Exploring pinning mechanism for single-bit domain wall devices
PhD internship, Master internship - LeuvenPosted Oct 17, 2026
Overview
The rapid growth of AI-driven applications today is
pushing conventional charge-based memory technologies to their limits due to
the concerns in reliability, scalability, and volatility. This pushes a
pressing need for alternative memory solutions that offer faster operation,
higher endurance, and non-volatile data storage. Spintronics, which exploits electron
spin in addition to charge, offers a promising pathway for next-generation
memory. Its combination of non-volatility, fast switching, and high integration
density makes Magnetic Random-Access Memory (MRAM) a strong candidate to
complement or replace conventional charge-based memories across the memory
hierarchy. MRAM uses Magnetic Tunnel Junctions
(MTJs) to store and read information through the magnetic state and Tunnelling
Magnetoresistance (TMR). While STT-MRAM suffers from high switching currents
and reliability concerns, SOT-MRAM separates read and write paths for faster
switching and improved endurance. However, switching the entire magnetic layer
remains energy-intensive, and reliable field-free switching is still a major
challenge. Single-bit domain-wall (DW) devices
offer an attractive alternative by encoding information in the position of a DW
within an extended magnetic layer. Since only the DW needs to be displaced
rather than the entire magnetic layer reversed, switching energy can be
significantly reduced. DW devices can also operate without an external magnetic
field, making them promise scalable and energy-efficient memory. At imec, we have demonstrated full
electrical control of nanoscale DWs using MTJs on 300 mm wafer for both writing
and reading, providing an important proof-of-concept for practical DW
manipulation at the nanoscale [1]. Building on this work, the project will
investigate the physics of DW motion, with a particular focus on reliable DW
confinement near the MTJ. A key challenge is to control the position of DW
while maintaining low-power operation. Because DWs can move easily under a
small driving current, excessive driving may cause DW to move beyond the
intended storage region, leading to loss of information. This project will
investigate different strategies to reliably confine the DW while maintaining
low-power operation and compatibility with CMOS-scalable devices. This project explores geometrical
pinning strategies to prevent DW annihilation and achieve reliable DW
confinement. The study will investigate the influence of geometrical design on
DW dynamics under both magnetic field- and SOT-driven DW motion. Different
pinning geometries will be designed and systematically investigated using
micromagnetic simulations with OOMMF and MuMax. The simulations will provide
insight into the underlying DW dynamics and the effectiveness of different
confinement schemes, guiding the development of robust and low-power DW-based
memory devices. The results will provide practical design guidelines for
optimizing geometrical pinning in future 1-bit DW-MRAM devices. https://www.imec-int.com/en/articles/imec-brings-magnetic-domain-wall-devices-closer-industrial-reality Type of internship : PhD internship, Master internship Duration : 6 months to one year Required educational background : Materials Engineering, Physics, Nanoscience & Nanotechnology Supervising scientist(s) : For further information or for application, please contact Van Dai Nguyen ( Van.Dai.Nguyen@imec.be ) The reference code for this position is 2026-INT-350 . Mention this reference code in your application. Only for self-supporting students. Applications should include the following information: resume motivation current study Incomplete applications will not be considered
Apply on the employer's site
Original posting: imec-int.com
RISC-V ecosystem
imec in the RISC-V ecosystem
RISC-V International: Community
Interuniversity Microelectronics Centre is an international research & development organization, active in the fields of nanoelectronics and digital technologies.
- RISC-V research/design: system-level integration of a digital AI accelerator with RISC-V
- Participates in RISC-V automotive and space-chip ecosystem work
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