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Record W2587613591 · doi:10.1039/c6cs00403b

A review of high temperature co-electrolysis of H<sub>2</sub>O and CO<sub>2</sub>to produce sustainable fuels using solid oxide electrolysis cells (SOECs): advanced materials and technology

2017· review· en· W2587613591 on OpenAlexaff
Yun Zheng, Jianchen Wang, Bo Yu, Wenqiang Zhang, Jing Chen, Jinli Qiao, Jiujun Zhang

Bibliographic record

VenueChemical Society Reviews · 2017
Typereview
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsNational Research Council CanadaVancouver Biotech (Canada)
FundersNational Natural Science Foundation of China
KeywordsElectrolysisOxideElectrochemistrySustainable energyEnergy storageMaterials scienceChemical engineeringEnergy transformationElectrochemical energy conversionChemistryInorganic chemistryElectrodeMetallurgyRenewable energyElectrical engineeringThermodynamicsEngineeringPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

electrochemical conversions, solid oxide cell material behaviors and degradation mechanisms are highlighted to obtain a better understanding of the high temperature electrolysis process in SOECs. Proposed research directions are also outlined to provide guidelines for future research.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.022
GPT teacher head0.331
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations755
Published2017
Admission routes1
Has abstractyes

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