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Record W4413005560 · doi:10.1039/d5ee02847g

Electrolysis of ethylene to ethylene glycol paired with acidic CO<sub>2</sub>-to-CO conversion

2025· article· en· W4413005560 on OpenAlexaff
Hongjun Chen, Heejong Shin, Jianan Erick Huang, Rui Kai Miao, Rong Xia, Weiyan Ni, Jiaqi Yu, Yongxiang Liang, Bosi Peng, Yuanjun Chen, Guangcan Su, Kaizhou Xie, Anita Ho‐Baillie, Edward H. Sargent

Bibliographic record

VenueEnergy & Environmental Science · 2025
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Toronto
FundersNational Research Foundation of KoreaAustralian Research CouncilNational Research FoundationAustralian Government
KeywordsEthylene glycolEthyleneElectrolysisChemistryNuclear chemistryOrganic chemistryElectrodeElectrolyteCatalysis

Abstract

fetched live from OpenAlex

A paired electrolysis system converts CO 2 to CO and ethylene to ethylene glycol in acid. Using an Ru–POM mediator and gold-modified electrodes, it achieves high selectivity, stability, and improved CO 2 utilization.

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 score0.049
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.004
GPT teacher head0.214
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

Citations10
Published2025
Admission routes1
Has abstractyes

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