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In-Materio Reservoir Computing Using Tailored Epitaxial Complex Oxides

Project description

High computational efficiency via epitaxial complex oxides

The ever-increasing power consumption of electronics necessitates energy-efficient solutions. By mimicking the brain's functions, neuromorphic engineering aims to overcome this issue, with reservoir computing being an approach offering flexibility in materials selection. Epitaxial complex oxides, featuring nonlinear properties and adjustable memory, show promise for adaptive reservoir computing. With support from the Marie Skłodowska-Curie Actions programme, the RECOMPUTE project aims to develop reservoir computing devices using thin films of complex oxides. It will combine nickelates, which exhibit tuneable nonlinear negative differential resistance, with relaxor ferroelectrics, which have adjustable memory capacity, in thin-film heterostructures. The project will explore the relationship between material properties and their effectiveness in solving cognitive tasks by creating prototype devices, optimising their electrical properties and simulating their performance.

Objective

The ever-increasing power consumption of electronics necessitates the development of new energy-efficient device paradigms for data storage and computation. In this pursuit, approaches aimed at mimicking the functionality of the human brain in artificial devices, so-called neuromorphic engineering, have attracted a lot of attention. Reservoir computing relying on a random, untrained reservoir provides a powerful platform to exploit materials for brain-inspired computing without strict requirements on the device-to-device variability. Implementing reservoir computing in-materio is, however, challenging because of difficulties to adapt the two main reservoir properties nonlinearity and memory capacity - to computational tasks. Epitaxial complex oxides offer a wealth of nonlinear material properties with tunable memory characteristics, making them ideal candidates for task-adaptive physical reservoir computing.

With RECOMPUTE, I aim to establish in-materio reservoir computing using epitaxial complex oxides to efficiently perform computational tasks. I propose to achieve this by combining in thin-film epitaxial heterostructures (i) rare-earth nickelates with a tunable nonlinear negative differential resistance and (ii) relaxor ferroelectrics with a memory capacity that is tunable via the chemical composition. By fabricating prototypical thin-film devices, characterizing and optimizing their electrical transport characteristics, and simulating their computational performance, I intend to shed light on the fundamental relationship between the intrinsic material properties of reservoir devices and their performance in solving different cognitive tasks a crucial insight that has been elusive so far.

Ultimately, the successful implementation of the proposed research will establish novel reservoir computing devices based on complex oxides and serve as a template for the study of other nonlinear systems for unconventional computing among and beyond complex oxides.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

RIJKSUNIVERSITEIT GRONINGEN
Net EU contribution

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€ 217 076,16
Address
Broerstraat 5
9712CP Groningen
Netherlands

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Activity type
Higher or Secondary Education Establishments
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