Evidence map›Paper›PMID 40198808›Full record

ArticleMacromolecular rapid communications2025

A Versatile Flow Reactor Platform for Machine Learning Guided RAFT Synthesis, Amidation of Poly(Pentafluorophenyl Acrylate).

Alexander P Grimm, Stephen T Knox, Clarissa Y P Wilding, Harry A Jones, Björn Schmidt, Olga Piskljonow, Dominik Voll, Christian W Schmitt, Nicholas J Warren, Patrick Théato

Abstract read
In one paragraph

Article in Macromolecular rapid communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
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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

10 authors.

Alexander P GrimmInstitute for Biological Interfaces III (IBG-3), Soft Matter Synthesis Laboratory, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.ORCID https://orcid.org/0000-0002-8423-1708
Stephen T KnoxSchool of Chemical and Process Engineering (SCAPE), University of Leeds (UoL), Woodhouse, Leeds, LS2 9JT, UK.ORCID https://orcid.org/0000-0001-5276-0085
Clarissa Y P WildingSchool of Chemical and Process Engineering (SCAPE), University of Leeds (UoL), Woodhouse, Leeds, LS2 9JT, UK.ORCID https://orcid.org/0000-0002-2441-9741
Harry A JonesSchool of Chemical and Process Engineering (SCAPE), University of Leeds (UoL), Woodhouse, Leeds, LS2 9JT, UK.
Björn SchmidtInstitute for Technical Chemistry and Polymer Chemistry (ITCP), Karlsruhe Institute of Technology (KIT), Engesserstraße 18, 76131, Karlsruhe, Germany.
Olga PiskljonowInstitute for Technical Chemistry and Polymer Chemistry (ITCP), Karlsruhe Institute of Technology (KIT), Engesserstraße 18, 76131, Karlsruhe, Germany.
Dominik VollInstitute for Technical Chemistry and Polymer Chemistry (ITCP), Karlsruhe Institute of Technology (KIT), Engesserstraße 18, 76131, Karlsruhe, Germany.
Christian W SchmittInstitute for Biological Interfaces III (IBG-3), Soft Matter Synthesis Laboratory, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.ORCID https://orcid.org/0000-0001-9875-5628
Nicholas J WarrenSchool of Chemical and Process Engineering (SCAPE), University of Leeds (UoL), Woodhouse, Leeds, LS2 9JT, UK.ORCID https://orcid.org/0000-0002-8298-1417
Patrick ThéatoInstitute for Biological Interfaces III (IBG-3), Soft Matter Synthesis Laboratory, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.ORCID https://orcid.org/0000-0002-4562-9254

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data-driven polymer research has experienced a dramatic upswing in recent years owing to the emergence of artificial intelligence (AI) alongside automated laboratory synthesis. However, the chemical complexity of polymers employed in automated synthesis still lacks in terms of defined functionality to meet the need of next-generation high-performance polymer materials. In this work, the automated self-optimization of the reversible addition-fragmentation chain-transfer (RAFT) polymerization of pentafluorophenyl acrylate (PFPA) is presented, a versatile polymer building-block enabling efficient post-polymerization modifications (PPM). The polymerization system consisted of a computer-operated flow reactor with orthogonal analytics comprising an inline benchtop nuclear magnetic resonance (NMR) spectrometer, and an online size exclusion chromatography (SEC). This setup enabled the automatic determination of optimal polymerization conditions by implementation of a multi-objective Bayesian self-optimization algorithm. The obtained poly(PFPA) is precisely modified by amidation taking advantage of the active pentafluorophenyl (PFP) ester. By controlling the feed ratios of solutions containing different amines, their incorporation ratio into the polymer, and therefore its resulting properties, can be tuned and predicted, which is shown using NMR, differential scanning calorimetry (DSC), and infrared (IR) analysis. The described strategy represents a versatile method to synthesize and modify reactive polymers in continuous flow, expanding the range of functional polymer materials accessible by continuous, high-throughput synthesis.

Indexed as

AcrylatesMachine LearningPolymersMagnetic Resonance SpectroscopyMolecular StructurePolymerizationAcrylatesPolymersdigital chemistryflow chemistrypost‐polymerization modificationRAFT‐polymerizationself‐optimization

Identifiers

PMID40198808
PMCPMC12687679

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Registered trials

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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.