Skip to main content
    • Aa
    • Aa

Energy science of clathrate hydrates: Simulation-based advances

  • Amadeu K. Sum (a1), David T. Wu (a2) and Kenji Yasuoka (a3)

The energy science of clathrate hydrates is a rapidly expanding field, with high-performance computing (HPC) playing an ever-growing role to help understand the molecular processes and properties that drive clathrate hydrates to nucleate and grow into crystalline, amorphous, or mixed structures, their non-stoichiometric nature upon formation, the formation mechanism from homogeneous and heterogeneous nucleation, and their stability and limits of metastability. Many of the questions that HPC can help to answer about hydrates are intractable experimentally because of the difficulty of measurements at the length (nanometers) and time (nanoseconds) scales imposed by the fundamental phenomena at the molecular level. At the same time, the length and time scales that are accessible by simulations pose limitations on what can be studied (e.g., phase equilibria and metastability, nucleation mechanisms, non-stoichiometry) and how it can be studied (e.g., Monte Carlo, molecular dynamics, metadynamics, transition path sampling, thermodynamic integration). Ultimately, the energy science of clathrate hydrates will benefit from HPC by gaining insight into the detailed mechanism for formation, dissociation, and stability.

Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

9. J.H. van der Waals , J.C. Platteeuw , Adv. Chem. Phys. 2, 1 (1959).

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

MRS Bulletin
  • ISSN: 0883-7694
  • EISSN: 1938-1425
  • URL: /core/journals/mrs-bulletin
Please enter your name
Please enter a valid email address
Who would you like to send this to? *


Full text views

Total number of HTML views: 7
Total number of PDF views: 21 *
Loading metrics...

Abstract views

Total abstract views: 118 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 20th August 2017. This data will be updated every 24 hours.