KTH Royal Institute of Technology

2D Materials for Electrochemical Transistors Targeting Near Zero Energy Neuromorphic Computing

  • Discovery
  • Performance
  • Properties
  • Synthesis & Processing
Academic project

Research question

Today’s computers are based on “Von Neumann” architectures that separate computing from data storage. This architecture has encountered a bottleneck—it is not only energy inefficient, but it also makes it hard to improve computing performance because time and energy are consumed in data storage and data access. Fusing computation with memory is the only way to fundamentally get around this bottleneck. Neuromorphic computer architectures based on two-terminal memristor devices has been proposed for in-memory computation. However, memristors come with many challenges, including variations in resistance of the memristor over space and time, large write currents, large noise, and low endurance. Furthermore, the read- and write-actions of many memristors are not separated. Our aim in this project is to develop new 2D materials and related material integration technologies for electrochemical transistors that overcome the challenges of two-terminal memristors. Specifically, we will develop electrochemical transistors based on MXenes for random-access memory (ECRAM) that will enable the next generation of in-memory computers.

Sustainability aspects

Compared to state-of-the-art computers based on CMOS transistors, the new types of electrochemical transistors we are developing will enable computer architectures that have the potential for 1000x higher energy efficiency. Our vision is that future system-level implementations of the technologies we develop can reach computation efficiencies of 1000 Teraops/watt and power extremely energy efficient computing in fields ranging from consumer applications to industrial applications, and custom super-computing. Furthermore, the material and integration technologies that we are developing for our new electrochemical transistors are potentially less energy and resource intensive than many of the currently used semiconductor materials and manufacturing processes, thus potentially contributing to reduced waste and more efficient use of materials and energy.

researcher photo

KTH Royal Institute of Technology

Frank Niklaus



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