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Record W3088595491 · doi:10.1002/ente.202000588

Superior Performance of Electrochemical Double Layer Supercapacitor Made with Asphaltene Derived Activated Carbon Fibers

2020· article· en· W3088595491 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergy Technology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates - Technology Futures
KeywordsMicroporous materialSupercapacitorElectrolyteMaterials scienceChemical engineeringElectrochemistryActivated carbonIonic liquidSpecific energyCapacitanceFiberElectrodeComposite materialOrganic chemistryChemistryAdsorption

Abstract

fetched live from OpenAlex

High energy and power values are obtained from fabricated electrochemical double layer supercapacitor (EDLS) cells derived from asphaltene precursors, which are a solid by‐product of bitumen extraction in pentane solvents. Chemical activation, using dry KOH, is used to activate carbon fibers. Chemical activation introduces high specific surface areas (SSAs) into the fiber microstructure by partially etching the carbon. The electrodes are prepared by mixing activated fibers, polytetrafluoroethylene (PTFE), and acetylene black to form flexible electrode films. The unique bimodal pore size distribution with large micropore and mesopore volumes (micropore volume as high as 0.88 cm 3 g −1 ), from chemical activation, generate high‐performance EDLS symmetric cells with capacitance values exceeding 310 F g −1 in aqueous electrolytes and 210 F g −1 in ionic liquid electrolytes (at a specific current of 40 mA g −1 ). A specific energy of 36 Wh kg −1 at a specific power of 525 W kg −1 is reached in ionic liquid electrolytes.

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.

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)0.000
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 score0.002
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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