Gallium nitride (GaN) electronics

Gallium nitride (GaN)-based high electron mobility transistor (HEMT) technology has made rapid progress over the last 2 decades. These devices are expected to contribute significantly towards efficiency improvement and downsizing of power supplies since the devices have the potential for realizing higher breakdown voltages and lower on-state resistances in comparison to silicon-based devices conventionally used (a projected 100x performance advantage), and to provide unprecedented microwave power amplification (>10x performance advantage over GaAs-based counterparts). Work on this research topic addresses the development of GaN devices technologies for today's applications including electric cars to 5G applications and covers associated circuit design as well.

For more information please follow the link: Gallium Nitride

Terahertz electronics

With the development of terahertz (THz) time-domain spectroscopy in the 1980s and 1990s, the field of terahertz (THz) science and technology has expanded rapidly from fundamental science to 'real world' applications. To fully exploit the unique features of THz radiation and solve arising challenges from all aspects of research to a wide range of applications, our group is working together with other leading THz electronic research groups and industry partners with the aim of providing a transformative THz electronics technology platform which will deliver revolutionising technologies addressing the challenges in the area of Information and Communication Technology (ICT). Our current focus is the development of novel high-resolution THz radar, non-destructive security imaging and ultra-high-speed wireless communications (beyond 5G) systems. The underpinning device technology in this work is the resonant tunnelling diode (RTD).

Neuromorphic circuits

The Internet, the personal computer and the mobile phone have revolutionized our lives. Within the last few decades, computing power has increased exponentially to sustain this transformation. Notably, the recent rise in Artificial Intelligence (AI) systems powered by computers that can learn without the need for explicit instructions is transforming our digital economy and our society as a whole. AI uses brain-inspired neural network algorithms powered by computers. However, these central processing units (CPUs) are extremely energy inefficient at implementing these tasks. This represents a major bottleneck for energy-efficient, scalable and portable AI systems. Reducing the energy consumption of the massively dense interconnects in existing CPUs needed to emulate complex brain functions is a major challenge. Together with other leading groups, our research aims at developing a nanoscale photonics-enabled technology capable of delivering compact, high-bandwidth and energy-efficient CPUs using optically interconnected spiking neuron-like sources and detectors. The underpinning device technology for our approach is the resonant tunnelling diode (RTD).