Monte Carlo Simulation of Exciton Bimolecular Annihilation Dynamics in Supramolecular Semiconductor Architectures
Bibliographic record
Abstract
We present a simulation of exciton dynamics in supramolecular assemblies of an oligo- p -phenylenevinylene derivative monofunctionalised with a quadruple hydrogen-bonding group (MOPV). MOPV molecules form helical stacks in dodecane solution through solvophobic and π−π interactions with thermotropic reversibility. We apply a model of incoherent excitation hopping using a Monte Carlo scheme to extract microscopic physical quantities relevant to energy diffusion and bimolecular annihilation processes within isolated nanostructures. We compare the simulation to ultrafast spectroscopic data, namely photoinduced absorption transients at various excitation fluences, their polarization anisotropy, and the dynamic photoluminescence red-shift. We observe that energy diffusion and bimolecular annihilation processes can be described with the same microscopic model based on a Förster-like model that takes into account the spatial extent of the excited state; these two processes are interconnected via the same underlying physics. We extract a high diffusion coefficient (∼0.08 cm 2 s -1 ) over the first few picoseconds following excitation, which plays an important role in dictating the bimolecular annihilation dynamics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".