Voltage-Reconfigurable Magnetic Invisibility: A New Concept for Data Security Based on Engineered Magnetoelectric Materials
REMINDS aims to revolutionize data security by using voltage to manipulate magnetism at the material level, enabling energy-efficient, hidden data storage and retrieval with potential anti-counterfeiting applications.
Projectdetails
Introduction
With the advent of Big Data, information is facing new, potentially more damaging, security threats. The current trend to enhance data protection is to use increasingly complex mathematical algorithms to encrypt information. This approach requires exponentially growing amounts of data, time, and power resources.
Project Overview
REMINDS proposes a radically new concept to boost data security: to act directly at the material level, i.e., in the way information is stored. The project is built on the disruptive idea of using voltage to activate/deactivate magnetism via strain or ion migration effects. It tackles novel strategies to control the mutual interactions between ferromagnetic (FM), antiferromagnetic (AFM), and ferroelectric (FE) materials.
Technical Challenges
While data written in ferromagnets can be read using conventional heads, AFM and FE materials are ‘invisible’ to magnetic sensors due to their lack of magnetic stray fields. Methods to read sub-200 nm AFM or FE domains are complex and often destructive.
Development Goals
REMINDS will develop advanced engineering protocols to:
- Transfer information from FM to AFM or FE materials.
- Keep the data ‘hidden’ in the AFM or FE layers while the FM state is switched off.
- Retrieve the information whenever deemed necessary.
Implementation Strategy
Neuromorphic-inspired layouts will be used to selectively apply these protocols to specific memory units that will incorporate stochastic physical phenomena. This will be the basis of new energy-efficient proof-of-concept data protection designs.
Testing and Applications
The working principle will be tested at lab scale for potential applications in anti-counterfeiting and anti-hacking technologies. REMINDS is expected to revolutionize magnetoelectricity, exploiting voltage-programmable magnetism to an unprecedented extent and forging an entirely new paradigm in data security.
Expected Outcomes
Its outcomes will bring ground-breaking scientific contributions to the fields of magnetism, spintronics, piezotronics, and flexible electronics, and will have a huge socio-economic impact.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.499.940 |
Totale projectbegroting | € 2.499.940 |
Tijdlijn
Startdatum | 1-2-2023 |
Einddatum | 31-1-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- UNIVERSITAT AUTONOMA DE BARCELONApenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Magneto-ionic data-security device integrated on flexible substratesSECURE-FLEXIMAG aims to enhance data security by developing an advanced device using innovative materials and designs to overcome current PUF limitations and improve efficiency and scalability. | ERC Proof of... | € 150.000 | 2025 | Details |
Engineering Magneto-ionic Materials for Energy-Efficient Actuation and Sensing: From Interfaces to Multifunctional Voltage-Tunable MicromagnetsACTIONS aims to develop energy-efficient magneto-ionic materials for low-power actuation and sensing in micro- and nanotechnologies by utilizing electrochemical reactions for magnetic control. | ERC Consolid... | € 1.994.165 | 2024 | Details |
Curvilinear multiferroicsThis project aims to develop curvilinear multiferroics by using geometric curvature to create new materials for energy-efficient computing, enhancing memory and logic devices beyond current technologies. | ERC Advanced... | € 2.500.000 | 2024 | Details |
Manipulating magnetic domains through femtosecond pulses of magnetic fieldFemtoMagnet aims to revolutionize data storage by engineering plasmonic nanodevices to generate ultrafast, reversible magnetic fields for nanoscale manipulation of magnetic domains. | ERC Consolid... | € 2.499.926 | 2024 | Details |
Magnetic memory supraparticles for perceptual matterThis project aims to develop SmartRust, smart magnetic particles that enable materials to perceive and communicate events, enhancing safety, maintenance, recycling, and autonomous manufacturing. | ERC Consolid... | € 1.999.250 | 2024 | Details |
Magneto-ionic data-security device integrated on flexible substrates
SECURE-FLEXIMAG aims to enhance data security by developing an advanced device using innovative materials and designs to overcome current PUF limitations and improve efficiency and scalability.
Engineering Magneto-ionic Materials for Energy-Efficient Actuation and Sensing: From Interfaces to Multifunctional Voltage-Tunable Micromagnets
ACTIONS aims to develop energy-efficient magneto-ionic materials for low-power actuation and sensing in micro- and nanotechnologies by utilizing electrochemical reactions for magnetic control.
Curvilinear multiferroics
This project aims to develop curvilinear multiferroics by using geometric curvature to create new materials for energy-efficient computing, enhancing memory and logic devices beyond current technologies.
Manipulating magnetic domains through femtosecond pulses of magnetic field
FemtoMagnet aims to revolutionize data storage by engineering plasmonic nanodevices to generate ultrafast, reversible magnetic fields for nanoscale manipulation of magnetic domains.
Magnetic memory supraparticles for perceptual matter
This project aims to develop SmartRust, smart magnetic particles that enable materials to perceive and communicate events, enhancing safety, maintenance, recycling, and autonomous manufacturing.
Vergelijkbare projecten uit andere regelingen
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
MagnetoElectric and Ultrasonic Technology for Advanced BRAIN modulationMETA-BRAIN aims to develop non-invasive, precise control of brain activity using magnetoelectric nanoarchitectures and ultrasonic technologies, enhancing treatment for neurological disorders. | EIC Pathfinder | € 2.987.655 | 2024 | Details |
Multi-property Compositionally Complex Magnets for Advanced Energy ApplicationsThe CoCoMag project aims to develop innovative, critical-element-free magnets using compositionally complex alloys to enhance e-mobility and magnetic refrigeration for a sustainable energy future. | EIC Pathfinder | € 2.987.943 | 2023 | Details |
Metaplastic Spintronics SynapsesMETASPIN aims to develop low-power spintronic artificial synapses with metaplasticity to prevent catastrophic forgetting in AI, integrating this technology into an ANN for multitask learning applications. | EIC Pathfinder | € 2.999.750 | 2023 | Details |
Magnetic neural Network for predictive maintenanceGolana Computing aims to develop bio-mimicking magnetic neurons for real-time analog signal analysis, enhancing predictive maintenance in manufacturing while minimizing energy consumption. | EIC Transition | € 2.499.999 | 2023 | Details |
REusable MAsk PatterningREMAP aims to revolutionize surface patterning by using reusable magnetic masks for high-throughput, eco-friendly manufacturing in advanced technologies like photovoltaics and biotechnology. | EIC Pathfinder | € 3.925.043 | 2022 | Details |
MagnetoElectric and Ultrasonic Technology for Advanced BRAIN modulation
META-BRAIN aims to develop non-invasive, precise control of brain activity using magnetoelectric nanoarchitectures and ultrasonic technologies, enhancing treatment for neurological disorders.
Multi-property Compositionally Complex Magnets for Advanced Energy Applications
The CoCoMag project aims to develop innovative, critical-element-free magnets using compositionally complex alloys to enhance e-mobility and magnetic refrigeration for a sustainable energy future.
Metaplastic Spintronics Synapses
METASPIN aims to develop low-power spintronic artificial synapses with metaplasticity to prevent catastrophic forgetting in AI, integrating this technology into an ANN for multitask learning applications.
Magnetic neural Network for predictive maintenance
Golana Computing aims to develop bio-mimicking magnetic neurons for real-time analog signal analysis, enhancing predictive maintenance in manufacturing while minimizing energy consumption.
REusable MAsk Patterning
REMAP aims to revolutionize surface patterning by using reusable magnetic masks for high-throughput, eco-friendly manufacturing in advanced technologies like photovoltaics and biotechnology.