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Diffusion-Controlled Electrosynthesis of Nanoporous Electrodes for Electrochemical Supercapacitors

2009· article· en· W1993835021 on OpenAlex
Gideon Moses Jacob, Igor Zhitomirsky

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of nano research · 2009
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceElectrosynthesisElectrolyteNanoporousElectrochemistryElectrodeCathodeChemical engineeringSupercapacitorDiffusionCapacitanceNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Nanostructured manganese dioxide films were obtained by electrosynthesis using 0.02-0.15 M KMnO4 solutions. The diffusion-controlled deposition mechanism is based on the reduction of anionic MnO4- at the cathode surface. The method allowed the fabrication of porous films for application in electrochemical supercapacitors (ES). It was shown that film porosity is beneficial for the charge transfer during deposition, crack prevention in thick films and electrolyte diffusion in fabricated ES electrodes. Porous nanostructured films showed good capacitive behavior in the 0.1 M Na2SO4 electrolyte in a voltage window of 1V. The specific capacitance decreased with increasing scan rate due to the diffusion limitation in the porous manganese dioxide electrodes

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.

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)0.004
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.034
GPT teacher head0.328
Teacher spread0.294 · 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