Research
Our research focuses on theoretical predictions of the glass transition using various model potentials. We explore monocomponent systems, mixtures, and non-spherical particles.
Monocomponent Systems:
Repulsive Interactions:
We investigate models such as Hard Spheres (HS), Weeks-Chandler-Andersen (WCA), and Hard Sphere Repulsive Yukawa (HSRY) to understand how purely repulsive forces affect the glass transition.
Attractive Interactions:
Our analysis includes models like Hard Spheres Square Well (HSSW), Hard Sphere Attractive Yukawa (HSAY), and Lennard-Jones (LJ), which incorporate attractive forces to see how they influence the transition into a gel or glassy state.
Competitive Interactions (HOT TOPIC):
We characterize systems with short-range attraction plus long-range repulsions through a hard sphere double Yukawa (HSDY) potential. This study aims to characterize the complex interplay of these forces.
Mixtures:
Repulsive Interactions:
We study systems such as Hard Spheres (HS) to understand how repulsive interactions between different species affect the overall behavior of the mixture.
Attractive Interactions (HOT TOPIC):
Investigating mixtures with the primitive model (PM) and Asakura-Oosawa (AO) model, we examine how attractive interactions between different components can lead to complex glassy behaviors.
Non-Spherical Particles:
Dipoles:
We explore the behavior and properties of dipolar particles in various conditions to see how their shape and interaction anisotropy affect their properties.
We delve into the fundamentals of non-equilibrium thermodynamics to understand how systems evolve over time when driven out of equilibrium.
Non-Equilibrium Onsager-Machlup (HOT TOPIC):
This research focuses on extending the Onsager-Machlup theory, which originally described fluctuations in equilibrium, to non-equilibrium systems. We aim to develop a stochastic thermodynamic framework that can accurately describe irreversible processes and predict system behavior far from equilibrium.
Time-Temperature Transformation Diagrams (TTTD):
We develop and utilize TTTDs to map out the relationship between time, temperature, and the structural transformation of materials. These diagrams help predict the conditions under which materials will undergo specific transformations, aiding in the design of materials with desired properties.
Rheology (HOT TOPIC):
Rheological properties, especially under non-equilibrium conditions, are a major focus. We investigate:
Viscosity:
Studying the viscosity behavior of different materials helps us understand how their flow properties change under various conditions.
Angell Plots:
We use Angell plots to analyze the temperature dependence of viscosity, providing insights into the fragility and stability of materials as they approach the glass transition.
Elastic Moduli (G' and G''): By investigating the storage (G') and loss (G'') moduli, we gain a deeper understanding of the elastic and viscous behavior of materials under stress.
Our theory generates extensive data, necessitating sophisticated methods for effective physical analysis. We employ various techniques to present and interpret these results.
Machine Learning (HOT TOPIC):
We apply machine learning techniques to analyze and predict material behavior based on the vast amounts of data generated by our theoretical models. Machine learning helps identify patterns and correlations that might not be immediately evident through traditional analysis methods.
Preparation Protocols:
Instantaneous (Quenches, Crunches):
We study the effects of rapid changes in conditions, such as sudden temperature drops (quenches) or pressure changes (crunches), to understand how these affect the structural and dynamic properties of materials.
Cooling Rates (HOT TOPIC): Investigating the impact of different cooling rates, we aim to determine how the rate at which a material is cooled affects its final structure and properties, providing insights into optimizing processing techniques.
Isobaric Process: Examining the effects of maintaining constant pressure during material processing helps us understand how pressure influences the structural and dynamic properties of materials during transformation.
This research framework outlines our comprehensive approach to understanding complex material behaviors through both theoretical and applied studies.