{
  "abstract": "Reinforcement learning (RL) is a promising strategy for identifying optimal solutions in vast search spaces. We have developed a framework in which the design of organic photoredox catalysts (OPCs) is deliberately formulated as a fragment-based puzzle that is well suited to RL. In this framework, an RL agent sequentially selects and orders molecular fragments and attempts to identify fragment combinations that afford high rewards, as calculated based on the similarity between the properties of the generated molecules and those of 4CzIPN, a well-known OPC. In addition to the rediscovery of a previously reported high-performance OPC, experimental validation of the proposed candidates revealed a TADF emitter with redox potentials similar to those of 4CzIPN, as well as an OPC with superior catalytic activity in several photoreactions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "name": "Naoki Noto",
      "orcid": "0000-0003-0996-9160"
    },
    {
      "name": "Mayu Hirakata"
    },
    {
      "name": "Mikito Fujinami"
    },
    {
      "name": "Yusuke Masuda",
      "orcid": "0000-0002-0386-9989"
    },
    {
      "name": "Ryosuke Kojima"
    },
    {
      "name": "Yasunori Matsui",
      "orcid": "0000-0002-7719-0071"
    },
    {
      "name": "Hiroshi Ikeda",
      "orcid": "0000-0002-8161-2177"
    },
    {
      "name": "Hiromi Nakai",
      "orcid": "0000-0001-5646-2931"
    },
    {
      "name": "Masaya Sawamura"
    },
    {
      "name": "Susumu Saito",
      "orcid": "0000-0003-0749-2020"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fqkfm6ycfgaws.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010145/v1",
  "fulltext_url": null,
  "id": "fqkfm6ycfgaws",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010145/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1605|Radical Photochemical Reactions"
    ]
  ],
  "openalex": "W7221094065",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010145/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-09",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/fqkfm6ycfgaws.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15010145",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010145/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:1605|Radical Photochemical Reactions",
      "subfield": "organic"
    }
  ],
  "title": "Designing organic photoredox catalysts as a fragment-based puzzle solved by reinforcement learning",
  "title_text": "Designing organic photoredox catalysts as a fragment-based puzzle solved by reinforcement learning",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/fqkfm6ycfgaws",
  "venue": "ChemRxiv",
  "versions": []
}