Supplementary Data for 31P NMR Prediction with Graph Neural Networks

Supplementary material 2 for a research paper on predicting 31P Nuclear Magnetic Resonance signals using a light-weight Graph Neural Network. The dataset, published on figshare by Dimitri Domnjuk under a CC-BY-4.0 license, is a 258.4 KB IPYNB file. Its last update was recorded on 2026-04-27.

Use Cases

• Reproducing or extending the GNN model for NMR signal prediction (inferred from domain, verify after download)
• Benchmarking graph-based models on molecular chemistry tasks (inferred from domain, verify after download)
• Analyzing the relationship between molecular structure and 31P NMR properties (inferred from domain, verify after download)

Strengths

• Published on the figshare platform with a clear CC-BY-4.0 license.
• Last updated on 2026-04-27 03:51:02.
• File format (IPYNB) suggests executable code or analysis notebooks are included.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count and column definitions are unknown, which may limit suitability assessment.
• The 258.4 KB size indicates a very limited scope, likely containing only supplementary examples or code.

Provenance

Source

figshare

Collection Method

Likely generated as supplementary material for a computational chemistry research paper.

Time Range

Publication date implied by last update in 2026.

Freshness

Last updated 2026-04-27 03:51:02.

Geography

null