Supplementary material 5 for a research paper on predicting 31P Nuclear Magnetic Resonance signals using a light-weight Graph Neural Network. The dataset is a 1.6 MB CSV file published on figshare by Dimitri Domnjuk under a CC-BY-4.0 license and last updated on 2026-04-27. Its specific content and row count are not detailed in the provided metadata.
Use Cases
- Benchmarking GNN architectures for NMR property prediction (inferred from domain, verify after download)
- Training models to map molecular structures to 31P NMR chemical shifts (inferred from domain, verify after download)
- Validating computational chemistry methods against experimental NMR data (inferred from domain, verify after download)
Strengths
- Published on figshare with a clear CC-BY-4.0 license.
- File size is 1.6 MB, indicating a manageable download.
- Last update timestamp is explicitly provided: 2026-04-27 03:51:03.
Limitations
- Metadata is minimal; actual content requires verification after download.
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
Provenance
- Source
- figshare
- Collection Method
- Likely generated as supplementary data for a computational chemistry research paper.
- Time Range
- null
- Freshness
- Last updated 2026-04-27 03:51:03; freshness should be verified.
- Geography
- null