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Record W6884453040 · doi:10.1021/cs4007588.s001

Aminolactone Chiral Modifiers for Heterogeneous Asymmetric\nHydrogenation: Corrected Structure of Pantoyl-Naphthylethylamine,\nIn-Situ Hydrogenolysis, and Scanning Tunneling Microscopy Observation\nof Supramolecular Aminolactone/Substrate Assemblies on Pt(111)

2016· article· en· W6884453040 on OpenAlexaff

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsScanning tunneling microscopeSupramolecular chemistryAdsorptionBond cleavageCatalysisScanning probe microscopy

Abstract

fetched live from OpenAlex

As established by Baiker and co-workers,\npantoyl-naphthylethylamine (PNEA) is an efficient synthetic chiral\nmodifier for the asymmetric hydrogenation of ketopantolactone (KPL)\nto pantolactone on supported Pt catalysts. We report a scanning tunneling\nmicroscopy (STM) study of PNEA and PNEA-derived aminolactone species\non Pt(111) and a reassignment of the relative stereochemistry of the\nmodifier. Robust organic chemistry methods were used to establish\nthat the structure of PNEA is <i>R</i>,<i>S</i> rather than <i>R</i>,<i>R</i>. The dissociative\nchemisorption of a fraction of PNEA adsorbed on Pt(111) yields two\nfragments that we attribute to a process involving C–N bond\nscission. We show that C–N bond scission occurs under hydrogenation\nconditions on PNEA-modified Pt/Al<sub>2</sub>O<sub>3</sub> catalysts,\nforming the aminolactone amino-4,4-dimethyldihydrofuran-2-one (AF).\nSTM measurements on (<i>S</i>)-AF and 2,2,2-trifluoroacetophenone\ncoadsorbed on Pt(111) show the formation of isolated 1:1 complexes.\nIn contrast, measurements on coadsorbed (<i>S</i>)-AF and\nKPL show fluxional supramolecular AF/KPL assemblies. The possibility\nthat such assemblies contribute to the overall enantioselectivity\nobserved for PNEA-modified Pt catalysts is discussed.

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 categoriesMeta-epidemiology (narrow)
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.021
GPT teacher head0.233
Teacher spread0.211 · 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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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