Jan Rieck: PhD at the University of Groningen, The Netherlands


Ferroelastic domain walls as memristors and their network behaviour


Prof. dr. Beatriz Noheda

Non-academic supervisor:

Dr. Siegfried Karg (IBM Research – Zurich, Switzerland)

Memristive behavior of domain wall networks

The project is focused on the synthesis and characterization of ferroelastic oxides with well defined domain walls. These domain walls are more conducting than the host materials and display memristive characteristics. The main part of the research will be performed at the Zernike Institute for Advanced Materials, University of Groningen. Additionally, ESR will spend the secondments at IBMResearch – Zurichfor the characterization of domain wall networks (1 month), at CSIC in Zaragoza, Spain for TEM characterization of the films (0.5 month), at SmartTip B.V., the Netherlands for development of suitable atomic force probes (1 month) and at aixACCT Systems GmbH, Germany for the development of dedicated hardware to perform electrical measurements (1 month).

The University of Groningen is the second oldest in the Netherlands. With its 6500 employees, it houses ~30000 students (incl. 3750 international students) and 1500 PhD students, 48% of whom are international. It belongs to the top 100 research universities in the world and is a member of the distinguished international Coimbra Group of European universities. The University of Groningen is in the top 3 of European research universities in the fields of Material Sciences and Chemistry.

The Zernike Institute for Advanced Materials is ranked as one of the best materials research institutes based on publication impact. It consists of approximately 250 physicists, chemists, and biologists working on fundamental leading-edge research in materials science. The research within MANIC belongs to the research initiative CogniGron (Groningen Cognitive Systems and Materials center), that joints the expertise from the Zernike Institute and that of the Bernoulli Institute for Mathematics, Computer Science and AI. A holistic approach that coordinates efforts in materials science, physics, mathematics, computer science and artificial intelligence to develop materials and systems that can learn, towards a future cognitive computer.

Additional information for applicants

  • We look for a candidate with a master/bachelor degree in Physics, Materials Science and/or Chemistry, or a combination thereof.
  • Local application requirements apply. Please visit the RUG website for more information.

For more details on the project, contact