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Record W4360999082 · doi:10.1002/anie.202218694

Supercharged CO <sub>2</sub> Photothermal Catalytic Methanation: High Conversion, Rate, and Selectivity

2023· article· en· W4360999082 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

VenueAngewandte Chemie International Edition · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsUniversity of Toronto
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsMethanationCatalysisSelectivityPhotothermal therapyChemical engineeringChemistryMaterials scienceReaction rateInorganic chemistryPhotochemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract To overcome the thermodynamic and kinetic impediments of the Sabatier CO 2 methanation reaction, the process must be operated under very high temperature and pressure conditions, to obtain an industrially viable conversion, rate, and selectivity. Herein, we report that these technologically relevant performance metrics have been achieved under much milder conditions using solar rather than thermal energy, where the methanation reaction is enabled by a novel nickel‐boron nitride catalyst. In this regard, an in situ generated HOB⋅⋅⋅B surface frustrated Lewis's pair is considered responsible for the high Sabatier conversion 87.68 %, reaction rate 2.03 mol g Ni −1 h −1 , and near 100 % selectivity, realized under ambient pressure conditions. This discovery bodes well for an opto‐chemical engineering strategy aimed at the development and implementation of a sustainable ‘Solar Sabatier’ methanation process.

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 score0.010
Threshold uncertainty score0.912

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 science0.0000.000
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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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