Scanning differential spreading resistance microscopy on actively driven buried heterostructure multiquantum-well lasers
Bibliographic record
Abstract
We have developed a new scanning probe microscopy-based technique, scanning differential spreading resistance microscopy (SDSRM), which enables the determination of free carrier distribution inside operating electronic and optoelectronic devices. The results of our SDSRM study of multiquantum-well (MQW) buried heterostructure (BH) lasers under zero and forward biases are reported. Individual QW-barrier layers can be resolved in high-resolution SDSRM. The SDSRM results show different internal carrier distribution within the MQW active region in BH lasers with and without biases and provide direct experimental evidence of electron overbarrier leakage. Our results demonstrate the utility of SDSRM to delineate quantitatively the transverse cross-sectional structure of complex two-dimensional devices such as MQW BH lasers under operating conditions, in which traditional probing such as secondary ion mass spectroscopy, scanning spreading resistance microscopy, and electron beam-induced current microscopy can either apply only to devices under zero bias or provide only qualitative pictures.
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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".