Facile Semiconductor p–n Homojunction Nanowires with Strategic p-Type Doping Engineering Combined with Surface Reconstruction for Biosensing Applications
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Photosensors with versatile functionalities have emerged as a cornerstone for breakthroughs in the future optoelectronic systems across a wide range of applications. In particular, emerging photoelectrochemical (PEC)-type devices have recently attracted extensive interest in liquid-based biosensing applications due to their natural electrolyte-assisted operating characteristics. Herein, a PEC-type photosensor was carefully designed and constructed by employing gallium nitride (GaN) p – n homojunction semiconductor nanowires on silicon, with the p -GaN segment strategically doped and then decorated with cobalt–nickel oxide (CoNiO x ). Essentially, the p – n homojunction configuration with facile p -doping engineering improves carrier separation efficiency and facilitates carrier transfer to the nanowire surface, while CoNiO x decoration further boosts PEC reaction activity and carrier dynamics at the nanowire/electrolyte interface. Consequently, the constructed photosensor achieves a high responsivity of 247.8 mA W −1 while simultaneously exhibiting excellent operating stability. Strikingly, based on the remarkable stability and high responsivity of the device, a glucose sensing system was established with a demonstration of glucose level determination in real human serum. This work offers a feasible and universal approach in the pursuit of high-performance bio-related sensing applications via a rational design of PEC devices in the form of nanostructured architecture with strategic doping engineering.
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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) | 0.000 | 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 it