Direct Nanoscale Imaging of Evolving Electric Field Domains in Quantum Structures
Bibliographic record
Abstract
The external performance of quantum optoelectronic devices is governed by the spatial profiles of electrons and potentials within the active regions of these devices. For example, in quantum cascade lasers (QCLs), the electric field domain (EFD) hypothesis posits that the potential distribution might be simultaneously spatially nonuniform and temporally unstable. Unfortunately, there exists no prior means of probing the inner potential profile directly. Here we report the nanoscale measured electric potential distribution inside operating QCLs by using scanning voltage microscopy at a cryogenic temperature. We prove that, per the EFD hypothesis, the multi-quantum-well active region is indeed divided into multiple sections having distinctly different electric fields. The electric field across these serially-stacked quantum cascade modules does not continuously increase in proportion to gradual increases in the applied device bias, but rather hops between discrete values that are related to tunneling resonances. We also report the evolution of EFDs, finding that an incremental change in device bias leads to a hopping-style shift in the EFD boundary--the higher electric field domain expands at least one module each step at the expense of the lower field domain within the active region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".