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Record W3210419644 · doi:10.1021/acs.accounts.1c00556

Precision Synthesis of Conjugated Polymers Using the Kumada Methodology

2021· article· en· W3210419644 on OpenAlexafffund
Susan Cheng, Ruyan Zhao, Dwight S. Seferos

Bibliographic record

VenueAccounts of Chemical Research · 2021
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolymerizationMonomerSteric effectsConjugated systemPolymerAtom-transfer radical-polymerizationPolymer chemistryChemistryCatalysisCombinatorial chemistryMaterials scienceNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Since the discovery of conductive poly(acetylene), the study of conjugated polymers has remained an active and interdisciplinary frontier between polymer chemistry, polymer physics, computation, and device engineering. One of the ultimate goals of polymer science is to reliably synthesize structures, similar to small molecule synthesis. Kumada catalyst-transfer polymerization (KCTP) is a powerful tool for synthesizing conjugated polymers with predictable molecular weights, narrow dispersities, specific end groups, and complex backbone architectures. However, expanding the monomer scope beyond the well-studied 3-alkylthiophenes to include electron-deficient and complex heterocycles has been difficult. Revisiting the successful applications of KCTP can help us gain new insight into the CTP mechanisms and thus inspire breakthroughs in the controlled polymerization of challenging π-conjugated monomers.In this Account, we highlight our efforts over the past decade to achieve controlled synthesis of homopolymers (p-type and n-type), copolymers (diblock and statistical), and monodisperse high oligomers. We first give a brief introduction of the mechanism and state-of-the-art of KCTP. Since the extent of polymerization control is determined by steric and electronic effects of both the catalyst and monomer, the polymerization can be optimized by modifying monomer and catalyst structures, as well as finding a well-matched monomer-catalyst system. We discuss the effects of side-chain steric hindrance and halogens in the context of heavy atom substituted monomers. By moving the side-chain branch point one carbon atom away from the heterocycle to alleviate steric crowding and stabilize the catalyst resting state, we were able to successfully control the polymerization of new tellurophene monomers. Inspired by innocent role of the sterically encumbered 2-transmetalated 3-alkylthiophene monomer, we introduce the treatment of hygroscopic monomers with a bulky Grignard compound as a water-scavenger for the improved synthesis of water-soluble conjugated polymers. For challenging electron-deficient monomers, we discuss the design of new Ni(II)diimine catalysts with electron-donating character which enhance the stability of the association complex between the catalyst and the growing polymer chain, resulting in the quasi-living synthesis of n-type polymers. Beyond n-type homopolymers, the Ni(II)diimine catalysts are also capable of producing electron-rich and electron-deficient diblock and statistical copolymers. We discuss how density functional theory (DFT) calculations elucidate the role of catalyst steric and electronic effects in controlling the synthesis of π-conjugated polymers. Moreover, we demonstrate the synthesis of monodisperse high oligomers by temperature cycling, which takes full advantage of the unique character of KCTP in that it proceeds through distinct intermediates that are not reactive. The insight we gained thus far leads to the first example of isolated living conjugated polymer chains prepared by a standard KCTP procedure, with general applicability to different monomers and catalytic systems. In summarizing a decade of innovation in KCTP, we hope this Account will inspire future development in the field to overcome key challenges including the controlled synthesis of electron-deficient heterocycles, complex and high-performance systems, and degradable and recyclable materials as well as cutting-edge catalyst design.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.256
GPT teacher head0.461
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2021
Admission routes2
Has abstractyes

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