Optoelectronic Artificial Synapses Using Solar Cell Materials for Neuromorphic Computing

Description

Neuromorphic computing¹ emulates human brain functions to surpass the traditional von Neumann architecture's computational efficiency limitations. Unlike typical binary systems, neuromorphic systems use spike inputs where information is encoded based on the signal's timing, shape, and magnitude. Key to this technology are artificial synapses, which have been developed using a range of approaches based on phase-change materials, memristors, and ion-exchange mechanisms. Artificial optoelectronic synapses convert light directly into current, providing advantages in robotics and AI due to their low energy use and wavelength sensitivity ². This is very similar to function of photovoltaic (PV) semiconductor materials, which are specifically designed to convert light into current. Particular materials, used as the basis of emerging low-cost solar cell technologies, such as antimony chalcogenides or perovskite materials, also exhibit the property of persistent photoconductivity. This enables current signals to be stored for extended durations, from seconds to weeks, mimicking the action of either long-term or short-term memory. This means there is an opportunity to redevelop these solar cell materials as artificial optoelectronic synapses.

 The Major Research Group at the University of Liverpool (UoL) is the leading European group working on antimony chalcogenide materials for next generation thin-film solar cells³. Because they can be fabricated by a range of industrially scalable deposition techniques, it makes these materials an exceptional choice for low-cost optoelectronic synapses, as well as PV. The analysis, materials optimisation and device development expertise honed over years of PV research al UoL, will be redeployed as a new approach to the challenge of developing these key building blocks of neural networks. This project will adapt existing solar cell technology, processes and characterisation methodologies at UoL to develop novel high-performance, low-cost artificial optoelectronic synapses. The aim will be to establish the key factors controlling synaptic plasticity⁴ via in-depth analysis of device performance linked to core materials properties.

The successful applicant will be based in UoL’s Stephenson Institute for Renewable Energy (SIRE) a multidisciplinary research centre focussed on the materials science of renewable energy technologies. They will work as part of the Major Research Group becoming an expert in thin film deposition and device fabrication, as well as in associated structural, optical and electronic analysis techniques. They will gain hands on experience in both thin film PV and artificial synapses giving them a unique perspective and range of skills This PhD will provide the student with enhanced training opportunities via the recently funded “SOLIS: Solar Cells-Inspired Inorganic Semiconductor Synaptic Systems for Low Energy Edge Computing and Visual Learning” a Marie Curie Staff Exchange Network (MC-SEN) which runs until April 2029. The student will be able to undertake research placements at some of our partner laboratories in Barcelona, Kyoto, Cape Town, Tallinn, Verona, Manilla and Rabat to receive experimental training from experts in solar cells, materials synthesis and artificial synapses. They will also have additional opportunities for collaboration with visiting scientists from the same laboratories, as well as to contribute to project meetings and to present at international conferences. Additionally, they will be involved with the RENEW-PV Co-operation in Science and Technology (COST) action network (https://renewpv.eu/). This is a network of over 200 scientists from >35 countries working on thin-film PV for which Dr Major is the Science and Communication coordinator. The student will have access to regular training events and network meetings/events to interact with leading international solar cell researchers.

Please quote reference PPPR073 when applying.

Please contact Dr Major (jon.major@liverpool.ac.uk) if you require further information on the project or wish to discuss and application.