A novel application of nanoporous gold to humidity sensing: a framework for a general volatile compound sensor
Bibliographic record
Abstract
Volatile organic compounds (VOC) are ubiquitous in industrial applications creating a pressing desire for novel transduction pathways to build a broad family of new gas sensors. Nanoporous gold (NPG) is a material with a vast range of untapped potential applications; offering a high surface area found generally in nanomaterials, while also being comparatively simple to fabricate. NPG based sensors can also leverage the unique physics of gold at the nanoscale. In this work, we leverage the multiple unique nanoscale phenomena associated with NPG to demonstrate two novel transduction mechanisms to sense humidity, a model compound. Through direct electrical measurements of NPG, we were able to sense changes in the electronic properties of NPG induced by ambient humidity. We propose two novel transduction mechanisms: chemoresistive changes induced by surface adsorption and electrochemical capacitive changes induced by the electric double layer to detect humidity. To our knowledge this is the first reported application of both these mechanisms for sensing any volatile compounds utilizing NPG.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".