Evidence map›Paper›PMID 41902478›Full record

ReviewAngewandte Chemie (International ed. in English)2026

Acceptorless Dehydrogenative Polymerization.

Xin Liu, Jessica L Lathrop, Garret M Miyake

Abstract readReview
In one paragraph

Review in Angewandte Chemie (International ed. in English), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xin LiuDepartment of Chemistry, Colorado State University, Center Ave, Fort Collins, Colorado, 80523, USA.
Jessica L LathropDepartment of Chemistry, Colorado State University, Center Ave, Fort Collins, Colorado, 80523, USA.
Garret M MiyakeDepartment of Chemistry, Colorado State University, Center Ave, Fort Collins, Colorado, 80523, USA.ORCID https://orcid.org/0000-0003-2451-7090

Funding

Organic Photoredox Catalysts for Synthetic Method DevelopmentR35GM144356 · NIGMS · COLORADO STATE UNIVERSITY · PI Garret Morgan Miyake · 2022 to 2026
$2.0M
National Science Foundation 2505700NIH HHS R35GM144356
6 · The paper itself

Abstract

The development of polymerization strategies for enabling the synthesis of polymeric materials with targeted properties remains a central pursuit at the interface of catalysis, polymer chemistry, and materials science. Acceptor-less dehydrogenative polymerization (ADP) has emerged as an approach for a step-growth polymerization for the construction of polyesters, polyamides, polyurethanes, and polyureas from unactivated alcohols and amines, liberating molecular hydrogen as the only by-product. Mechanistically, ADP represents the macromolecular extension of the x framework, wherein transition-metal catalysts mediate sequential substrate dehydrogenations and condensations. By leveraging well-established small-molecule dehydrogenation chemistry into a repetitive polymer-forming sequence, ADP unites synthetic efficiency with sustainability to offer access to structurally diverse and high-performance polymers directly from readily available feedstocks. This minireview highlights the mechanistic foundations, representative catalytic systems, and emerging polymer architectures realized through ADP while identifying some critical challenges and future opportunities we envision will shape its evolution into an enabling platform for green and circular macromolecular design.

Indexed as

Acceptor‐less dehydrogenative polymerizationCatalysisChemically recyclable polymersSustainabilityTransition‐metal complex

Identifiers

PMID41902478
PMCPMC13110771

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.