Generation of Hot Electrons with Chiral Metamaterial Perfect Absorbers: Giant Optical Chirality for Polarization-Sensitive Photochemistry
Bibliographic record
Abstract
Chiral plasmonic metamaterials have shown very interesting possibilities as chiral optical absorbers for circularly polarized light detection, as their optical response can be manipulated through the careful design of their geometry. Exhibiting the generation of hot electrons, chiral plasmonic nanostructures can be potentially used for polarization-sensitive photochemistry and chiral photocatalysis, in which the excited hot electrons induce surface reactions. In this study, we show that chiral metamaterial perfect absorbers (MMPAs) can be utilized for plasmon-induced polarization-sensitive photochemistry involving hot electrons, with extremely strong differential chiral responses. The calculated nearly perfect optical absorption (∼98%) of metamaterials demonstrate that the MMPAs can strongly absorb the photons and direct a significant part of the radiant energy to the generation of energetic (hot) carriers. Through the elaborate design of the plasmonic antenna geometry, we theoretically present a MMPA exhibiting a very large circular dichroism in its optical response. In addition, the greatly asymmetric electromagnetic field enhancement response of the MMPA to left and right circularly polarized light leads to a large chiral effect in the hot electron generation. In our calculations with the optimized designs, the g -factor reaches a value of 1.52, close to the theoretical upper limit of 2, higher than that of chiral colloidal nanocrystals with plasmonic resonances and much higher than for any chiral molecules. The remarkably strong chiral effect in hot electron generation, predicted in our study, suggests that plasmonic MMPAs can be used in polarization-sensitive photochemical applications and for photodetection.
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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".