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Record W2766168051 · doi:10.1002/advs.201770052

Photothermal Catalysis: Photothermal Catalyst Engineering: Hydrogenation of Gaseous CO<sub>2</sub> with High Activity and Tailored Selectivity (Adv. Sci. 10/2017)

2017· article· en· W2766168051 on OpenAlexaff
Jia Jia, Hong Wang, Zhuole Lu, Paul G. O’Brien, Mireille Ghoussoub, Paul N. Duchesne, Ziqi Zheng, Peicheng Li, Qiao Qiao, Lu Wang, Alan Gu, Feysal M. Ali, Yuchan Dong, Qiang Wang, Kulbir Kaur Ghuman, Thomas E. Wood, Chenxi Qian, Yue Shao, Chenyue Qiu, Miaomiao Ye, Yimei Zhu, Zheng‐Hong Lu, Peng Zhang, Amr S. Helmy, Chandra Veer Singh, Nazir P. Kherani, Doug D. Perovic, Geoffrey A. Ozin

Bibliographic record

VenueAdvanced Science · 2017
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsCanada Research ChairsDalhousie UniversityYork UniversityUniversity of Toronto
Fundersnot available
KeywordsMethanationPhotothermal therapyCatalysisSelectivityCarbon monoxideNanocrystalPhotothermal effectWater-gas shift reactionMethaneChemical engineeringChemistryCarbon fibersPalladiumNanotechnologyMaterials scienceCarbon dioxidePhotochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The size dependence of the photothermal effect of palladium nanocrystals enables the selectivity of the solar powered heterogeneous catalytic hydrogenation of carbon dioxide to be finely tailored towards producing either carbon monoxide through the reverse water gas shift reaction, CO2 + H2 → CO + H2O, favored for small nanocrystals or to methane, via the Sabatier methanation reaction, CO2 + 4H2 → CH4 + 2H2O, preferred for larger nanocrystals. This is described by Geoffrey A. Ozin and co-workers in article number 1700252.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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