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Ferroelectric REsistors as Emerging Materials for Innovative Neuromorphic Devices

Project description

Nanoscale resistors pave the way for neuromorphic chips for computing

Neuromorphic computing seeks to leverage brain-like and synapse-like architectures and processing to open the door to the brain's amazing potential for computational power, speed, energy efficiency and learning. Ferroelectric materials exhibit a spontaneous polarisation that is reversible by the application of an electric field, making them suitable for memory storage. Ferroelectric resistors have additional benefits with tuneable resistance (and voltage) over a large continuous range that can emulate synapses. The EU-funded FREEMIND project is exploiting nanoscale ferroelectric resistors to realise synapses and neural networks on compact neuromorphic chips.

Objective

Neuromorphic computing such as deep-learning algorithms arise as a promising solution to treat the exploding amount of data generated worldwide, but at the cost of expensive time and energy budget on conventional hardware. There is an urgent need for a low-power, compact neuromorphic chip that can support bio-inspired computing: a network of cells collocating storage (non-volatility) and computing (synaptic plasticity). This work proposes to achieve such cell using a ferroelectric resistor, down-scaled to nanometer thickness to allow direct electron tunneling through the ferroelectric barrier (ferroelectric tunnel junction): the learning functionality (i.e. synaptic plasticity) will be implemented through the control of the distribution of the (non-volatile) ferroelectric domains. The fellow will bring her expertise in ferroelectric tunnel junctions and will combine it with IBM’s expertise in device and circuits integration and characterization, making use of the state-of-the-art equipment offered by their research center. In order to accelerate the creation of an end-to-end neuromorphic device, she will lead a collaboration with ETH Zurich and will benefit from their expertise in predictive physics-based modeling. The research project will aim at: (i) the demonstration of a non-volatile and plastic ferroelectric “synapse” made of Hf0.5Zr0.5O2 – a fully CMOS-compatible material, (ii) the development of models of individual cells and of a neural network and (iii) providing design guidelines for neuromorphic hardware based on this technology. The outcome will be to evaluate performances not only of individual synapses but of a neural network as a whole. Through the Action, the fellow will not only aim at creating a novel technology; but also at leading an interdisciplinary research project uniting complementary actors for an innovative solution to a society challenge.

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MSCA-IF-EF-SE - Society and Enterprise panel

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(opens in new window) H2020-MSCA-IF-2018

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Coordinator

IBM RESEARCH GMBH
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.

€ 191 149,44
Address
SAEUMERSTRASSE 4
8803 RUESCHLIKON
Switzerland

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Region
Schweiz/Suisse/Svizzera Nordwestschweiz Aargau
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 191 149,44
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