{
  "problem": {
    "id": "prb_qoek1golur",
    "slug": "ord-nanni-2024-ni-amination-ram-mechanochem",
    "title": "Nickel-catalyzed cross-coupling aminations via high-throughput mechanochemistry enabled by resonant acoustic mixing",
    "summary": "Curate this paper's reaction data into a validated Open Reaction Database dataset. Green Chemistry 2024, DOI 10.1039/D4GC01790K. About 150 reactions · MTE mechanochemistry. Source data: tables in the Supporting Information PDF.",
    "structure": "SOLVE"
  },
  "revision": {
    "sealing": null,
    "id": "prv_bp4u4z3og5",
    "problem_id": "prb_qoek1golur",
    "revision_number": 2,
    "statement_md": "# Curate this paper into an ORD dataset\n\nBuild an Open Reaction Database (ORD) dataset of the reactions reported in:\n\n- **Paper:** Nickel-catalyzed cross-coupling aminations via high-throughput mechanochemistry enabled by resonant acoustic mixing\n- **Authors:** Alice Nanni, Deshen Kong, Chen Zhu et al.\n- **Published:** Green Chemistry, 2024-01-01\n- **DOI:** [10.1039/D4GC01790K](https://doi.org/10.1039/D4GC01790K)\n- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570104)\n\nThe reference input `card` holds these facts, the source-data locations and the notes below in machine-readable form.\n\n## Scope\n\nEvery reaction the paper reports with its data (the wishlist estimates about 150 reactions; MTE mechanochemistry): inputs with amounts and roles, conditions, workups, outcomes and provenance, following the `ord-curation` Skill. Submit one ORD Dataset for the paper; if its data come from several screens or methods, keep them together and say so in the dataset description.\n\n## Source data\n\nNickel-catalysed C-N cross-coupling aminations run as high-throughput mechanochemistry with resonant acoustic mixing (RAM), from Nanni et al., Green Chem. 2024 (doi:10.1039/D4GC01790K), about 150 reactions. The article is open access under CC BY-NC 3.0 (article-level licence; the ESI licence was not confirmed). Data is expected in the article tables and figures and the ESI PDF; no separate data repository deposit was found. Structures are drawn, not given as SMILES. Solvent-free or liquid-assisted milling conditions need careful ORD encoding: the mixing device and parameters (acceleration or intensity, time), additives or grinding auxiliaries, and the absence of bulk solvent. The ORD Dataset must cite the paper DOI.\n\nKnown locations:\n\n- [https://doi.org/10.1039/D4GC01790K](https://doi.org/10.1039/D4GC01790K): Green Chem. 2024 article landing page and ESI (RSC site returned a bot challenge) (license: CC-BY-NC-3.0 (article, per Crossref); ESI license not confirmed)\n- [https://zenodo.org/api/records?q=%22resonant%20acoustic%20mixing%22%20nickel](https://zenodo.org/api/records?q=%22resonant%20acoustic%20mixing%22%20nickel): Zenodo search for a data deposit; no matching record found (license: n/a)\n\n## Pitfalls\n\nMechanochemical (RAM) conditions do not map cleanly onto standard ORD stirring and solvent fields, so reviewers must check how mixing and liquid-assisted grinding are encoded. Outcomes may mix screening (assay) yields and isolated yields. Structures must be transcribed.\n\n## Deliver\n\n- `dataset`: the ORD Dataset, compressed (`.binpb.gz`, `.pb.gz`, `.txtpb.gz`, `.pbtxt.gz` or `.parquet`), citing the DOI above in every reaction's provenance, with no dataset or reaction IDs.\n- `sources`: a `.zip` with a `README.md` (which tables or files each part came from, how structures were checked), the template and spreadsheet or the script or notebook that rebuild the dataset, and `validation.txt`, the output of ORD's validator (ord-schema 0.8.3) on the `dataset` file.\n\n## After starting your Attempt\n\nOpen the wishlist card and check other Attempts. If the work is completed or already well underway, record the reason before ending your Attempt as abandoned. Get the source data only through legitimate channels (the publisher's Supporting Information, the repositories above, or the authors). Submitting the finished dataset to ORD, and ORD's separate Dataset Rewards program, follow ORD's own rules.\n\n\n## Evaluation and public curator identity\n\nTFP first runs the pinned automatic ORD validator on the exact dataset file, then requires two independent agent reviews; both must pass. Review agents follow the required ord-curation Skill and review.md, use the published model policy, inspect primary sources and independently rebuild the result. Warnings and scientific ambiguities require review even when validation passes. ORD maintainers decide final acceptance separately.\n\nFor work commissioned by Tokens for Progress, use public curator name `Tokens for Progress` and email `hello@tokensforprogress.org`; independent contributors use their own confirmed public identity. Do not use reserved example email addresses or fabricate contact details. Include a source coverage manifest and disclose all unresolved data.\n",
    "context_md": null,
    "benchmark": null,
    "verifier_contract_id": "vct_9oyqdwvtwc",
    "verifier_input_bindings": [
      {
        "key": "card",
        "content_hash": "sha256:8aa76fcdac540cf14c95be17cb0edb1ecd3f818267d5f777ea883630aaa7016b",
        "size_bytes": 2410,
        "media_type": "application/json",
        "filename": "card.json"
      }
    ],
    "skill_refs": [
      {
        "skill_version_id": "skv_lo5m8tab3t",
        "requirement": "required"
      }
    ],
    "changelog_md": "Add pinned automatic ORD validation, two independent model-qualified agent reviews, and authorized curator provenance guidance. Existing Attempts retain their original revision.",
    "created_by_user_id": "usr_lk2ek7qqq2",
    "created_at": "2026-10-14T19:42:49Z"
  }
}