Cellulose Nanocrystals as Chiral Inducers: Enantioselective Catalysis and Transmission Electron Microscopy 3D Characterization
Bibliographic record
Abstract
Cellulose nanocrystals (CNCs), derived from cellulose, provide us with an opportunity to devise more sustainable solutions to current technological challenges. Enantioselective catalysis, especially heterogeneous, is the preferred method for the synthesis of pure chiral molecules in the fine chemical industries. Cellulose has been long sought as a chiral inducer in enantioselective catalysis. We report herein an unprecedentedly high enantiomeric excess (ee) for Pd patches deposited onto CNCs used as catalysts for the hydrogenation of prochiral ketones in water at room temperature and 4 bar H2. Our system, where CNCs acted as support and sole chiral source, achieved an ee of 65% with 100% conversions. Cryo-electron microscopy, high-resolution transmission electron microscopy, and tomography were used for the first time to study the 3D structure of a metal functionalized CNC hybrid. It established the presence of sub-nanometer-thick Pd patches at the surface of CNCs and provided insight into the chiral induction mechanism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".