The brain excels at detecting and processing multiple events rapidly and efficiently to generate appropriate responses. Inspired by this capability, neuromorphic (brain-like) technologies are attracting growing research interest for sensing and in-sensor information processing. Whilst most existing neuromorphic systems still rely on classical digital electronics, photonic approaches are emerging as powerful alternatives due to their inherent advantages, including ultrafast operation, energy efficiency, low crosstalk, high bandwidth, parallelism, and efficient optical communications1,2.
This PhD Studentship will investigate transformative photonic–electronic systems that exploit resonant quantum tunnelling (QT) effects in opto-electronic devices to enable light-powered neuromorphic sensing and in-sensor processing platforms. These systems will combine ultrafast, low-power operation with low SWaP (Size, Weight, and Power) potential and operate at key telecommunication wavelengths (850, 1310, 1550nm) to ensure full compatibility with existing fibre-optic and wireless optical communication and sensor networks.
The research will focus on optoelectronic devices such as photo-detecting resonant tunnelling diodes (RTDs)3-5 and vertical-cavity surface-emitting lasers (VCSELs)6, designed with custom epitaxial layer structures to achieve controllable resonant QT behaviour at room temperatures. These devices will function as artificial photonic–electronic spiking neurons, generating neural-like excitable spikes in response to optical and/or electrical stimuli—mimicking biological neurons but operating up to seven orders of magnitude faster3-6. Their unique dynamics arise from negative differential resistance (NDR) regions in their current–voltage characteristics, produced by QT effects in their structures, which in turn enable controllable nonlinear spiking regimes triggered by optical or electrical perturbations at infrared wavelengths3-6.
Building on these principles, the project will design, fabricate, and characterise neuromorphic photonic–electronic sensing systems capable of converting optical and electrical events into spike-encoded signals at ultrahigh speeds. These systems will represent the first generation of event-based, spike-enabled photonic–electronic technologies for advanced sensing and in-sensor processing applications.
The developed photonic-electronic devices will be integrated with fibre-optic sensing infrastructures, including platforms based upon Fibre Bragg Gratings (FBGs) and Distributed Acoustic Sensors (DAS), using widely deployed fibre-optic telecom networks. This integration will enable fast (nanosecond speeds) and energy-efficient event-based interrogator systems capable of detecting and classifying optical, electrical, and acoustic events (e.g., strain, temperature, turbulence, or RF/audio signals) through their characteristic spike patterns. The systems will also support ultrafast optical communication of event signals to remote receivers via optical wireless or fibre links, opening new possibilities for infrastructure monitoring, fault detection, and security applications.
Practical implementations of this neuromorphic, quantum-enabled photonic–electronic technology will be explored in collaboration with industrial partner Fraunhofer UK, which co-funds this studentship (50%) and provides expertise in fibre-optic and light-enabled sensing technologies. Application areas include energy (e.g., wind farm monitoring), security (e.g., RF/audio detection), and manufacturing (e.g., remote strain, pressure, and temperature sensing).
Finally, the project will also develop neuromorphic algorithms to support the operation and training of the spike-based photonic-electronic sensing systems of the programme7,8. This interdisciplinary research, bridging photonics, quantum tunnelling structures, sensing systems, and neuromorphic technologies, will deliver a new class of ultrafast, energy-efficient photonic sensing and in-sensor processing platforms for remote sensing, smart networks, and edge-computing applications.