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Record W2325085856 · doi:10.1166/jnn.2005.059

Electrokinetic Power Generation by Means of Streaming Potentials: A Mobile-Ion-Drain Method to Increase the Streaming Potentials

2005· article· en· W2325085856 on OpenAlexaff
Jun Yang, Fuzhi Lu, Larry W. Kostiuk, Daniel Y. Kwok

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2005
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStreaming currentElectrokinetic phenomenaMaterials scienceCapacitorIonOptoelectronicsPotential gradientPower (physics)VoltageNanotechnologyElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

We show, by natural occurring phenomena of charge separation near the solid-liquid interface in microchannels, that electricity can be generated by forcing water through a ceramic rod with no moving part and emission. A single hand push on a syringe is our source of power which easily generates a streaming potential of over 20 V and a streaming current of 30 microA. By means of streaming potentials, two capacitors were charged and discharged alternatively to light-up two Light-Emitting-Diodes in every ten seconds. From our specific choice of liquid/solid pair, an efficiency of 0.8% was obtained. A mobile-ion-drain method is also demonstrated to increase the streaming potential.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)

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.

Opus teacher head0.006
GPT teacher head0.236
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2005
Admission routes1
Has abstractyes

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