An Ultrasensitive Silicon Photonic Ion Sensor Enabled by 2D Plasmonic Molybdenum Oxide
Bibliographic record
Abstract
Silicon photonics has demonstrated great potential in ultrasensitive biochemical sensing. However, it is challenging for such sensors to detect small ions which are also of great importance in many biochemical processes. A silicon photonic ion sensor enabled by an ionic dopant-driven plasmonic material is introduced here. The sensor consists of a microring resonator (MRR) coupled with a 2D restacked layer of near-infrared plasmonic molybdenum oxide. When the 2D plasmonic layer interacts with ions from the environment, a strong change in the refractive index results in a shift in the MRR resonance wavelength and simultaneously the alteration of plasmonic absorption leads to the modulation of MRR transmission power, hence generating dual sensing outputs which is unique to other optical ion sensors. Proof-of-concept via a pH sensing model is demonstrated, showing up to 7 orders improvement in sensitivity per unit area across the range from 1 to 13 compared to those of other optical pH sensors. This platform offers the unique potential for ultrasensitive and robust measurement of changes in ionic environment, generating new modalities for on-chip chemical sensors in the micro/nanoscale.
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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 | 0.000 | 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 | 0.001 |
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".