Size Control of the Mechanism of Exciton Polarization in Metal Oxide Nanocrystals through Fermi Level Pinning
Bibliographic record
Abstract
Light–matter interaction in certain aliovalently doped metal oxide nanocrystals (NCs) results in the generation of localized surface plasmon resonance (LSPR) in the near- to mid-infrared, allowing for their implementation in various technologies, including photovoltaics, sensing, and electrochromics. These materials could also facilitate coupling between plasmonic and semiconducting properties, making them highly interesting for electronic and quantum information technologies. In the absence of dopants, free charge carriers can arise from native defects such as oxygen vacancies. Here we show using magnetic circular dichroism spectroscopy that the exciton splitting in In 2 O 3 NCs is induced by both localized and delocalized electrons and that contributions from the two mechanisms are strongly dependent on the NC size, owing to Fermi level pinning and the formation of a surface depletion layer. In large NCs, the angular momentum transfer from delocalized cyclotron electrons to the excitonic states is the dominant mechanism of exciton polarization. This process diminishes with decreasing NC size, owing to the rapidly reduced volume of the plasmonic core. On the other hand, exciton polarization in small NCs is dominated by localized electron-spin-induced splitting of the excitonic states. This mechanism is independent of NC size, suggesting that wave functions of localized spin states on NC surfaces do not overlap with the excitonic states. The results of this work demonstrate that the effects of individual and collective electronic properties on excitonic states can be simultaneously controlled by NC size, making metal oxide NCs a promising class of materials for quantum, spintronic, and photonic technologies.
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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 | 0.000 | 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 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".