A new high‐throughput approach to measure copolymerization reactivity ratios using real‐time FTIR monitoring
Bibliographic record
Abstract
Abstract This paper presents a novel high‐throughput approach to measure copolymerization reactivity ratios from a single experiment using high‐speed real‐time Fourier transform infrared (FTIR) monitoring of the isobutylene/isoprene (IB/IP) system initiated by 2‐chloro‐2,4,4‐trimethyl‐pentane (TMPCl)/TiCl 4 in hexane/methyl chloride (Hx/MeCl) 60:40 v/v solvent at −80 °C. Traditional polymer analysis is severely limited in this system, which is riddled by side reactions. The reactivity ratios calculated by linear (Mayo‐Lewis and Kelen‐Tüdös) methods and by a nonlinear least square (NLLS) method (van Herk algorithm) showed good agreement with r 1 =1.32 and r 2 = 0.74 calculated using Mayr's nucleophilicity scale. Combination of the Kelen‐Tüdös and NLLS methods yielded r 1 = 1.17 ± 0.01 and r 2 = 0.99 ± 0.02. These values agree well with those reported by Thaler et al. but disagree with most reported data. © 2004 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 42: 4084–4100, 2004
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".