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MAG-IONICS

PROJECTS

Enabling magneto-ionics for information technologies: secure and energy-efficient data storage and advanced computing (MAG-IONICS)

  • FINANCIAL ENTITY
    Agencia Estatal de Investigación (268.750 €)
  • DURATION
    2025-2028
  • PRINCIPAL INVESTIGATOR
    Prof. Jordi Sort, Dr. Enric Menéndez
  • PERSONNEL INVOLVED
    Nicolau López Pintó, Simone Privitera Uno, Luís Martínez Armesto, Irena Spasojevic, Huan Tan, Alberto Quintana, Pau Solsona, Eva Pellicer, Enric Menéndez, Jordi Sort

This Project aims to extend the use of magneto-ionic actuation for advanced memory and computing concepts, including applications in data security.

MAG-IONICS is an interdisciplinary research project aimed at developing advanced magneto-ionic materials that enable control of magnetism through voltage-driven ion motion. These materials hold immense potential for next-generation information technologies, such as energy-efficient memory devices (including neuromorphic and probabilistic computing) and secure systems for data protection, including anti-hacking and anti-counterfeiting solutions. The project explores a diverse range of materials, including transition-metal oxide and nitride thin films and lithographed structures (facilitating oxygen and nitrogen ion migration), as well as novel compounds designed for voltage-driven motion of ions like carbon, sulphur, or boron. These materials will undergo comprehensive structural, magnetic, and electrical characterization. Cutting-edge magnetometry techniques with in-situ voltage application (using liquid or solid electrolytes) will be employed to analyse magneto-ionic behaviour. Advanced methods, such as positron annihilation lifetime spectroscopy (to study structural defects like vacancies) and nanocalorimetry (to detect subtle phase transitions), will shed light on the underlying mechanisms. Ab initio calculations will further support this understanding. The project prioritizes improving key performance metrics such as ion diffusion speed, endurance (cycling stability), and threshold voltage (to enhance energy efficiency). Insights gained will be applied in two primary areas: (i) low-power data storage and advanced computing, and (ii) data security (e.g., true random number generators and physical unclonable functions).