Publications by authors named "Ziyue Zou"
Article Synopsis
- The study explores crystal nucleation in supersaturated colloid suspensions using advanced molecular dynamics simulations combined with machine learning.
- The simulations show that in the colloidal system, crystallization occurs in a sequence from vapor to dense liquid droplets and then to crystalline phases, overcoming several energy barriers.
- By using a reaction coordinate based on the State Predictive Information Bottleneck, the researchers effectively analyze phase transitions and calculate free energy differences between phases while identifying key molecular features impacting these changes.
Article Synopsis
- - This study introduces a method using a graph neural network (GNN) and an autoencoder to extract low-dimensional representations from features of experimental crystal structures, which helps in analyzing state transitions and thermodynamic properties.
- - The researchers applied their method to examine the nucleation processes of different forms of iron and glycine in their molten states, employing simple convolution and pooling techniques.
- - The results demonstrated that the GNN-derived variables efficiently captured state changes and matched experimental thermodynamic rankings, highlighting the potential of this approach for improved sampling in various systems and techniques.
Article Synopsis
- Molecular dynamics (MD) allows for detailed studies of physical systems but faces challenges with long timescales, prompting the need for enhanced sampling methods to better explore different configurations.
- The integration of machine learning (ML) techniques into enhanced sampling has emerged as a promising solution, leveraging data-driven approaches and synergies between ML and MD.
- This review examines the intersection of ML and MD, detailing successful strategies like dimensionality reduction and reinforcement learning, while also addressing current challenges and open questions in this emerging field.
Article Synopsis
- Nucleation is a complex process that is common in various scientific and engineering contexts, but studying it is challenging due to the wide range of time and length scales involved.
- This research uses advanced molecular dynamics simulations and deep learning to better understand NaCl nucleation in both molten and aqueous environments, focusing on the reaction coordinates that influence nucleation.
- Findings reveal a one-step nucleation mechanism characterized by the role of local ion density, emphasizing that while ion density fluctuations are necessary for nucleation, other factors like enthalpy and local structure are also critical near transition states.
Quantifying the Relevance of Long-Range Forces for Crystal Nucleation in Water.
J Chem Theory Comput
December 2023
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 physical picture, elucidating the roles of different interactions in nucleation processes. In this work, we make use of three complementary techniques to disentangle the role played by short- and long-range interactions in solvent-mediated nucleation.
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- * A survey of 625 college students revealed that factors such as hometown, monthly expenses, and parents’ smoking history significantly affected their tobacco control intentions and behaviors, with performance expectancy and social influence showing direct positive effects.
- * The study suggests that enhancing students' expectations and e-health literacy, fostering supportive social environments, and improving conditions for tobacco control are crucial for curbing smoking rates among non-smokers, while also advocating for smoke-free campus initiatives.
Driving and characterizing nucleation of urea and glycine polymorphs in water.
Proc Natl Acad Sci U S A
February 2023
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 into the molecular details of nucleation, some form of molecular dynamics simulations is typically performed; these simulations, in turn, are limited by their ability to run long enough to sample the nucleation event thoroughly.
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- * The study focuses on urea nucleation from a melt, utilizing a method called spectral gap optimization of order parameters (SGOOP) in combination with well-tempered metadynamics simulations to analyze the process.
- * The findings reveal important insights about the influences of various order parameters on nucleation and provide accurate predictions of phase transitions, which can enhance the understanding of nucleation in complex systems.