Scanning spreading resistance microscopy current transport studies on doped III–V semiconductors
Bibliographic record
Abstract
Two-dimensional (2D) carrier concentration profiling using scanning spreading resistance microscopy (SSRM) has been carried out on molecular beam epitaxy-grown GaAs and InP dopant calibration samples. The current transport mechanisms between the diamond-coated SSRM tip and the III–V semiconductor cleaved surface (110) was investigated as a function of semiconductor dopant concentration via current–voltage (I–V) measurement. A positive or negative tip bias was applied while scanning over each dopant concentration region (1016–1019 cm−3). The results were compared to simulated I–V curves based on thermionic emission theory. The best fits to the data obtained under forward bias indicated that the contact barrier heights, φb, were much lower than expected from conventional large area planar contacts to GaAs or InP. The effect increases with increasing doping concentration, as a result of a combination of barrier height lowering mechanisms such as image forces, thermionic field emission and minority carrier injection. Under reverse bias, the thermionic emission theory only holds for highly doped semiconductors while for low doping, surface and bulk generation currents determine the overall detectable SSRM current.
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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".