Supplementary Material 7 for 31P NMR Prediction with Graph Neural Networks

A 3.6 MB supplementary file published on figshare by Dimitri Domnjuk on 2026-04-27. The file is an IPYNB notebook likely containing code, data, or analysis supporting a research paper on predicting 31P Nuclear Magnetic Resonance signals using a light-weight Graph Neural Network. The specific data content and structure require verification after download.

Use Cases

• Reproducing or extending the GNN-based NMR signal prediction methodology (inferred from domain, verify after download)
• Analyzing the structure-property relationships for phosphorus-containing molecules (inferred from domain, verify after download)
• Benchmarking lightweight GNN architectures on quantum chemical tasks (inferred from domain, verify after download)

Strengths

• Published under the permissive CC-BY-4.0 license.
• File size is precisely 3.6 MB.
• Last updated on 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 7' provides no details on the notebook's specific contents.

Provenance

Source

figshare

Collection Method

Likely generated as part of academic research.

Time Range

Publication date is 2026-04-27; data collection period is unknown.

Freshness

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

Geography

null