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TRACE: A Topological Algorithm for Detecting Additive-Coordinated Hydrate Cages.

Jun-Wei Hsu1, Shiang-Tai Lin1

  • 1Department of Chemical Engineering, National Taiwan University, Taipei 106319, Taiwan.

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|November 14, 2025
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Summary
This summary is machine-generated.

A new algorithm, TRACE, identifies cage structures in clathrate hydrates, crucial for understanding climate mitigation and energy technologies. It tracks how additives influence hydrate formation and nucleation kinetics.

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Area of Science:

  • Materials Science
  • Chemical Engineering
  • Computational Chemistry

Background:

  • Clathrate hydrates are vital for climate mitigation, energy resources, and carbon capture and storage (CCS) due to their gas storage capacity.
  • Understanding hydrate cage structures in molecular simulations is key to studying nucleation and growth mechanisms.

Purpose of the Study:

  • Introduce TRACE (Topological Ring and Additive-Coordinated Cage Explorer), a novel open-source algorithm for detecting and classifying hydrate cage structures.
  • Enable the investigation of additive effects on hydrate formation by incorporating them into the cage identification process.

Main Methods:

  • Developed TRACE, an algorithm for detecting and classifying structural motifs (rings, cups, cages) in molecular dynamics simulations of hydrate nucleation.
  • Validated TRACE using CO2 hydrate systems with urea, a kinetic promoter.
  • Quantified cage statistics, lifetimes, additive retention times, and nucleation kinetics using mean first-passage time (MFPT) analysis.

Main Results:

  • TRACE successfully detects and classifies various cage structures formed during hydrate nucleation.
  • The algorithm quantified the impact of urea on CO2 hydrate nucleation kinetics and structural evolution.
  • Demonstrated TRACE's ability to track structural changes and additive retention over time.

Conclusions:

  • TRACE provides a robust tool for characterizing microstructural development in clathrate hydrate formation.
  • The algorithm offers new insights into additive-modulated nucleation pathways by bridging structural and kinetic information.
  • TRACE is well-suited for studying the role of additives in hydrate formation for applications like CCS.