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Record W2913806803 · doi:10.1021/acscatal.8b05001

TEMPO in Chemical Transformations: From Homogeneous to Heterogeneous

2019· article· en· W2913806803 on OpenAlexaff
Hazi Ahmad Beejapur, Qi Zhang, Kecheng Hu, Li Zhu, Jianli Wang, Zhibin Ye

Bibliographic record

VenueACS Catalysis · 2019
Typearticle
Languageen
FieldChemistry
TopicChemical Synthesis and Reactions
Canadian institutionsConcordia University
FundersNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsReuseHomogeneousNitroxylBiochemical engineeringVariety (cybernetics)ChemistryHeterogeneous catalysisCombinatorial chemistryNanotechnologyComputer scienceCatalysisOrganic chemistryMaterials scienceWaste managementEngineering

Abstract

fetched live from OpenAlex

The organic nitroxyl radical, TEMPO (2,2,6,6-tetramethylpiperidine- N -oxyl), finds a variety of industrial applications for chemical transformations. Because of economic and environmental concerns, the recovery and reuse of TEMPO with maintained high activity are of the utmost importance. In this Review, we summarize the most important advances made by the scientific community in TEMPO immobilization on various organic and inorganic support materials for recovery and reuse, and we discuss the activity and stability, as well as the procedures. Also summarized is the wide range of applications of TEMPO in both homogeneous and heterogeneous forms in chemical transformations, beginning from methodology tuning in synthetic chemistry to the use in polymer chemistry.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations205
Published2019
Admission routes1
Has abstractyes

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