Modeling of piezoelectric power nano-generators using Brownian particles
Bibliographic record
Abstract
We have designed a piezoelectric power nano-generator unitcell (device) where gas molecules are moving in Brownian motion and these molecules collide with a piezoelectric material. Due to the collision by gas molecules on the piezoelectric material, a voltage difference is induced across the piezoelectric material. We developed a simple model to calculate the voltage and power generation by using the method of statistical mechanics. Here we considered that gas molecules are not interacting with each other. We have created a design to connect nano-generator unitcells to form a chip in series configurations to enhance the production of the power nano-generation. Our design for the new power generator shows that as the thickness of the piezoelectric material increases so does the voltage generation. Our design can continuously generate electricity and this feature is better than solar panels that only work during daytime and windmills that cannot work without wind. It can work in a natural atmosphere environment. In the future when a new way of printing chips at low costs is discovered, then generating electricity will be very cheap using our design.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".