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Record W3025670647 · doi:10.1149/ma2020-01381670mtgabs

Characterisation of Tantalum Carbide As a Support for Iridium Based Oxygen Evolution Reaction Catalyst for Polymer Electrolyte Membrane Water Electrolysis

2020· article· en· W3025670647 on OpenAlexaff
Nafiseh Rezaei, Brant A. Peppley

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceIridiumCatalysisParticle sizeChemical engineeringBall millSpecific surface areaCatalyst supportScanning electron microscopeElectrolysisElectrolyteMetallurgyMetalComposite materialElectrodeChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Due to the high price and limited production of iridium metal, reducing the iridium loading is a matter of great concern. One approach to lower the iridium loading is the deposition of Ir-based electrocatalysts on a low cost support, which not only enhances the dispersion of electrocatalysts but also improves the electrochemical stability. Another approach is increasing the surface area of the support. The larger the surface area of a support, the better the dispersion of the catalyst on the support. This implies a larger number of available active sites. Ball milling is a simple and environmentally friendly method to reduce the support particle size and increase the surface area of the support. The effect of TaC support surface area on the performance of the supported Ir-based catalyst was studied by Karimi et al. [1]. They found that a 7-fold increase in the TaC support surface area (from 0.9 m2/g to 6.2 m2/g) improves the performance of the supported catalyst by around 50%. In this work, TaC was selected as a support and ball milled with mono-sized (3 mm in diameter) spherical zirconia balls for 7 and 14 days. The particle size and surface area of ball milled TaC were analyzed using Scanning Electron Microscopy (SEM)/ImageJ and nitrogen physisorption methods, respectively. It was observed that ball milling decreases the particle size and increases the surface area of support. After 14 days of ball milling, the TaC showed smaller particle size and larger surface area compared to after 7 days of ball milling. Evaluating the support stability prior to catalyst stability is a crucial process to eliminate unsuitable supports. The electrochemical stability of TaC as a support was evaluated in a strong acidic environment (0.5M H2SO4) and at an oxidizing voltage using cyclic voltammetry (CV) and (EIS). [1] F. Karimi and B. A. Peppley, “Metal Carbide and Oxide Supports for Iridium-Based Oxygen Evolution Reaction Electrocatalysts for Polymer-Electrolyte-Membrane Water Electrolysis,” Electrochim. Acta, vol. 246, pp. 654–670, 2017.

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

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