Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Zou, Ziyue"'
Molecular dynamics simulations offer detailed insights into atomic motions but face timescale limitations. Enhanced sampling methods have addressed these challenges but even with machine learning, they often rely on pre-selected expert-based features
Externí odkaz:
http://arxiv.org/abs/2409.11843
We investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations reveal that crystallization in the model colloidal system studied here,
Externí odkaz:
http://arxiv.org/abs/2404.17722
Autor:
Zou, Ziyue, Tiwary, Pratyush
In this study, we present a graph neural network-based learning approach using an autoencoder setup to derive low-dimensional variables from features observed in experimental crystal structures. These variables are then biased in enhanced sampling to
Externí odkaz:
http://arxiv.org/abs/2310.07927
Even though nucleation is ubiquitous in different science and engineering problems, investigating nucleation is extremely difficult due to the complicated ranges of time and length scales involved. In this work, we simulate NaCl nucleation in both mo
Externí odkaz:
http://arxiv.org/abs/2309.09284
Understanding nucleation from aqueous solutions is of fundamental importance in a multitude of fields, ranging from materials science to biophysics. The complex solvent-mediated interactions in aqueous solutions hamper the development of a simple phy
Externí odkaz:
http://arxiv.org/abs/2307.13189
Molecular dynamics (MD) enables the study of physical systems with excellent spatiotemporal resolution but suffers from severe time-scale limitations. To address this, enhanced sampling methods have been developed to improve exploration of configurat
Externí odkaz:
http://arxiv.org/abs/2306.09111
With the advent of faster computer processors and especially graphics processing units (GPUs) over the last few decades, the use of data-intensive machine learning (ML) and artificial intelligence (AI) has increased greatly, and the study of crystal
Externí odkaz:
http://arxiv.org/abs/2304.13815
Crystal nucleation is relevant across the domains of fundamental and applied sciences. However, in many cases its mechanism remains unclear due to a lack of temporal or spatial resolution. To gain insights to the molecular details of nucleation, some
Externí odkaz:
http://arxiv.org/abs/2210.04822
Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process as we
Externí odkaz:
http://arxiv.org/abs/2108.10459
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