This research develops microscopic copper wire "bridges" that improve heat transfer between computer chips and cooling systems. By reducing chip temperatures by around 3°C, the technology can lower data centre cooling energy by approximately 10%, improving efficiency and supporting more sustainable AI infrastructure.

This research develops brain-inspired computer chips using memristors, devices that can store and process information simultaneously like biological synapses. By enabling in-memory computing, the technology reduces energy consumption while supporting applications such as autonomous robots and image processing. The work advances efficient hardware for future artificial intelligence systems.

This thesis presents the design and verification of a custom RISC-V processor implemented on Field-Programmable Gate Array (FPGA) technology. The project optimized hardware efficiency, achieved stable 50 MHz performance, and enabled software execution using SystemVerilog design and official benchmarks. It demonstrates how open-source hardware enables affordable, customizable computing solutions.