Porous silver nanosheets: a novel sensing material for nanoscale and microscale airflow sensors
Bibliographic record
Abstract
Fabrication of nanoscale and microscale machines and devices is one of the goals of nanotechnology. For this purpose, different materials, methods, and devices should be developed. Among them, various types of miniaturized sensors are required to build the nanoscale and microscale systems. In this research, we introduce a new nanoscale sensing material, silver nanosheets, for applications such as nanoscale and microscale gas flow sensors. The silver nanosheets were synthesized through the reduction of silver ions by ascorbic acid in the presence of poly(methacrylic acid) as a capping agent, followed by the growth of silver in the shape of hexagonal and triangular nanoplates, and self-assembly and nanojoining of these structural blocks. At the end of this process, the synthesized nanosheets were floated on the solution. Then, their electrical and thermal stability was demonstrated at 120 °C, and their atmospheric corrosion resistance was clarified at the same temperature range by thermogravimetric analysis. We employed the silver nanosheets in fabricating airflow sensors by scooping out the nanosheets by means of a sensor substrate, drying them at room temperature, and then annealing them at 300 °C for one hour. The fabricated sensors were tested for their ability to measure airflow in the range of 1 to 5 ml min(-1), which resulted in a linear response to the airflow with a response and recovery time around 2 s. Moreover, continuous dynamic testing demonstrated that the response of the sensors was stable and hence the sensors can be used for a long time without detectable drift in their response.
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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 | 0.001 | 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 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".