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Record W2786964961 · doi:10.1149/ma2018-01/1/161

An Investigation into Biomass-Derived Carbon Electrode Scalability and Large-Scale Monolith Electrode Capacitors

2018· article· en· W2786964961 on OpenAlexaff
Aldrich Ngan, Donald W. Kirk, Charles Q. Jia

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSupercapacitorMaterials scienceEnergy storageCarbon fibersNanotechnologyElectrodeBiocharElectrolyteCapacitorPyrolysisElectrochemistryChemical engineeringComposite materialComposite numberElectrical engineeringChemistryVoltage

Abstract

fetched live from OpenAlex

With the increasing drive towards renewable energy sources, the need for further development in electrical energy storage is apparent. As it stands, the temporal misalignment between energy generation and electrical use or demand gives rise to grid-scale issues that can only be addressed by the de-coupling of energy generation and energy demand [1]. This is achievable through improved electrical energy storage technologies, where supercapacitors and batteries stand at the forefront. Electrochemical double layer capacitors (EDLCs) store charge physically using the reversible adsorption of ions onto materials that are often highly conductive, and porous with high specific surface areas. The clear majority of EDLCs both in research and in commercial use utilize porous carbon powder electrodes, held together with binder materials and compressed into thin-films [2]. These would typically be made of graphene, carbon nanotubes or activated carbons. Our group investigates biochar, or biomass-derived carbon, as potential monolithic electrodes rather than thin-film powders now used. Through a controlled pyrolysis process, these monolithic biochar electrodes can retain the internal macrostructures of the sugar-maple (acer saccharum) hardwood, the precursor material of this study. As such, natural mass-transport pathways are available to facilitate electrolyte and ion transport. Monolithic electrodes also provide the benefits of reducing non-active materials such as non-conductive binder materials, and allows the simple construction of larger electrodes that are structurally robust. The scalability of supercapacitors is an important aspect for tackling the large-scale issues in energy storage. This study investigates biochar electrode scalability by pushing the limits of electrode size and analyzing electrochemical performance as a supercapacitor. Previous studies on monolithic biochar supercapacitors explored electrodes in the millimetre size range, with masses of approximately 1 milligram [3]. This study uses electrodes orders of magnitude larger, measuring 2.3 cm x 1.3 cm x 9.6 cm, with masses of 1.4 grams. Preliminary testing was carried out in a two-cell setup in 4M KOH electrolyte with cyclic voltammetry, galvanostatic charge and discharge cycling and chronoamperometric charge and discharge. The results of these experiments are promising, showing high specific capacitances of 35 F/g at 5 mA/g, and 28 F/g at 200 mA/g. Energy storage capability is shown through chronoamperometric charge and discharge to be 83 Joules or 8.23 Wh/kg with a peak power output of approximately 285 W/kg. References [1] Simon P, Gogotsi Y. Materials for electrochemical capacitors. Nature Materials. 2008;7:845-854. [2] Wang Q, Yan J, Fan Z. Carbon materials for high volumetric performance supercapacitors: design, progress, challenges and opportunities. Energy and Environmental Science. 2016;9(3):729-762 [3] Zhang L, Jiang J, Holm N, Chen F. Mini-chunk biochar supercapacitors. Journal of Applied Electrochemistry. 2014;44:1145-51

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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