{
  "abstract": "Growing global challenges in healthcare, energy, sustainability, and technology have motivated increased automation and robotics to accelerate material discovery and development. Continuous droplet flow chemistry has provided a solution to non-uniform mixing and transport phenomena and provides the advantages of batch reactions for screening individual reaction conditions and reagent compositions. Dynamic experimentation in flow chemistry enables the exploration of a broad design space while minimizing the use of reagents and time by continuously varying reaction parameters (such as temperature, concentration, reaction time). Here, an automated polymer synthesis platform with dynamic experimentation capabilities was implemented. The platform leveraged syringe pumps, a custom uniform irradiance photochemical reactor with tunable temperature control, inline Fourier transform infrared spectroscopy (FTIR), and an online benchtop nuclear magnetic resonance spectrometry (NMR) at 80 MHz for automated and data-rich polymer synthesis. The combination of inline FTIR, online NMR, and offline (500 MHz) NMR enabled cross-validation between analytical techniques, and parity plots comparing data between the techniques had an R 2 value greater than 0.99 for the dynamic experiment exploring the PET-RAFT homopolymerization of methyl acrylate. Dynamic experimentation was also used to explore the copolymerization of methyl acrylate and dimethylacrylamide. The obtained rich data were used to generate accurate Gaussian process regression models for the polymerization reactions with R 2 values greater than 0.9 for parity plots of the model vs experimental monomer conversion values. The Gaussian process regression model of the copolymerization was used to understand copolymerization reaction kinetics by determining reactivity ratios under various light intensity and temperature conditions.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Chemical Engineering",
    "Massachusetts Institute of Technology"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Dylan J. Walsh"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Katharina A. Fransen",
      "orcid": "0000-0002-1612-1777"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Alexander Bentley"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Federico Florit"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Klavs F. Jensen"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Bradley D. Olsen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a1n50wxkznr7g.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15009942/v1",
  "fulltext_url": null,
  "id": "a1n50wxkznr7g",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009942/v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2204|Innovative Microfluidic and Catalytic Techniques Innovation"
    ]
  ],
  "openalex": "W7220716365",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15009942/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/a1n50wxkznr7g.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15009942",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009942/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "Dynamic Flow Experimentation for Data-Rich Polymer Synthesis",
  "title_text": "Dynamic Flow Experimentation for Data-Rich Polymer Synthesis",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/a1n50wxkznr7g",
  "venue": "ChemRxiv",
  "versions": []
}