Study of deep levels in GaAs p–i–n structures
Bibliographic record
Abstract
An experimental study of the capacitance–voltage (C–V) characteristics and deep-level transient spectroscopy (DLTS) of p +–p 0–i–n 0 structures based on undoped GaAs, grown by liquid-phase epitaxy at two crystallization-onset temperatures T o (950 and 850°C), with optical illumination switched off and on, are performed. It is shown that the p 0, i, and n 0 layers of epitaxial structures are characterized by the presence of defects with deep donor- and acceptor-type levels in concentrations comparable with those of shallow donors and acceptors. Interface states are found, which manifest themselves in the C–V characteristics at different measurement temperatures and optical illumination; these states form an additive constant. A distinct temperature dependence of the steady-state capacitance of the structures is revealed. It is found that the injection of minority carriers under an applied positive filling pulse and optical recharging lead to modification of the structure and, correspondingly, the DLTS spectra of the p +–p 0–i–n 0 structures. It is revealed that the p +–p 0–i–n 0 GaAs structures grown at T o = 850°C are characterized by a lack of interface states and that the recharging of acceptor-type deep traps under illumination does not change the C–V characteristics. The conventionally measured DLTS spectra reveal the presence of two hole traps: HL5 and HL2, which are typical of GaAs layers.
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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) | 0.001 | 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".