Distinguishing Aromaticity from Antiaromaticity with Information-Theoretic and Energetic Information Quantities and Their Links to Molecular Properties
Bibliographic record
Abstract
Aromaticity and antiaromaticity are foundational concepts in chemistry, yet their precise classification, differentiation, and quantification remain the subject of ongoing debate in the literature. In this work, we systematically investigate aromaticity and antiaromaticity patterns for a series of substituted fulvene derivatives in both lowest singlet and triplet states and then cross-correlate their numerical results from the information-theoretic approach (ITA), energetic information, topological analysis, and molecular properties (e.g., atomic polarizability, C 6 dispersion coefficient, Hirshfeld charge, and electron density) with different aromaticity indexes (e.g., NICS(0), NICS(1), FLU, HOMA, and HOMER). Our cross-correlation results reveal that aromatic and antiaromatic systems exhibit completely opposite patterns in each of the spin states. In addition to ITA quantities previously identified that can be employed to distinguish aromaticity from antiaromaticity, newly introduced energetic information, and the topological analysis of ITA quantities also verify this regularity. Notably, the same opposite behavior between aromaticity and antiaromaticity is also observed for atomic polarizability, C 6 dispersion coefficient, Hirshfeld charge, and electron density, uncovering the intrinsic connections between electron delocalization and molecular response properties. Furthermore, the four properties demonstrate strong linear correlations with the ITA and energetic information quantities. This study should have provided new qualitative and quantitative perspectives and insights into understanding aromatic and antiaromatic propensities of molecular systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".