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High Performance Supercapacitors Electrode Derived from the Pine Needles

2014· article· en· W2029341215 on OpenAlexfundno aff
Pei Yu Wang, Guo Heng Zhang, Hai Yan Jiao, Xiao Ping Zheng

Bibliographic record

VenueAdvanced materials research · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsnot available
FundersNatural Science Foundation of Gansu ProvinceRyerson UniversityNorthwest University for NationalitiesNational Science Foundation
KeywordsSupercapacitorCarbonizationMaterials scienceCapacitanceElectrodeActivated carbonElectrochemistryElectrolyteCapacitive sensingCurrent densitySpecific surface areaChemical engineeringEnergy storageNanotechnologyOptoelectronicsComposite materialElectrical engineeringPower (physics)ChemistryAdsorptionOrganic chemistryCatalysisEngineering

Abstract

fetched live from OpenAlex

In this paper, Pine needles (PNs) were used to synthesize porous activated carbon by the carbonization and activation processes. The material for PNs were carbonized at 600 °C and activated at 800 °C(denoted as AC-800) show typical amorphous character, and display porous structures with high specific surface areas 2729 m 2 /g via XRD and BET measurements. As the electro-active material, AC-800 electrode exhibit ideal capacitive behaviors in aqueous electrolytes, and the maximal specific capacitance is as high as 286 F/g at the current density of 1 A/g. Furthermore, AC-800 electrode shows excellent electrochemical cycle stability with ~94 % initial capacitance being retained after 2000 cycles. The desirable capacitive performances enable the PNs to act as a new biomass source of carbonaceous materials for high performance supercapacitors and low-cost electrical energy storage devices.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.012
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.031
GPT teacher head0.294
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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