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Triboelectric Nanogenerator versus Piezoelectric Generator at Low Frequency (<4 Hz): A Quantitative Comparison

2020· article· en· 129 citations· W3036291007 on OpenAlex· 10.1016/j.isci.2020.101286

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Bench or experimentalConsensus signal: Bench or experimental
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.157
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.039
GPT teacher head0.264
Teacher spread
0.226 · how far apart the two teachers sit on this one work
Validation status
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

Abstract

Triboelectric nanogenerators (TENGs) and piezoelectric generators (PGs) are generally considered the two most common approaches for harvesting ambient mechanical energy that is ubiquitous in our everyday life. The main difference between the two generators lies in their respective working frequency range. Despite the remarkable progress, there has been no quantitative studies on the operating frequency band of the two generators at frequency values below 4 Hz, typical of human motion. Here, the two generators are systematically compared based on their energy harvesting capabilities below 4 Hz. Unlike PGs, the TENG demonstrates higher power performance and is almost independent of the operating frequency, making it highly efficient for multi-frequency operation. In addition, PGs were shown to be inapplicable for charging capacitors when a rectifier was attached to the system. The results of this work reveal the tremendous potential of flexible TENGs for harvesting energy at low frequency.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
iScience
Topic
Advanced Sensor and Energy Harvesting Materials
Field
Engineering
Canadian institutions
McMaster UniversityUniversity of Toronto
Funders
not available
Keywords
Triboelectric effectEnergy harvestingNanogeneratorRectifier (neural networks)Electrical engineeringCapacitorGenerator (circuit theory)PiezoelectricityPower (physics)Low frequencyPhysicsAcousticsMaterials scienceOptoelectronicsComputer scienceVoltageEngineeringTelecommunications
Has abstract in OpenAlex
yes