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Active HORIZON European Commission

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


Funder European Commission
Recipient Organization Universitat Politecnica de Catalunya
Country Spain
Start Date Apr 01, 2025
End Date Mar 31, 2029
Duration 1,460 days
Number of Grantees 8
Roles Participant; Associated Partner; Coordinator
Data Source European Commission
Grant ID 101183049
Grant 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.

All Grantees

Universita Degli Studi Di Verona; The Ritsumeikan Trust Academic Juridical Person; University of the Philippines Diliman; Universitat Politecnica de Catalunya; Moroccan Foundation for Advanced Science Innovation and Researchfondation Mascir; The University of Liverpool; University of the Western Cape; Tallinna Tehnikaülikool

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