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Performance of activated stainless steel and nickel-based anodes in alkaline water electrolyser

2023· article· en· W4321767345 on OpenAlexaff
Hamid Reza Zamanizadeh, Alejandro Oyarce Barnett, Svein Sunde, Bruno G. Pollet, Frode Seland

Bibliographic record

VenueJournal of Power Sources · 2023
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNorges Forskningsråd
KeywordsAnodeScanning electron microscopeElectrochemistryLinear sweep voltammetryMaterials scienceElectrodeBar (unit)Cyclic voltammetryAnalytical Chemistry (journal)ChemistryChemical engineeringComposite materialChromatography

Abstract

fetched live from OpenAlex

Four different alloys including SS316, SS304, Inconel718 and Incoloy800 are activated by electro-oxidation at +1.70 V vs. RHE in 7.5 M KOH for 18 h. Their OER activity are evaluated ex-situ using linear sweep voltammetry in 1.0 M KOH in a three-electrode electrochemical cell. X-ray photoelectron microscopy and scanning electron microscopy are used to obtain the surface composition and surface morphology. It is found that the OER activity improves as the Ni content at the surface increases. A Ni mesh along with untreated and activated SS316 meshes were investigated in-situ in 30 wt% KOH at 80 °C in an alkaline electrolyser. The effect of temperature up to 80 °C as well as pressure up to 9 bar are studied on the cell performance. It is observed that the cell with activated SS316 as anode is outperforming those with the Ni and untreated SS316 as anode. Up to 255 h durability tests at constant current of 0.8 A cm−2 at 80 °C and 9 bar shows no degradation in the performance of the cells containing Ni and activated SS316 as anode. SS316 is also activated in-situ at 1.76 A cm−2 for 18 h and 2 bar. The in-situ activation improves the SS316 OER activity.

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 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 score0.006
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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

Citations31
Published2023
Admission routes1
Has abstractyes

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