Final Thesis

FVM Simulation of Artificial Synapses

Key Info

Basic Information

Unit:
Chemical Process Engineering
Type:
Masterthesis
Focus/Key Topic:
simulativ
Date:
09/01/2019

Contact

Artificial neural networks are being applied to increasingly complex problems like automatic object recognition in video or the optimization of membrane processes. Compared to the implementation of such networks on common computing architectures, natural neural networks like the human brain show significantly higher degrees of parallelism and connectivity, while requiring only a fraction of the energy to operate.

In order to leverage these properties and to create more life like neural networks, synaptic plasticity can be implemented trough ion transport in polymer electronic devices.

An FVM Model that descirbes the basic ion transport and electrochemical porcesses will help to better understand these devices and improve them in the future.

This work focues on the extension of an existing model from 1D to 2D in order to study important dynamic effects when applying the device as an artificial synapse.

We offer:

  • An introduction to the Finite Volume Method
  • Interesting project with lots of challenges
  • Intense mentoring

Our expectations:

  • You should be open minded and enjoy working in a team!
  • Study engineering, information science or a related field
  • Be able to communicate in English

Interested?
Feel free to give me a call, send an email or come by my office!

Chemische Verfahrenstechnik (AVT.CVT) | DWI Leibniz Institut
Forckenbeckstraße 50, Raum 2.56
Tel: +49 241 80 29949
Email: daniel.felder@avt.rwth-aachen.de