Residual impurities in high purity InP grown by chemical beam epitaxy
Bibliographic record
Abstract
In the past few years, chemical beam epitaxy (CBE) has succeeded in producing high purity InP with residual carrier concentrations in the low 10/sup 14/ cm/sup -3/ range and liquid nitrogen temperature mobilities much higher than 10/sup 5/ cm/sup 2//Vs. The authors present the results of a study where they have combined electrical, chemical, and optical measurements to identify the residual impurities in InP layers grown with different growth parameters. It is shown that S and Si are the two major residual donor impurities in InP layers grown by CBE and that they originate from the gas sources. Arsenic contamination of InP layers is a common problem in gas source systems, particularly when a single cracker cell is used for both As and P sources. However this contamination can be greatly reduced with a thorough baking prior to InP growth. The concentration of acceptors is negligible and too low to allow the identification of the residual acceptor impurities. Under optimized growth conditions, InP layers with residual carrier concentrations less than 10/sup 14/ cm/sup -3/ can be routinely grown with 77 K mobilities larger than 2 /spl times/ 10/sup 5/ cm/sup 2//Vs.>
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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 | 0.001 |
| 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 | 0.000 |
| 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".