorine radicals of organic chemicals, comprising the steps of:

[0051] First, data collection: the room temperature (298K) k of organic compounds is collected from a large number of literature and books Cl value, if an organic compound contains k from more than one source Cl value, take the average value. Finally, the k of 506 organic compounds with a temperature of 298K are obtained Cl Value, organic compounds are alkanes, alkenes, alkynes, organic alcohols, ethers, ketones, aldehydes, acids, esters, thio organic compounds, acyl organic compounds, organic amines, silicones, polycyclic aromatic hydrocarbons and their substitutes, heterocyclic compounds And its derivatives, nitro substitutes or halogenated organic compounds.

[0052] Secondly, electronic structure optimization and data set grouping: In the quantum chemical calculation software Gaussian09, the structures of all organic chemicals in the data set w...

Embodiment 2

[0063] Given an organic compound 6-nitro-m-cresol, to predict its logk Cl value. First, based on the structural information of 6-nitro-m-cresol, the electronic structure was optimized using the Gaussian09 software package. E is then calculated based on the above results HOMO ,#X:C,qH ave , qC ave , (E LUMO -E HOMO ) 2 , #nonHatom: C, S, s - max , #H values ​​are -0.261,0,0.168,-0.091,0.022,1.571,3.412,0.562,7 respectively. Calculation of d for organic chemicals using AMBIT Discovery software i The value is 0.486 (Cl The predicted value is -10.716, the experimental value is -10.712, and the residual value is 0.0037. The predicted value is in good agreement with the experimental value.

Embodiment 3

[0065] Given an organic compound crotonaldehyde, to predict its logk Cl value. First, based on the structural information of crotonaldehyde, the electronic structure was optimized using the Gaussian09 software package. E is then calculated based on the above results HOMO ,#X:C,qH ave , qC ave , (E LUMO -E HOMO ) 2 , #nonHatom: C, S, s - max , #H values ​​are -0.264, 0, 0.142, -0.139, 0.038, 1.25, 2.743, 1.184, 6 respectively. Calculation of d for organic chemicals using AMBIT Discovery software i The value is 0.388 (Cl The predicted value is -9.753, the experimental value is -9.569, and the residual value is 0.1837. The predicted value is in good agreement with the experimental value.

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Abstract

The invention discloses a method for adopting a quantitative structure-activity relation model to predict a reaction rate constant of chlorine free radical of organic chemicals. According to the method, a quantum chemistry descriptor with structural characters is figured out only by means of basic molecular structure information of the organic chemicals, and by adopting a constructed QSAR prediction model, a kCl value of the organic chemicals can be predicted quickly and efficiently. The method follows a guide rule issued for the construction and verification of a QSAR model by the Organization For Economic Co-Operation And Development (OECD). According to the method, by adopting a genetic algorithm-multiple linear stepwise regression analysis combination use method (GA-MLR) and a supportvector machine-multiple linear stepwise regression analysis combination use method (SVM-MLR), the transparency degree is high and more convenience is provided for application; since quantum chemistrydescriptors are adopted in all GA-MLR models, the physical meaning of the descriptors is clear; the method has a specific application domain, and is applicable to abundant organic varieties, excellentin goodness of fit, robustness and prediction capability, easy to program and capable of supplying important data support to environmental risk evaluation and management of the organic chemicals.

Description

technical field [0001] The invention belongs to the field of ecological risk assessment testing strategies, and relates to a method for predicting the reaction rate constant of chlorine free radicals of organic chemicals by using a quantitative structure-activity relationship model. Background technique [0002] Chlorine radical reaction rate constant of organic chemicals in the atmosphere (k Cl ) is an important parameter for assessing the atmospheric persistence of chemicals, and is of great significance for characterizing the ecological environmental risk and environmental fate of chemicals. Atmospheric chlorine radical (·Cl) has strong chemical reactivity to organic pollutants, and its reaction rate constant with most organic pollutants is one to more orders of magnitude higher than that of the most important free radical in the atmosphere (hydroxyl radical) . However, since it has been considered in the past that ·Cl mainly exists in the ocean and coastal areas, and i...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 谢宏彬张勇虔李雪花陈景文
Owner DALIAN UNIV OF TECH
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