Parameter-free structure-property correlation via progressive reaction posets for substituted benzenes

Area of Science:

• Computational chemistry
• Chemical informatics
• Physical organic chemistry

Background:

• Progressive reaction networks in chemistry can be represented as partially ordered sets (posets).
• The direction of chemical reactions defines the partial ordering of molecular species within these networks.
• Investigating correlations between similarly ordered properties is a natural extension of this concept.

Purpose of the Study:

• To investigate the correlation between the ordering of molecular properties in substituted benzenes.
• To explore the predictive power of reaction posets for molecular properties.
• To develop a parameter-free method for predicting chemical properties.

Main Methods:

• Representing chemical reaction networks as partially ordered sets (posets).
• Analyzing over 30 properties for methyl and chloro-substituted benzenes.
• Applying posetic correlation analysis to identify relationships between properties.
• Utilizing reaction posets for interpolative, parameter-free property prediction.

Main Results:

• A favorable posetic correlation was demonstrated for the studied substituted benzenes.
• The reaction poset approach allows for simple, parameter-free prediction of certain molecular properties.
• Identified numerical indicators for assessing the quality of predictive models.

Conclusions:

• Reaction networks as posets provide a valuable framework for understanding chemical systems.
• The posetic correlation method offers a straightforward and effective way to predict molecular properties.
• This approach is deemed reasonable and shows potential for computational chemistry applications.