Active Computing & AI Clean Energy

Solar Cells-Inspired Inorganic Semiconductor Synaptic Systems for Low Energy Edge Computing and Visual Learning

In plain English

AI plain-English summary

Solar cells that normally harvest light are being repurposed as artificial brain cells that learn from what they see. Today’s computers struggle with the energy demands of artificial intelligence because they separate memory and processing, forcing data to shuttle back and forth. The SOLIS project tackles this by turning inorganic thin-film materials—the same stable, tunable semiconductors used in photovoltaics—into optical memristors that both store and process information. These materials exhibit persistent photoconductivity, meaning they remember light exposure, which mimics how biological synapses strengthen or weaken connections. The consortium brings together photovoltaic and materials experts to develop hardware that learns directly from visual input, bypassing the need for separate cameras and processors. If successful, this could transform edge computing—the small devices that process data locally rather than in the cloud. A security camera, for instance, could recognise a person without sending video to a remote server, saving energy and bandwidth. The project also aims to establish a shared framework for characterising these optical synapses, accelerating the field. While the work is still fundamental materials science, it opens a path toward hardware-level machine learning that is faster, more efficient, and free from the constraints of conventional computer architecture.

View original technical description
The rapidly expanding field of artificial intelligence (AI) and machine learning exposes the limitations of conventional Von Neumann architecture. Neuromorphic computing, inspired by the highly energy efficient functionning of the brain, has emerged as a solution for efficient unsupervised learning, particularly relevant qith the advent of edge computing and visual computing applications. Solar cell-inspired materials, offering persistent photoconductivity allowing to simulate synaptic plasticity, have the potential to revolutionise neuromorphic visual computing. The SOLIS project forms an international consortium of experts from photovoltaics and materials science to explore inorganic thin film materials' potential as artificial visual synapses. These materials, tuneable and stable, promise reliable optically controlled MEMRISTORS suitable for diverse light intensities and wavelenghts. The collaboration, emphasising staff exchanges and transparent sharing of data, methods and persons, aims to reinforce our understanding, innovate with materials like 2D MXenes, and establish a shared framework for optoelectronic characterisation of visual synapses. The project aligns with Europe's objective to catch up in the field of AI and possibly become a leader in hardware-level machine learning, offering opportunities for scientists from Third Countries and EU countries alike. SOLIS will be an important milestone for EU research and the PV field as a whole, unlocking new applications for inorganic thin film materials and offering a paradigm shift toward visual computing and AI free from the constraints of current materials and architectures.

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Researchers

Jonathan Major (Principal Investigator)Ken Durose (Co-Investigator)Laurie Phillips (Co-Investigator)

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Original classification

Research and Innovation

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