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Published on: September 18, 2016
The "anthracene problem": closed-form conjugated-circuit models of ring currents in linear polyacenes
Patrick W Fowler1, Wendy Myrvold
1Department of Chemistry, University of Sheffield, Sheffield, UK.
Conjugated-circuit models for induced π ring currents show perimeter currents are strongest in central rings for linear polyacenes. However, these models often overestimate current increases compared to advanced computational methods.
Area of Science:
- Theoretical Chemistry
- Computational Chemistry
- Quantum Chemistry
Background:
- Induced π ring currents are crucial for understanding aromaticity and electronic properties of molecules.
- Existing conjugated-circuit models vary in their inclusion of circuits and weighting schemes.
- The choice of circuits in these models can be represented using graph theory.
Purpose of the Study:
- To analyze and compare different conjugated-circuit models for induced π ring currents.
- To derive and apply closed-form solutions for linear polyacenes.
- To assess the predictive accuracy of these models against ab initio calculations.
Main Methods:
- Development of a graph-matching approach for selecting circuits in π systems.
- Derivation of closed-form solutions for conjugated-circuit models applied to linear polyacenes.
- Comparison of model predictions with ipsocentric ab initio, pseudo-π, and Hückel-London methods.
Main Results:
- All analyzed models predict the most intense perimeter current in the central rings of linear polyacenes.
- The models provide simple closed-form solutions for these systems.
- A tendency for models to overestimate the rate of increase in central ring current with system size (N) was observed.
Conclusions:
- Conjugated-circuit models offer valuable insights into induced π ring currents, particularly regarding current distribution.
- Despite variations in assumptions, models consistently identify central rings as having the strongest perimeter currents.
- Further refinement is needed to match the accuracy of advanced molecular orbital treatments for quantitative predictions.
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