Master Theses

In our project, the objective is to detect nitrogen dioxide gas (NO2) through Carbon Nanotube (CNT) gas sensor array by repeatedly measuring the transfer characteristics of the CNT-FETs (Field Effect Transistors) in the array. However, achieving sensor recovery poses a challenge, necessitating the application of high voltage pulses at regular intervals to heat the channel and desorb gas molecules (self-heating). Our current measurement mode face challenges in independently controlling and tuning the voltages for each device. This project aims to develop a new PCB design that addresses these challenges.

Type: Setup design, experimental
The overall goal of this project is the development of an artificial robotic skin which integrates tactile sensing capabilities into an artificial finger. For a more accurate and reproducible fabrication, the placement of the tactile arrays onto the silicone finger must be characterized and improved to reduce finger to finger variation.

Characterization of SWNTs synthetized by a CVD process on MEMS chips by Raman spectroscopy utilizing multiple laser wavelengths. Determination of presence of DWNTs, bundles and individual SWNTs as well as their characteristics and quality.

Development of a toolchain based on COMSOL and Matlab to simulate the modulation of charge transport in carbon nanotube sensors due to mechanical or chemical effects.

SWNT decoration by preselected nanoparticle types and determination of the impact of the material onto nanotube characteristics and CNFET performance.

Keywords: Artificial robotic finger, finite element method, graph neural networks, simulation
Motivation: The overall goal of this project is the implementation of a simulation model of an artificial robotic finger with integrated tactile  sensing arrays on a silicone finger. To enable real time simulation for training robotic hands, a computationally efficient model is required