Interfacial Contact Engineering Enables Giant‐Performance Semiconductor Nanomembrane Optoelectronic Devices
Bibliographic record
Abstract
Abstract Contact properties at a nanoscale interface critically influence the electrical behaviors of heterogeneous semiconductor devices. Herein, a platform is established to systematically investigate semiconductor nanomembrane interfacial contacts and their impact on the optoelectronic performance of various heterojunctions. Photodiodes with asymmetrical and symmetrical junctions are synthesized through a combination of different contact material stacks and processing steps. Adjusting the surface Schottky barrier height is essential in controlling charge injection and reducing the noise current. Two principal strategies are utilized to enhance the Schottky barrier: surface passivation through interfacial reactions and tuning the buffer layer work function. For electron‐rich Si nanomembranes (SiNMs), an indium‐tin‐oxide (ITO) buffer layer is demonstrated to boost the Schottky barrier through both above strategies by varying device fabrication processing. The work‐function tunable semiconductor‐like ITO (semi‐ITO) is developed for the Schottky junction, while the Ohmic contact is optimized by inserting an emerging low work‐function ytterbium oxide (YbO x ) layer. Extraordinary performance in sensing faint light is demonstrated, including fA/ µm level reverse dark current, rectification ratio of ≈10 8 , picowatt‐level illumination resolution, self‐powered detection, and rapid response speed (≈2.57 µs rise time). This research offers a universal approach to modifying interfacial contacts for advanced semiconductor nanomembrane optoelectronic devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".