Magnetic Coupling in Non-Kekulé Diradical Hydrocarbons via Multiconfigurational Pair-Density Functional Theory
Bibliographic record
Abstract
Understanding the behavior of electron spins in nanomaterials is crucial for the advancement of quantum technologies. However, studying single spins presents significant challenges both experimentally and theoretically, as radicals are often unstable under experimental conditions, and sophisticated quantum mechanical approaches with extremely high computational demands, such as CASPT2 and NEVPT2, are often required. This has resulted in a limited understanding of many spin processes at the nanoscale, as emphasized by recent cutting-edge scanning probe microscopy experiments exploring conjugated hydrocarbons known as nanographenes. Some of these systems have diradical character, with two unpaired π-electrons in a non-Kekulé electronic structure that yields magnetic and electric properties not seen in classical hydrocarbons. In this work, we use a recently developed (range-separated) multiconfigurational on-top pair density functional theory (MC-ctPDFT or MC-sr-ctPDFT) method to study the magnetic coupling in both small model non-Kekulé diradicals and models of nanographenes. We show that standard density functional theory fails to correctly describe those molecules whose ground state is a singlet instead of a triplet, sometimes considered a violation of Hund's rule. Our method accounts for both static and dynamic correlations and compares well with common approaches such as NEVPT2 and CASPT2, but exhibits a much lower asymptotic computational cost. By expansion of the method to encompass more complex molecular environments, it could be further utilized to investigate surface interactions and catalytic processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".