Supplementary Material 8 for GNN Prediction of 31P NMR Signals

Supplementary material 8 from a research article on predicting 31P Nuclear Magnetic Resonance signals using a light-weight Graph Neural Network. The dataset is published on figshare under a CC-BY-4.0 license by author Dimitri Domnjuk and was last updated on 2026-04-27. The specific content and structure of this supplementary file are not detailed in the available metadata.

Use Cases

• Benchmarking Graph Neural Network architectures for NMR signal prediction (inferred from domain, verify after download)
• Training models to map molecular graphs to 31P NMR chemical shifts (inferred from domain, verify after download)
• Validating computational chemistry methods against experimental spectroscopic data (inferred from domain, verify after download)

Strengths

• Published on the figshare platform with a clear CC-BY-4.0 license.
• File size is 1.4 MB, indicating a manageable download.
• Last update timestamp is 2026-04-27 03:51:03.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count and column definitions are unknown, which may limit suitability assessment.
• The description 'Supplementary material 8' provides no specifics on data content or format.

Provenance

Source

figshare

Collection Method

Likely generated as part of computational research.

Time Range

Publication date is 2026-04-27.

Freshness

Last updated 2026-04-27 03:51:03.

Geography

null