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Record W4213371555 · doi:10.1021/acsenergylett.2c00214

Single-Step Production of Alcohols and Paraffins from CO<sub>2</sub> and H<sub>2</sub> at Metric Ton Scale

2022· article· en· W4213371555 on OpenAlexfundno aff
Chi Chen, Mahlet Garedew, Stafford W. Sheehan

Bibliographic record

VenueACS Energy Letters · 2022
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsnot available
FundersDivision of Industrial Innovation and PartnershipsOntario Centres of ExcellenceNational Aeronautics and Space Administration
KeywordsTonTonneChemistryScale (ratio)Production (economics)Waste managementOrganic chemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVEnergy FocusNEXTSingle-Step Production of Alcohols and Paraffins from CO2 and H2 at Metric Ton ScaleChi ChenChi ChenAir Company, 407 Johnson Avenue, Brooklyn, New York 11206, United StatesMore by Chi Chen, Mahlet GaredewMahlet GaredewAir Company, 407 Johnson Avenue, Brooklyn, New York 11206, United StatesMore by Mahlet Garedew, and Stafford W. Sheehan*Stafford W. SheehanAir Company, 407 Johnson Avenue, Brooklyn, New York 11206, United States*[email protected]More by Stafford W. Sheehanhttps://orcid.org/0000-0003-0432-9260Cite this: ACS Energy Lett. 2022, 7, 3, 988–992Publication Date (Web):February 16, 2022Publication History Received26 January 2022Accepted8 February 2022Published online16 February 2022Published inissue 11 March 2022https://pubs.acs.org/doi/10.1021/acsenergylett.2c00214https://doi.org/10.1021/acsenergylett.2c00214newsACS PublicationsCopyright © Published 2022 by American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views12242Altmetric-Citations1LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (4 MB) Get e-AlertscloseSUBJECTS:Alcohols,Bioethanol,Catalysts,Fossil fuels,Hydrocarbons Get e-Alerts

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.053
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0530.027

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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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 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

Citations12
Published2022
Admission routes1
Has abstractyes

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