Ultra‐high performance size‐exclusion chromatography of synthetic polymers
Bibliographic record
Abstract
Ultra-high performance size-exclusion chromatography (UHP SEC) is a newly developed disruptive technology that allows the high-resolution separation of synthetic polymers in as little as 2 min. The capability of UHP SEC for the characterization of synthetic polymers in organic solvents has been demonstrated. Using the Waters ACQUITY UPLC® H-Class system and ethylene-bridged hybrid size-exclusion chromatography (SEC) columns packed with 1.7 to 2.5-μm particles with pore sizes ranging from 45 to 900 Å, size-based separations of polystyrene and poly(methyl methacrylate) standards in tetrahydrofuran and poly(ethylene oxide) standards in 20 mM ammonium acetate in methanol are achieved within 2-4 min. The speed of analysis is about ten times faster than conventional SEC separations, and greater resolution is achieved. Average molecular weights of selected commercial polymers have been determined using ultra-high performance and conventional SEC. Average M data of analyzed samples are in good agreement using the two approaches. An inherent limitation of SEC in UHP mode is the characterization of very high M polymers (above ca. 2 million Da) due to the deformation and/or mechanical shearing of large molecules at high flow rates.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".