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Record W2166409786 · doi:10.1149/06429.0057ecst

Electrodeposition of Nanoscale Manganese Oxide onto Nickel Foam for Energy Storage Applications

2015· article· en· W2166409786 on OpenAlexaff
M.P. Clark, Wei Qu, Douglas G. Ivey

Bibliographic record

VenueECS Transactions · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsNational Research Council CanadaUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceSupercapacitorCyclic voltammetryPEDOT:PSSNickelCapacitanceChemical engineeringManganeseOxideAnodeX-ray photoelectron spectroscopyGrain sizeNanotechnologyMetallurgyElectrodeElectrochemistryChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

A template free anodic electrodeposition process has been developed to deposit Mn oxide and Mn oxide/ PEDOT rods onto Ni foam substrates for use as a supercapacitor. The deposit morphology has been optimized by varying deposition conditions and by characterization using SEM imaging. TEM diffraction indicates that the deposits are poorly crystalline, with a grain size less than 20 nm. XPS analysis revealed that the deposits are present as a combination of MnO2 and MnOOH. The capacitive performance of the deposits was characterized using cyclic voltammetry. The addition of PEDOT increased the capacitance of deposits from 120 (0.29 F/cm2) to 159 F/g (0.50 F/cm2) at 5 mV/s. Capacitance retention after 500 cycles was 91% and 113% for deposits with and without PEDOT, respectively.

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 score0.003

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 head0.018
GPT teacher head0.239
Teacher spread0.221 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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