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Record W2888863811 · doi:10.1134/s1023193518080050

Reversible Solid Oxide Fuel Cell for Power Accumulation and Generation

2018· article· en· W2888863811 on OpenAlexfundno aff
Д.А. Осинкин, Н. М. Богданович, С. М. Береснев, E. Yu. Pikalova, Д. И. Бронин, Yu. P. Zaikov

Bibliographic record

VenueRussian Journal of Electrochemistry · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsnot available
FundersArctic Institute of North America
KeywordsPower densityHigh-pressure electrolysisElectrolyteAnodeElectrolysis of waterHydrogenElectrodeElectrolysisSolid oxide fuel cellMaterials sciencePolymer electrolyte membrane electrolysisCurrent densityElectrochemistryAnalytical Chemistry (journal)Hydrogen fuelChemistryInorganic chemistryThermodynamicsPower (physics)

Abstract

fetched live from OpenAlex

The anodic and cathodic polarization dependences for the oxygen electrode based on lanthanum-strontium manganite and the fuel Ni-cermet electrode are studied in the temperature range of 700–900°С in gas media that correspond to working conditions of a reversible fuel cell. The temporal behavior of these electrodes is studied in the course of periodic polarity changes of current with the density of 0.5 A/cm2. The electrode overvoltage is shown to be about 0.1 V in modes of power generation and water electrolysis at 900°С and the current density of 0.5 A/cm2. A single electrolyte supported tubular solid-oxide fuel cell was fabricated and tested in the fuel-cell and hydrogen-generation modes. It is found that at 900°С and overvoltage of 0.7 V, the cell generates the specific electric power of 0.4 W/cm2 when the 50% H2 + 50% H2O gas mixture is used as the fuel and air is used as the oxidizer. At the water electrolysis with the current density of 0.5 A/cm2, which under normal conditions corresponds to generation of about 0.2 and 0.1 L/h of hydrogen and oxygen, respectively, the consumed power is about 0.55 W/cm2. The efficiency of the conversion cycle electric power–hydrogen–electric power is 70–75%.

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)0.000
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 score0.465

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.021
GPT teacher head0.302
Teacher spread0.282 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueRussian Journal of ElectrochemistrySame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207