Coal-DOM Molecular Fingerprints Under Simulated Geothermal Conditions

Supplementary tables and raw data from a study on the thermal evolution of coal-derived dissolved organic matter (Coal-DOM). The dataset, authored by Peng Ge and shared under CC-BY-4.0, includes results from experiments simulating geothermal conditions at 25 and 50°C on coals of different ranks. It was last updated on 2026-05-08.

Use Cases

• Predicting thermal reactivity of dissolved organic matter based on key molecular descriptors like O/C ratio and AI_mod.
• Identifying water sources in deep coal mines using quantifiable organic fingerprints that complement conventional indicators.
• Tracing water-inrush pathways by analyzing rank-specific molecular transformation pathways under geothermal perturbation.
• Training interpretable machine learning models (e.g., XGBoost-SHAP) on molecular data from ultrahigh-resolution mass spectrometry.

Strengths

• Data is derived from controlled experiments simulating two distinct geothermal temperatures (25°C and 50°C).
• Analysis integrates ultrahigh-resolution mass spectrometry (FT-ICR MS) with an interpretable machine learning framework.
• Dataset is shared under a permissive CC-BY-4.0 license, facilitating reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 9.6 MB file size suggests a relatively small dataset.

Provenance

Source

Peng Ge via figshare

Collection Method

Laboratory experiments on coal samples under simulated geothermal conditions, analyzed with FT-ICR MS and machine learning.

Freshness

Last updated 2026-05-08 17:23:09; freshness should be verified.