Designing polyethylenes of complex chain architectures via Pd–diimine-catalyzed “living” ethylene polymerization
Bibliographic record
Abstract
Polymer chain architecture is a critically important chain parameter governing intrinsically the properties and applications of polymers. The rapid developments in "living"/controlled polymerization techniques, particularly the controlled radical polymerization techniques, in the past two decades have enabled the precision synthesis of novel polymers having a great variety of complex yet well-defined chain architectures from various monomer stocks. For polyolefins synthesized via catalytic coordination polymerization, the design of complex chain architectures, however, has only started recently because of the relatively limited advancements in the catalytic "living" olefin polymerization technique. In this regard, the versatile Pd-diimine catalysts have provided some unprecedented opportunities, due to their outstanding features, in rendering successfully a novel class of polyethylenes of various new complex chain architectures through the "living" ethylene polymerization protocol. The complex chain architectures designed to date have included hyperbranched, hybrid hyperbranched-linear, block, gradient and block-gradient, star, telechelic, graft and comb, and surface-tethered polymer brushes. This Feature Article attempts to summarize the recent developments achieved in the area, with an emphasis on the synthetic strategies for the architectural design. These developments demonstrate the great potential for further advancements of this new exciting research area.
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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 | 0.001 |
| 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".