Predicting the properties of bitumen using machine learning models trained with force field atom types and molecular dynamics simulations

Assaf, Eli I.; Liu, Xueyan; Lin, Peng; Ren, Shisong; Erkens, Sandra

doi:10.1016/j.matdes.2024.113327

Materials & Design

2024

DOI: 10.1016/j.matdes.2024.113327

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Predicting the properties of bitumen using machine learning models trained with force field atom types and molecular dynamics simulations

Eli I. Assaf,

Xueyan Liu,

Peng Lin

et al.

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Predicting the properties of bitumen using machine learning models trained with force field atom types and molecular dynamics simulations

Cited by 2 publications

References 46 publications

Subsurface amorphization-induced ultrasmooth and ultrahard surface during the diamond turning of polycrystalline pure copper

Subsurface amorphization-induced ultrasmooth and ultrahard surface during the diamond turning of polycrystalline pure copper

Predicting the dynamic moduli and viscosities of bitumens via oscillatory strain-controlled molecular simulations

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