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Intelligent Design of Autonomous Materials

The Group on Intelligent Design of Autonomous Materials welcomes competitive and enthusiastic applicants to conduct cutting-edge research at HKUST in Hong Kong. Interested persons with theoretical or computational background in Applied Mathematics, Physics, Biophysics, Materials Science, Mechanical Engineering, or Chemical Engineering are encouraged to send enquiries to Rui's email address at

ruizhang@ust.hk

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Our Research

Our society is currently facing unprecedented challenges in health, energy, and the environment, which have created a strong demand in new materials which are renewable, multifunctional, light-weight, and can interact with human more safely and intelligently. Soft materials are a promising candidate for this purpose. The overarching goal of the our Group is to harness soft materials, such as active matter, liquid crystals, polymers, colloids, metamaterials, and their composites to design next-generation, autonomous materials and soft machines.

Specifically, our group will employ traditional and emerging computational methods, including machine learning, to propose novel soft materials with nontraditional functionalities, features, and dynamics. Examples include active fluids with tailorable flow patterns, multiphase systems sensitive to specific stimuli, and origami materials with novel shape-changing behaviors in response to external fields. These new soft materials are promising for soft robotics, wearable devices, space exploration, 4D printing, energy harvesting, smart buildings, sensing and diagnosis, and etc.

 

Our group strives to borrow the wisdom from biological systems and design synthetic materials and machines that are low-cost, green, biocompatible, and intelligent. Our research is multidisciplinary, covering Physics, Biology, Chemistry, Materials Science, Chemical and Mechanical Engineering.

Universality of Dynamic Flow Structures in Active Viscoelastic Liquids

Zhe Feng, Tiezheng Qian and Rui Zhang#

Journal of Fluid Mechanics – Accepted

Active fluids encompass a wide range of non-equilibrium fluids, in which the self-propulsion or rotation of their units can give rise to large-scale spontaneous flows. Despite the diversity of active fluids, they are commonly viscoelastic. Therefore, we develop a hydrodynamic model of isotropic active liquids by accounting for their viscoelasticity. Specifically, we incorporate an active stress term into a general viscoelastic liquid model to study the spontaneous flow states and their transitions in two-dimensional channel, annulus, and disk geometries. We have discovered rich spontaneous flow states in a channel as a function of activity and Weissenberg number, including unidirectional flow, traveling wave, and vortex-roll states. The Weissenberg number acts against activity by suppressing the spontaneous flow. In an annulus confinement, we find that a net flow can be generated only if the aspect ratio of the annulus is not too large nor too small, akin to some three-dimensional active flow phenomena. In a disk geometry, we observe a periodic chirality-switching of a single vortex flow, resembling the bacteria-based active fluid experiments. The two phenomena reproduced in our model differ in Weissenberg number and frictional coefficient. As such, our active viscoelastic model offers a unified framework to elucidate diverse active liquids, uncover their connections, and highlight the universality of dynamic active-flow patterns.

The Intelligent Design of Autonomous Materials Group is proudly supported by the Research Grants Council of Hong Kong, Guangdong Natural Science Foundation, and ASPIRE League.

The Hong Kong University of Science and Technology

(852) 2358 5734

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