Smart CNT Nanocomposite Sensing Structures for Robotic and Biomedical Systems

Successful applicants will join VinUniversity as Research Assistants / Master’s students at the College of Engineering and Computer Science (CECS), VinUniversity.

📍 Project Information

As robotic and biomedical systems increasingly require safe and adaptive interaction with humans, there is a growing demand for smart materials that can simultaneously provide structural support and sensing capabilities. However, existing solutions often separate these functions, leading to increased system complexity and limited performance.

This project aims to develop a new class of smart materials that combine structural strength with embedded sensing capabilities. The research focuses on carbon nanotube (CNT)-reinforced polymer composites that can detect pressure, strain, and impact directly within the material structure.

A key innovation of the project is the ability to “train” the sensing behavior of the material by adjusting 3D printing conditions, material composition, and internal design—drawing inspiration from neuroplasticity in the human brain. Students will work on developing CNT composites for extrusion-based 3D printing, embedding conductive pathways directly into printed structures, and conducting synchronized mechanical and electrical testing to evaluate performance.

In addition, AI models will be developed to predict sensing behavior based on material and printing parameters, reducing reliance on traditional trial-and-error approaches. The project will deliver practical prototypes, including a robotic gripper pad, a biomedical brace insert, and a helmet liner.

Principal Investigator: Prof. Simon Park

📍 Research Objectives

The project focuses on the following key objectives:

(i) Develop CNT-based composite materials for extrusion-based 3D printing

(ii) Design and embed conductive sensing pathways within printed structures

(iii) Investigate the relationship between mechanical properties and electrical responses

(iv) Develop AI models to predict sensing behavior from material and process parameters

(v) Build application-driven prototypes for robotics, biomedical, and protective systems

Through these efforts, the project aims to enable smart, adaptive materials that enhance safety and performance in human–machine interaction.

📍 Project Contact

For further information about the project, please contact Prof. Simon Park via email [email protected]

Graduate Admissions Contact 

• VinUni Graduate Admissions
•  0978 549 846
• [email protected]

Apply now: https://apply.vinuni.edu.vn/graduate/s/login/ 

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