Molecular Models of Symmetry-Protected Quantum Batteries: Electronic Structure and Exciton Dynamics
Bibliographic record
Abstract
Quantum batteries, which store energy in long-lived excited states, have been theoretically predicted to possess several advantages over conventional classical batteries. While quantum battery research has been predominantly theoretical, preliminary experimental demonstrations have emerged. To advance the field beyond abstract theoretical models, we propose in this work molecular models that bring quantum batteries closer to physical realization. These models consist of anthracene-based chromophores in a hexagonal arrangement. Time-dependent density functional theory calculations confirm the existence of the previously predicted dark states in these models and yield monomeric excitation energies and couplings between the monomeric excited states, which are needed for parametrizing the Frenkel exciton Hamiltonians. Following the parametrizations, exciton dynamics simulations are carried out for all models starting from their respective dark states, under both symmetry-preserving (storage) and symmetry-breaking (discharge) conditions. Both the magnitude and sign of the on-site energy gaps are found to influence the exciton discharge rates, exhibiting a turnover as this gap is varied from large negative to large positive values. Notably, the rate exhibits a maximum when the energy gap is negative, and the turnover behavior is asymmetric about this point, with higher rates for negative gaps. Marcus theory provides a qualitative framework for explaining the trends in the simulated exciton discharge rates as both the sign and magnitude of the energy gap are varied. Overall, this work establishes a computational approach for designing molecular models of quantum batteries, sheds light on the nature of the dark states for exciton storage, and establishes design principles for controlling exciton transfer rates.
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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 | 0.000 |
| 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".