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Record W4221105210 · doi:10.1002/ese3.1107

The application of nonthermal plasma in methanol synthesis via CO<sub>2</sub> hydrogenation

2022· article· en· W4221105210 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergy Science & Engineering · 2022
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsNatural Resources CanadaWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisMethaneRenewable energyMethanolCombustionGasolineProcess engineeringNonthermal plasmaChemistryEnvironmental scienceNanotechnologyChemical engineeringMaterials sciencePlasmaOrganic chemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract CH 3 OH is an energy carrier that can be generated from renewable resources and be used as a fuel in fuel cells and internal combustion engines and a platform chemical for the synthesis of value‐added chemicals or gasoline. Carbon dioxide (CO 2 ) hydrogenation is one of the widely researched methods to generate methanol. The traditional CO 2 hydrogenation reaction method (requires high H 2 pressure and temperatures) has attracted considerable attention. However, the new emerging field of catalysis referred to as nonthermal plasma (NTP) catalysis has also been developed extensively for methane reforming and CO 2 hydrogenation to methane and CO. The plasma‐assisted approach not only presents remarkable advantages, such as room temperature and atmospheric H 2 pressure but also has great potential to be powered by renewable electricity in a flexible way since it can be easily switched on/off. In this account, we review the recent articles published on methanol synthesis from CO 2 and H 2 using NTP. We reviewed and discussed the mechanism of this reaction under NTP, the modification of the reactor configurations, and the rationale behind the catalyst design. In the end, we discussed the advantages and disadvantages of each of these works and the future perspectives of this interesting privileged reaction. We believe this review is of interest to researchers active in sustainable heterogeneous catalysis.

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.

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)0.001
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 score0.027
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.005
GPT teacher head0.202
Teacher spread0.198 · 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