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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".