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Record W2981494409 · doi:10.1002/anie.201912367

Zeolite‐Encaged Single‐Atom Rhodium Catalysts: Highly‐Efficient Hydrogen Generation and Shape‐Selective Tandem Hydrogenation of Nitroarenes

2019· review· en· W2981494409 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 · 2019
Typereview
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsDalhousie University
FundersNational Key Research and Development Program of ChinaHigher Education Discipline Innovation ProjectShanghaiTech UniversityNational Natural Science Foundation of China
KeywordsCatalysisChemistryZeoliteAmmonia boraneRhodiumHydrolysisInorganic chemistryHydrogen productionOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Single‐atom catalysts are emerging as a new frontier in heterogeneous catalysis because of their maximum atom utilization efficiency, but they usually suffer from inferior stability. Herein, we synthesized single‐atom Rh catalysts embedded in MFI ‐type zeolites under hydrothermal conditions and subsequent ligand‐protected direct H 2 reduction. C s ‐corrected scanning transmission electron microscopy and extended X‐ray absorption analyses revealed that single Rh atoms were encapsulated within 5‐membered rings and stabilized by zeolite framework oxygen atoms. The resultant catalysts exhibited excellent H 2 generation rates from ammonia borane (AB) hydrolysis, up to 699 min −1 at 298 K, representing the top level among heterogeneous catalysts for AB hydrolysis. The catalysts also showed superior catalytic performance in shape‐selective tandem hydrogenation of various nitroarenes by coupling with AB hydrolysis, giving >99 % yield of corresponding amine products.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.043
GPT teacher head0.289
Teacher spread0.246 · 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