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Record W4318706860 · doi:10.1038/s41467-023-36259-9

COx hydrogenation to methanol and other hydrocarbons under mild conditions with Mo3S4@ZSM-5

2023· article· en· W4318706860 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.

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsMinistry of Education and Child Care
FundersMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsMethanolZSM-5ChemistryCatalysisOrganic chemistryZeolite

Abstract

fetched live from OpenAlex

Abstract The hydrogenation of CO 2 or CO to single organic product has received widespread attentions. Here we show a highly efficient and selective catalyst, Mo 3 S 4 @ions-ZSM-5, with molybdenum sulfide clusters ([Mo 3 S 4 ] n+ ) confined in zeolitic cages of ZSM-5 molecular sieve for the reactions. Using continuous fixed bed reactor, for CO 2 hydrogenation to methanol, the catalyst Mo 3 S 4 @NaZSM-5 shows methanol selectivity larger than 98% at 10.2% of carbon dioxide conversion at 180 °C and maintains the catalytic performance without any degeneration during continuous reaction of 1000 h. For CO hydrogenation, the catalyst Mo 3 S 4 @HZSM-5 exhibits a selectivity to C 2 and C 3 hydrocarbons stably larger than 98% in organics at 260 °C. The structure of the catalysts and the mechanism of CO x hydrogenation over the catalysts are fully characterized experimentally and theorectically. Based on the results, we envision that the Mo 3 S 4 @ions-ZSM-5 catalysts display the importance of active clusters surrounded by permeable materials as mesocatalysts for discovery of new reactions.

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)0.000
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 score0.262
Threshold uncertainty score0.612

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.307
Teacher spread0.282 · 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