Project Ideas

Unlock the power of memristive technology for ultra-high dense data storage, arithmetic logic, AI hardware, sensors, and security applications.

Memristor-based Random Number Generator

This project aims to examine the reliability of memristor devices for random number generator applications. Memristor (resistor with memory) is a programmable two-terminal sandwich structure electronic device (metal/insulator/metal) that can retain its bit value (binary digit, “1” or “0”) without the necessity of continuous power, unlike SRAM/DRAM.

Become part of our community and collaborate on groundbreaking research projects that inspire and challenge the status quo.

Your contributions can make a significant impact in your area of expertise.

Memristor-based Arithmetic Logic Units

The realisation of logic functions using memristor could significantly reduce computing power consumption. In this project, the student will design ALU circuits based on memristors experimental electrical data.

Memristor for data storage applications

Memristor brings promise as a universal memory technology that could replace conventional technologies in the market today. Memristor offers an opportunity to realise ultra-dense memory due to its feasibility of being integrated with a diode instead of a transistor, maintaining its integrated cell size to 4F^2.

Silicon synapses for artificial intelligence hardware

This project aims to develop neuromorphic chips for artificial intelligence (AI) hardware accelerators. You will exploit the architecture of memristive technologies to deliver faster, smaller, and lower-powered AI chips than the conventional chips that gadgets currently use. The final objective of this project is to build an application demonstrator employing AI chips to run neuromorphic computations on a field programmable gate array (FPGA).

Electrical and chemical modelling of memristive synapses

Memristor nanodevices are capable of mimicking neurons' communication through synaptic plasticity. You will design a massive array of fully functional memristor prototypes and simulate how diffusion and drift of ions/defects could lead to synaptic plasticity. The final objective of this project is to model the impact of materials and electrical parameters on plasticity behaviour.