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Record W2612604422 · doi:10.2991/iceesd-17.2017.168

MnO2 Nanotubes Synthesized with One-step Hydrothermal Method as Efficient Bi-functional Cathode Catalyst for a Rechargeable Zinc-air Battery

2017· article· en· W2612604422 on OpenAlexaff
Haoran Li, Xuemei Li, Qi Nie, Keryn Lian, Jinli Qiao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Toronto
FundersDonghua University
KeywordsCathodeBattery (electricity)Hydrothermal circulationCatalysisZincMaterials scienceChemical engineeringZinc compoundsNanotechnologyAnodeElectrodeChemistryMetallurgyElectrical engineeringEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

This paper reports the preparation and electro-catalytic activity of MnO 2 nanotube catalysts for both oxygen reduction reaction (ORR) and oxygen evolution reduction (OER) in alkaline media. The catalysts were synthesized by a simple hydrothermal method under controlling the different temperatures. Results of electrochemical characterization with emphasis on the activity of the catalyst are presented, which was demonstrated by cyclic voltammetry (CV) and linear sweep voltammetry (LSV) employing a rotating disk electrode (RDE) technique. The experiments show that the as-prepared MnO 2 catalyst with nanotube structure exhibited high electro-catalytic activity and stability during battery discharge, charge and cycling processes in 6 M KOH electrolyte. The primary Zn-air battery showed a discharge peak power density ~293 mW cm -2 , which corresponds to the energy density ~725 mA hg -1 . The rechargeable Zn-air battery exhibited a small charge-discharge voltage polarization of ~0.7 V at 10 mA cm -2 , high reversibility and stability over short charge and discharge cycles, and ~1.1 V for a long charge and discharge cycles test.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.633
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.035
GPT teacher head0.295
Teacher spread0.260 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations3
Published2017
Admission routes1
Has abstractyes

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