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Ferroelectric 2D materials heterostructures for optical neuromorphic device functionalities

Project description

Lighting the way to smarter computing

Traditional computing systems, built on von Neumann architecture, are hitting performance and energy limits as AI and machine learning demands grow. Neuromorphic computing, which is designed to mimic the brain, offers a more efficient alternative, especially when powered by light. The EIC-funded 2DFERROPLEX project aims to overcome current challenges by developing all-optical neuromorphic components using innovative 2D ferroelectric materials. These materials, with properties like tunable polarisation and exciton control, could enable devices that process data at light speed with minimal energy use. By integrating them into photonic neural networks, 2DFERROPLEX aims to create the world’s first optical artificial neuron. This is a major step toward ultra-fast, low-power neuromorphic computing.

Objective

The 2DFERROPLEX project aims to pioneer a new frontier in neuromorphic computing by harnessing the unique properties of two-dimensional (2D) ferroelectric materials to develop all-optical neuromorphic components. Traditional computing architectures, particularly von Neumann-based systems, are increasingly limited in addressing the demands of modern applications like artificial intelligence (AI), machine learning, and edge computing. Neuromorphic systems, which emulate the architecture and functions of the human brain, offer a potential solution by improving computational efficiency, speed, and energy consumption. However, implementing neuromorphic systems in real-world applications, particularly using photonic approaches, remains a challenge. 2DFERROPLEX aims to address these challenges by developing novel materials, devices, and architectures that will enable all-optical control in neuromorphic computing systems, drastically improving computational efficiency and reducing power consumption.
The primary objective of 2DFERROPLEX is to demonstrate how 2D heterostructures can be utilized as key components in all-optical neuromorphic systems. By leveraging the unique properties of 2D ferroelectrics, such as tunable ferroelectric polarization and exciton manipulation, the project seeks to develop devices that operate at the speed of light, thus unlocking an unprecedented level of computational power while minimizing energy consumption. The project also aims to integrate these devices into photonic neural networks, creating the world’s first optical artificial neuron—a fundamental building block for future neuromorphic systems.

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Call for proposal

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(opens in new window) HORIZON-EIC-2024-PATHFINDERCHALLENGES-01

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Coordinator

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 235 077,26
Total cost

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No data

Participants (6)

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