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Record W2060506270 · doi:10.14447/jnmes.v16i4.150

A Ferric-Air Battery base on Solid Oxide Fuel Cell for Electrical Energy Storage

2013· article· en· W2060506270 on OpenAlexvenueno aff
Ting Luo, Shaorong Wang, Le Shao, Jiqing Qian, Xiaofeng Ye, Zhongliang Zhan, Tinglian Wen

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2013
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsnot available
Fundersnot available
KeywordsBattery (electricity)OxideFerricRedoxEnergy storageSolid oxide fuel cellMaterials scienceElectrochemistryChemical engineeringHydrous ferric oxidesElectrodeInorganic chemistryChemistryMetallurgyAnode

Abstract

fetched live from OpenAlex

We report a ferric-air, solid oxide battery that consists of a tubular solid oxide cell with Ca(OH)2/CaO dispersed Fe/FeOx powders integrated as the redox-active materials in the fuel chamber. The key feature here is the use of Ca(OH)2 to prevent agglomeration and coarsening of Fe/FeOx powders, and more importantly to enable in situ production of H2/H2O as the electrochemical active redox couple in the fuel electrode. The proof-of-concept solid oxide battery exhibits an energy capacity of 144 Wh kg-1-Fe at a ferric utilization of 18.8% and excellent stability in ten discharge/charge cycles with a voltage efficiency of 83% that have great potential for improvement. These results showed encouraging promise of the ferric-air, solid oxide batteries for electrical energy storage applications.

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 categoriesMeta-epidemiology (narrow)
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 score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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
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

Citations1
Published2013
Admission routes1
Has abstractyes

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