Statistical and physical principles for the prediction of complex system behaviors
Project Description
Real-world condensed phases usually exhibit both solid-like (elastic) and fluid-like (viscous) behaviors. Examples include tooth pastes, honey and cornstarch suspensions. Crystals and ideal liquids have been relatively well studied. Viscoelastic materials are, however, more challenging. Moreover, many biological fluids, such as biofilms, cytoplasm, and bacteria suspensions, are active in the sense that chemical energy is converted into locomotion of motor proteins or bacteria, rendering the system in a nonequilibrium state. In this project, we seek to understand and model a range of active viscoelastic materials using particle-based and continuum simulations. Through the development of active viscoelastic models, we will be able to reproduce biofluids phenomena and make predictions that await future experimental work.
Supervisor
ZHANG, Rui
Co-Supervisor
LI, Sai Ping
Quota
1
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
The applicant is supposed to learn and apply statistical and physical models to analyze real world systems in terms of complex networks. The project involves literature reading, using Python and other programming language to process data and perform scientific computations.
Applicant's Learning Objectives
1. Understanding of the basic concepts of complex networks.
2. Understanding of percolation theory and time series analysis.
3. Processing and analyzing artificial and real-world data using percolation theory and time series analysis.

Complexity of the project
Moderate