Convenient enantioseparation by monolithic imprinted capillary clamped in a chip with electrochemical detection
Bibliographic record
Abstract
A microchip integrated with a monolithic imprinted capillary has been manufactured for performing the chip-based capillary electrochromatographic enantioseparation. The microporous monolith anchored on the inner wall of the microchannel was prepared by in situ chemical copolymerization, and characterized with scanning electron microscopy, IR spectroscopy, and solid-state UV-vis spectroscopy. The monolithic network with high porosity gave a large surface area, good permeability, low mass-transfer resistance, and thus high separation efficiency. A portable microchip was conveniently constructed by integrating an imprinted capillary with 5-cm length as the separation channel and a carbon fiber microdisk working electrode for amperometric detection. Using L-tyrosine (L-Tyr) as the template molecule, Tyr enantiomers could be baseline separated within 55 s under the optimized preparation and separation conditions. The linear ranges for online amperometric detection of both Tyr enantiomers were from 20 to 2400 μM. The microporous monolithic chip strategy exhibited excellent separation efficiency and promising analytical application in enantioseparation. It opens an avenue for high-throughput screening of chiral compounds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".