Bibliographic record
Abstract
In the effective mass approximation, the effect of a planar external uniform electric field on excitonic states in a CdSe nanoplatelet (NPL) is considered.It is shown that an external field deforms the Coulomb-like potential of electron-hole attraction in a NPL, which ultimately leads to the destruction of the exciton as a bound state.Computational calculations show the degree of deformation of the electron-hole potential and the change in the spatial distribution of the probability density (exciton wave function) under the influence of an external field.Curves are also shown that illustrate the degree of shift in the position of the main exciton energy level (Stark shift) under the influence of an external field.In the region of weak fields, the magnitude of the energy shift has a quadratic dependence on the external field strength.For strong fields, this dependence on the field is linear.It is also shown that the effect of an external field on excitonic states in a NPL strongly depends on the number of atomic monolayers in the direction of size quantization of charge carriers.It is also shown that the effect of an external field on excitonic states in a nanoplate strongly depends on the number of monolayers in the direction of size quantization of charge carriers.As the number of monolayers increases, the effect of the external field increases, which is a consequence of a decrease in the exciton binding energy with increasing of NPL thickness.
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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) | 0.002 | 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".