# Curate this paper into an ORD dataset

Build an Open Reaction Database (ORD) dataset of the reactions reported in:

- **Paper:** Nickel-catalyzed cross-coupling aminations via high-throughput mechanochemistry enabled by resonant acoustic mixing
- **Authors:** Alice Nanni, Deshen Kong, Chen Zhu et al.
- **Published:** Green Chemistry, 2024-01-01
- **DOI:** [10.1039/D4GC01790K](https://doi.org/10.1039/D4GC01790K)
- **ORD wishlist card:** [open on GitHub](https://github.com/orgs/open-reaction-database/projects/11?pane=issue&itemId=126570104)

The reference input `card` holds these facts, the source-data locations and the notes below in machine-readable form.

## Scope

Every 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.

## Source data

Nickel-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.

Known locations:

- [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)
- [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)

## Pitfalls

Mechanochemical (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.

## Deliver

- `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.
- `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.

## Before you start

Open the wishlist card. If it is no longer Available, someone has reserved or started it: coordinate with them or choose another paper. 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.