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Record W2259127842 · doi:10.1038/srep10983

Alternating current line-filter based on electrochemical capacitor utilizing template-patterned graphene

2015· article· en· W2259127842 on OpenAlexaff
Zhenkun Wu, Liyi Li, Ziyin Lin, Bo Song, Zhuo Li, Kyoung‐sik Moon, Ching‐Ping Wong, Shu‐Lin Bai

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsMinistry of Education and Child Care
FundersAdvanced Research Projects AgencyAdvanced Research Projects Agency - EnergyNational Natural Science Foundation of China
KeywordsGrapheneMaterials scienceCapacitanceCapacitorElectrodeFilter (signal processing)OxideElectrolytic capacitorOptoelectronicsAlternating currentLine (geometry)VoltageNanotechnologyComputer scienceElectrical engineeringChemistry

Abstract

fetched live from OpenAlex

Aluminum electrolytic capacitors (AECs) are widely used for alternating current (ac) line-filtering. However, their bulky size is becoming more and more incompatible with the rapid development of portable electronics. Here we report a scalable process to fabricate miniaturized graphene-based ac line-filters on flexible substrates at room temperature. In this work, graphene oxide (GO) is reduced by patterned metal interdigits at room temperature and used directly as the electrode material. The as-fabricated device shows a phase angle of -75.4° at 120 Hz with a specific capacitance of 316 µF/cm(2) and a RC time constant of 0.35 ms. In addition, it retains 97.2% of the initial capacitance after 10000 charge/discharge cycles. These outstanding performance characteristics of our device demonstrate its promising to replace the conventional AECs for ac line filtering.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.289
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations73
Published2015
Admission routes1
Has abstractyes

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