/Ion-gated Neuromorphic architectures with Prussian Blue Analogs

Ion-gated Neuromorphic architectures with Prussian Blue Analogs

PhD - Leuven | Just now

From ion flow to intelligent hardware

Artificial intelligence is increasingly limited by the energy cost of moving data between memory and processing units. Neuromorphic computing seeks to overcome this challenge by mimicking the operating principles of the human brain, where memory and computation are co-localized. Emerging ion-based materials like PBA offer a unique opportunity to realize such adaptive and energy-efficient hardware.

This PhD project will explore the fabrication of 3D neuromorphic architectures with PBA as ion-insertion material for ion-guided resistive switching. Instead of utilising conventional transistors, information pathways can be formed and reinforced through electrochemically controlled ion motion in networks of nanoscale conductive elements. Inspired by biological synapses, repeated ionic activity can strengthen preferred conduction pathways, creating adaptive hardware capable of learning directly through physical processes.

The project builds upon imec expertise in electrochemical deposition of Prussian Blue Analogs (PBAs), a versatile class of ion-insertion materials whose electrical, ionic, magnetic and optical properties can be tuned through electrochemical control.

The project will investigate design and fabrication of 3D nanowire architectures of ion-insertion materials as electrochemical switching units using electrochemical techniques. The project will then develop experimental demonstration of ion-guided “learning behaviour” and memory formation at the intersection of ionics, materials science, and neuromorphic engineering.

 

What You Will Do

  • Electrochemical fabrication of 3D architectures with Prussian Blue Analog materials.
  • Develop nanoscale ionic switching protocols and networks.
  • Characterize electrochemical, electrical and structural properties using state-of-the-art facilities.
  • Collaborate with experts in materials chemistry, nanoelectronics, device physics and bio-inspired computing.
  • Publish results in leading scientific journals and present at international conferences.


 


 

Required background: Materials chemistry, Physics, Nanoscience

Type of work: 70% Experimental, 10% modelling, 10% Literature

Supervisor: Philippe Vereecken (KU Leuven)

Co-supervisor: Philippe Vereecken (KU Leuven)

Daily advisor: Sai Gourang Patnaik, Rico Rupp

The reference code for this position is 2027-136. Mention this reference code in your application.

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