Morphology and Optical Properties of Ultrathin Tellurium-Doped Gallium Phosphide Nanowires
Bibliographic record
Abstract
The high degree of control over the morphology and optoelectronic properties of semiconductor nanowires (NWs) makes them attractive for applications such as thermoelectrics, quantum emitters, and photodetectors. However, NW growth is still not fully understood as many parameters play a role in the determination of NW morphology and crystal structure, which in turn governs resulting optoelectronic properties. We report tellurium-doped GaP NWs with positive tapering and radii measuring as low as 5 nm grown by the self-assisted vapor–liquid–solid mechanism using selective-area molecular beam epitaxy. The occurrence of ultrathin nanoantenna showed a dependence on pattern pitch (separation between NWs) with a predominance at 600 nm pitch, and exhibited radius oscillations that correlate with polytypic zincblende (ZB)/wurtzite (WZ) segments. A growth model explains the positive tapering of the NW leading to an ultrathin tip from the suppression of surface diffusion of Ga adatoms on the NW sidewalls by Te dopant flux. The model also provides a relationship between the radius modulations and the oscillations of the droplet contact angle, predicting the quasi-periodic radius oscillations and corresponding crystal phase transitions. Photoluminescence and cathodoluminescence at 10 K reveal distinct spectra corresponding to either the ZB or WZ phase. Emission above and below ~2.15 eV are associated with ZB and WZ, respectively. The characteristic WZ spectrum arises from a bound exciton and its phonon replicas, consistent with published results. The origin of emission in the ZB regime is less conclusive, but may originate from the splitting of a bound exciton by the field of an axial defect. The results presented in this thesis establish a link between NW growth, morphology, and optoelectronic properties to inform future work involving ultrathin NWs.
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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".