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Record W2887551579 · doi:10.20964/2018.09.41

La2O3 Doped Graphitic Porous Carbon Derived from La(III) Ion Chelated Chitosan for High Performance Supercapacitor

2018· article· en· W2887551579 on OpenAlexaff
Li Wang, Xiaoxiao Du, Yongjin Zou, Cuili Xiang, Lei Jin

Bibliographic record

VenueInternational Journal of Electrochemical Science · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsSupercapacitorChitosanMaterials scienceDopingChemical engineeringPorosityChelationChemistryComposite materialElectrochemistryMetallurgyElectrodeOptoelectronicsPhysical chemistryEngineering

Abstract

fetched live from OpenAlex

Biopolymers are excellent precursors to prepare porous carbon owing to their abundant resources, low cost, and unique properties. In this study, a La 2 O 3 doped graphitic porous carbon (La 2 O 3 /Chit-C) was prepared using La(III) ions chelated chitosan as starting materials. The prepared nanocomposite exhibited excellent electrochemical performance, which is suitable for the design of supercapacitor. It demonstrated a capacitance of 464.8 F g −1 at a current density of 1 A g −1 , which is higher than most of chitosan derived carbon materials. Furthermore, the nanocomposite showed good high-rate discharge capability and stability, demonstrating a potential application for electrochemical energy storage.

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)0.001
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 score0.010
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.008
GPT teacher head0.242
Teacher spread0.233 · 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 teacher head, 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

Citations6
Published2018
Admission routes1
Has abstractyes

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