Understanding the relationship between atomic structure and relaxation dynamics is essential for revealing the physical behavior of metallic glasses. In this work, we integrate molecular dynamics simulations, Elastically Collective Nonlinear Langevin Equation theory, and artificial intelligence to investigate both th...
Hanh Bich Vu, Ngo T. Que, Anh D. Phan· Journal of Physical Chemistr...· 0 citations
We combine machine learning and theoretical modelling to predict and analyze the thermal and molecular dynamics properties of metallic glasses. First, we use machine learning models to estimate the glass transition temperature (Tg) from alloy compositions. Our approach uses the most minimal input features to date, simp...
Ngo T. Que, Hanh Bich Vu, Nguyen T. T. Duyen et al.· Journal of Physics, Conferen...· 0 citations
This study explores data-driven approaches for predicting the thermal decomposition temperature of polymers using both classical machine learning (CML) models and a small language model (SLM), suggesting that small language models can serve as a valuable alternative modeling strategy for predicting polymer thermal prop...
Nguyen T. T. Duyen, Ngo T. Que, Hanh Bich Vu· Journal of Physics, Conferen...· 0 citations
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