Charge Carrier Lifetime and Trap States in Novel Pure-Boron-Based Ultrashallow <i>p</i> – <i>n</i> Junctions
Bibliographic record
Abstract
Trap states and carrier transport parameters are critical to the performance ofp–n-junction-based photodetectors. This study investigates ultrashallowp–njunctions for ultraviolet and low-energy particle detection fabricated using chemical vapor deposition-based pure-boron deposition (CVD-PB) with a junction depth only tens of nanometers, in comparison, also using ion implantation (IMP), epitaxy (EPI), and vacuum evaporation (VEP). Deep-level photothermal spectroscopy (DLPTS) and homodyne photocarrier radiometry (HoPCR) were used to analyze charge carrier dynamics, including charge carrier lifetime and trap states. A phenomenological theoretical model for HoPCR signals was developed to explain trap-state-modulated carrier transport dynamics. CVD-PB junctions demonstrated long recombination lifetimes in the doping layer (7.09 ± 0.01 μs) and bulk (35.80 μs), comparable to high-energy ion-implanted (HE-IMP) junctions (5.68 ± 0.58 and 36.10 μs). EPI and VEP junctions have short carrier bulk recombination lifetimes (1.95 ± 0.17 and 0.63 ± 0.03 μs, respectively). DLPTS revealed an electron trap in the EPI junction with an activation energy of 0.09 eV and a capture cross section of 7.52 × 10-20± 6.82 × 10-21cm2; no detectable traps were observed in CVD-PB or HE-IMP junctions. Simulations showed that EPI junctions had twice the dark current of CVD-PB and HE-IMP at 10 V, with a 15% reduction in photocurrent. When reversely biased at 5 V and without typical guarding ring designs generally used in optoelectronics, CVD-PB exhibited the lowest dark current (0.95 μA/cm2) when compared to HE-IMP (3.25 μA/cm2) and EPI (51.77 μA/cm2).
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".