Direct Arylation Polymerization of Degradable Imine-Based Conjugated Polymers
Bibliographic record
Abstract
The development and optimization of reliable polymerization methods are needed for the synthesis of degradable imine-based conjugated polymers, which are attractive materials for transient electronics. Direct arylation polymerization (DArP) has emerged as a sustainable and atom-economical synthetic method for the preparation of well-defined conjugated polymers. Compared to polymerization methods such as imine polycondensation or Stille cross-coupling polymerization, which require monomer functionalization, direct arylation proceeds via C–H activation and thereby reduces synthetic complexities and toxic byproducts. Here, we report the first use of DArP for the synthesis of an imine-based indacenodithiophene (IDT) copolymer, p(IDT–TIT). Polymers prepared via DArP can result in branched or cross-linked polymer chains due to the reactivity of C–H bonds in the monomers. In this report, we demonstrate a systematic study focusing on the reaction conditions needed to prepare p(IDT–TIT) via DArP with tetramethylethylenediamine as a coligand. The degradable polymer is characterized via nuclear magnetic resonance spectroscopy, high-temperature gel permeation chromatography, and ultraviolet–visible–near-infrared spectroscopy. With the simplicity of monomer preparation and reaction conditions, we anticipate that this efficient synthetic protocol will lead to higher synthetic adoption in the research community to aid the exploration of high-performance imine-based degradable materials.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".