Mechanical properties and cage transformations in CO2-CH4 heterohydrates: a molecular dynamics and machine learning study

笼子 分子动力学 动力学(音乐) 计算机科学 化学 化学物理 物理 计算化学 数学 组合数学 声学
作者
Yu Zhang,Xintong Liu,Qiao Shi,Yongxiao Qu,Yongchao Hao,Yuequn Fu,Jianyang Wu,Zhisen Zhang
出处
期刊:Journal of Physics D [Institute of Physics]
卷期号:57 (46): 465302-465302 被引量:5
标识
DOI:10.1088/1361-6463/ad6dcf
摘要

Abstract The substitution of natural gas hydrates with CO 2 offers a compelling dual advantage by enabling the extracting of CH 4 while simultaneously sequestering CO 2 . This process, however, is intricately tied to the mechanical stability of CO 2 -CH 4 heterohydrates. In this study, we report the mechanical properties and cage transformations in CO 2 -CH 4 heterohydrates subjected to uniaxial straining via molecular dynamics (MD) simulations and machine learning (ML). Results indicate that guest molecule occupancy, the ratio of CO 2 to CH 4 and their spatial arrangements within heterohydrate structure greatly dictate the mechanical properties of CO 2 –CH 4 heterohydrates including Young’s modulus, tensile strength, and critical strain. Notable, the introduction of CO 2 within clathrate cages, particularly within 5 12 small cages, weakens the stability of CO 2 –CH 4 heterohydrates in terms of mechanical properties. Upon critical strains, unconventional clathrate cages form, contributing to loading stress oscillation before fracture of heterohydrates. Intriguingly, predominant cage transformations, such as 5 12 6 2 –4 1 5 10 6 3 or 4 2 5 8 6 4 and 5 12 –4 2 5 8 6 1 cages, are identified, in which 4 1 5 10 6 2 appears as primary intermediate cage that is able to transform into 4 1 5 10 6 3 , 4 2 5 8 6 2 , 4 2 5 8 6 3 , 5 12 and 5 12 6 2 cages, unveiling the dynamic nature of heterohydrate structures under straining. Additionally, ML models developed using MD data well predict the mechanical properties of heterohydrates, and underscore the critical influence of the spatial arrangement of guest molecules on the mechanical properties. These newly-developed ML models serve as valuable tools for accurately predicting the mechanical properties of heterohydrates. This study provides fresh insights into the mechanical properties and cage transformations in heterohydrates in response to strain, holding significant implications for environmentally sustainable utilization of CO 2 –CH 4 heterohydrates.

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