Summary
The digitalization of the world and the rise of the Big-Data era continuously push towards improved computing capabilities able to sustain new and complex functionalities. Traditional computer architectures based on the Von Neumann model present limitations when dealing with rapidly growing technologies such artificial intelligence, since to low access speed between the separated memory and CPU inevitably leads to low processing capabilities and high energy consumptions. A possible solution to overcome these limitations is the development of non-volatile memories (NVMs) as element with both storage and logic capabilities, enabling the computation of tasks directly on the memory unit (in-memory computing). MagnOxy aims at developing a novel solid state battery-like NVM based on the control of magnetic properties of functional oxide thin films through a fast (de)intercalation of oxygen ions. The control of magnetism through the reversible (de)intercalation of ions into a target material, mediated by the application of an electrical bias through an ionic electrolyte (i.e. magneto-ionics, MI) is the most recent approach for controlling magnetism by voltage. MI-based magneto-electric random-access memories (MeRAM) have the potential to deliver robust, fast and energy efficient NVMs for in-memory computing. However, MI control is still at an early stage of the R&D process and many aspects still needs to be improved to deliver a competitive device. In essence, MagnOxy will provide: i) A solid state thin film device based on the electrochemical insertion of oxygen ions at RT ii) A large and analogically tuneable magnetic response of the cell ii) A fast (~100 ms) magnetic switching capabilities through the implementation of nanoionics concept for boosting ionic motion iii) An improved understanding of the oxygen-ion intercalation mechanisms in oxide perovskite thin films iv) Device scalability and miniaturization.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101107093 |
| Start date: | 01-01-2024 |
| End date: | 31-12-2025 |
| Total budget - Public funding: | - 181 152,00 Euro |
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Original description
The digitalization of the world and the rise of the Big-Data era continuously push towards improved computing capabilities able to sustain new and complex functionalities. Traditional computer architectures based on the Von Neumann model present limitations when dealing with rapidly growing technologies such artificial intelligence, since to low access speed between the separated memory and CPU inevitably leads to low processing capabilities and high energy consumptions. A possible solution to overcome these limitations is the development of non-volatile memories (NVMs) as element with both storage and logic capabilities, enabling the computation of tasks directly on the memory unit (in-memory computing). MagnOxy aims at developing a novel solid state battery-like NVM based on the control of magnetic properties of functional oxide thin films through a fast (de)intercalation of oxygen ions. The control of magnetism through the reversible (de)intercalation of ions into a target material, mediated by the application of an electrical bias through an ionic electrolyte (i.e. magneto-ionics, MI) is the most recent approach for controlling magnetism by voltage. MI-based magneto-electric random-access memories (MeRAM) have the potential to deliver robust, fast and energy efficient NVMs for in-memory computing. However, MI control is still at an early stage of the R&D process and many aspects still needs to be improved to deliver a competitive device. In essence, MagnOxy will provide: i) A solid state thin film device based on the electrochemical insertion of oxygen ions at RT ii) A large and analogically tuneable magnetic response of the cell ii) A fast (~100 ms) magnetic switching capabilities through the implementation of nanoionics concept for boosting ionic motion iii) An improved understanding of the oxygen-ion intercalation mechanisms in oxide perovskite thin films iv) Device scalability and miniaturization.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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