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Record W4366286918 · doi:10.1515/pac-2023-0111

The nitro to amine reduction: from millions of tons to single molecule studies

2023· article· en· W4366286918 on OpenAlexafffund
J. C. Scaiano, Bowen Wang, Connor R. Bourgonje, Mahzad Yaghmaei

Bibliographic record

VenuePure and Applied Chemistry · 2023
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsUniversity of Ottawa
FundersCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsChemistryNitrobenzeneCatalysisPalladiumAmine gas treatingNitroAnilineMoleculeCombinatorial chemistryPhotochemistryNanotechnologyChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Palladium nanostructures are interesting heterogeneous catalysts because of their high catalytic activity in a vast range of highly relevant reactions such as cross couplings, dehalogenations, and nitro-to-amine reductions. In the latter case, the catalyst Pd@GW (palladium on glass wool) shows exceptional performance and durability in reducing nitrobenzene to aniline under ambient conditions in aqueous solutions. To enhance our understanding, we use a combination of optical and electron microscopy, in-flow single molecule fluorescence, and bench chemistry combined with a fluorogenic system to develop an intimate understanding of Pd@GW in nitro-to-amine reductions. We fully characterize our catalyst in situ using advanced microscopy techniques, providing deep insights into its catalytic performance. We also explore Pd cluster migration on the surface of the support under flow conditions, providing insights into the mechanism of catalysis. We show that even under flow, Pd migration from anchoring sites seems to be minimal over 4 h, with the catalyst stability assisted by APTES anchoring.

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 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 score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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 teacher head, 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

Citations1
Published2023
Admission routes2
Has abstractyes

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