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Record W2613980906 · doi:10.3390/app7050511

Facile Synthesis of α-MnO2 with a 3D Staghorn Coral-like Micro-Structure Assembled by Nano-Rods and Its Application in Electrochemical Supercapacitors

2017· article· en· W2613980906 on OpenAlexafffund
Yonghong Bing, Lei Zhang, Shichun Mu, Jiujun Zhang

Bibliographic record

VenueApplied Sciences · 2017
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsBC Innovation CouncilNational Research Council Canada
FundersUniversity of British Columbia
KeywordsMaterials scienceSupercapacitorElectrochemistryNanotechnologyNanorodRodChemical engineeringMicrostructureElectrodeComposite materialChemistry

Abstract

fetched live from OpenAlex

Abstract: Manganese oxides with an alpha crystal structure are synthesized via combined solid-state reaction and wet chemical processing, which is a simple and inexpensive synthetic route easy for mass production. The effects of the synthetic reaction duration and the temperature of acid treatments on crystal structure, morphology, and electrochemical capacitive properties of α-MnO2 are discussed. It is evidenced that the samples treated in acid for a longer time at 25 °C display the uniform nanorods that are aggregated to form micro-buildings with fine features on the surface of rods. This microstructure possesses large surface areas and more active sites that are easy to access electrochemically, leading to a better electrochemical capacitive performance. We expected that these results would provide the practical information for shape- and morphology-controlled synthesis for nanostructured functional materials in supercapacitor applications.

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)0.000
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 score0.585

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.233
Teacher spread0.222 · 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

Citations8
Published2017
Admission routes2
Has abstractyes

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