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Record W3113989839 · doi:10.21203/rs.3.rs-127974/v1

Integration of 3D interconnected sodium hydroxide modified biochar with the tile-like architecture of cobalt oxides for asymmetric supercapacitors

2020· preprint· en· W3113989839 on OpenAlexaff
Omid Norouzi, Seyed Esmaeil Mohammadi Pourhoseini, Hamid Naderi, Francesco Di Maria, Animesh Dutta

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSupercapacitorCapacitanceCobaltBiocharMaterials scienceChemical engineeringRabCurrent densityPyrolysisElectrodeChemistryMetallurgyPhysics

Abstract

fetched live from OpenAlex

Abstract Two state-of-the-art electrodes were successfully synthesized and used to assemble both symmetric and asymmetric type supercapacitors. 3DFAB was fabricated by direct pyrolysis of green macroalgae in the presence of NaOH. Possible mechanisms of NaOH activation is proposed, which explains the formation of oxygen functional groups through quick penetration of OH- and NaOH into the vacancies. To obtain CoTLM, the tile-like architecture of cobalt oxides was introduced to the 3D interconnected functional algal biochar (3DFAB) by a simple one-pot hydrothermal method under mild conditions. For the symmetric supercapacitors, the maximum specific capacitance of RAB, 3DFAB, and CoTLM were 177 F g− 1, 322 F g− 1, and 529 F g− 1 at a scan rate of 5mVs− 1. Regarding cobalt-based asymmetric systems, the maximum capacitance for the RAB//CoTLM and 3DFAB//CoTLM were ∼300 F g− 1 and 400 F g− 1, respectively. The 3DFAB//CoTLM showed a higher energy density compared with RAB//CoTLM, while the RAB//CoTLM exhibited better cycling performance (99.1% of its initial capacitance after 4 k cycles at the current density of 4 A g 1).

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 score0.002

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 science0.0000.000
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 head0.063
GPT teacher head0.324
Teacher spread0.261 · 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
Published2020
Admission routes1
Has abstractyes

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