46 citations · 100 across the 9 of their papers we have counts for
9 papers
Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics
Ziyue Zou, Dedi Wang, Pratyush Tiwary
Molecular dynamics simulations offer detailed insights into atomic motions but face timescale limitations. Enhanced sampling methods have addressed these challenges but even with m…
Simulating Crystallization in a Colloidal System Using State Predictive Information Bottleneck based Enhanced Sampling
Vanessa J. Meraz, Ziyue Zou, Pratyush Tiwary
We investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations re…
Enhanced sampling of Crystal Nucleation with Graph Representation Learnt Variables
Ziyue Zou, Pratyush Tiwary
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 cryst…
Is the Local Ion Density Sufficient to Drive NaCl Nucleation from the Melt and Aqueous Solution?
Ruiyu Wang, Shams Mehdi, Ziyue Zou +1
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…
Quantifying the relevance of long-range forces for crystal nucleation in water
Renjie Zhao, Ziyue Zou, John D. Weeks +1
Understanding nucleation from aqueous solutions is of fundamental importance in a multitude of fields, ranging from materials science to biophysics. The complex solvent-mediated in…
Enhanced Sampling with Machine Learning: A Review
Shams Mehdi, Zachary Smith, Lukas Herron +2
Molecular dynamics (MD) enables the study of physical systems with excellent spatiotemporal resolution but suffers from severe time-scale limitations. To address this, enhanced sam…