Skip to Content

Transport at Nanoscale Interfaces

Hybrid Nanoscale Interfaces

Ultra-low power sensors are key components in mobile and autonomous systems, for the Internet of Things, and as functional elements in wearable systems for the Internet of Humans. Nanomaterials such as 1D nanotubes & nanowires and 2D materials have shown unique properties for ultra-sensitive, ultra-low power sensor applica-tions. Single Walled Carbon Nanotubes (SWNT) devices have been successfully demonstrated for chemical and physical sensing at unprecedented low power consumption in the range of μW per sensor function.
Today, the biggest barrier for technology transfer or commercialization of SWNT or other nanomaterial sensors is the lack of an industrial manufacturing process for a high device yield at low cost. This project aims to devel-op a new manufacturing process for nano-electronic sensor systems, with functional nanostructures, demon-strated for Single Walled Carbon Nanotubes (SWNTs), but applicable beyond SWNTs. The goal is to increase today’s state-of-the-art speeds by a factor of 1000 and to demonstrate that a fabrication of 1’000 components per hour is feasible.
For this purpose, we developed a high-throughput approach to rapidly identify suspended carbon nanotubes (CNTs) by using high-speed Raman imaging and deep learning analysis. Raman spectroscopy has the ad-vantages of being a non-contact approach, providing chemical and structural information with micrometer spa-tial resolution. Machine learning is used for on-the-fly classification of the low signal-to-noise ratio Raman spec-tra acquired using miliseconds integration times

Collaborators in Laboratory: Dr. Rolf Brönnimann, Rico Muff, Dr. Jan Overbeck, Prof. Michel Calame

External partners: Seoho Jung (ETHZ), Dr. Cosmin Roman (ETHZ), Dr. Miroslav Haluska (ETHZ), Sebastian Böhl, Prof. Christofer Hierold (ETHZ), Natanael Lanz (ETHZ),  Sascha Weikert (ETHZ), Prof. Konrad Wegener (ETHZ), Luis Barba (EPFL), Prof. Martin Jaggi (EPFL).

Funding: This project (Nano Assembly) is funded by the Strategic Focus Area - Advanced Manufacturing (SFA-AM). M.L.P. and J.Z. acknowledge funding by the EMPAPOST-DOCS-II program, which has received funding from the European Union’s Horizon 2020 research and innova-tion program under the Marie Skłodowska–Curie Grant Agreement no. 754364. M.L.P. also acknowledges fund-ing from the Swiss National Science Foundation under the Spark grant no. 196795.

  1. Zhang et al. High-speed identification of suspended carbon nanotubes using Raman spectroscopy and deep learning. Microsystems & Nanoengineering (2022).


Transport at Nanoscale Interfaces Laboratory

Contact us


Prof. Dr. Mickael Lucien Perrin

Prof. Dr. Mickael Lucien Perrin
Group Leader Quantum Devices

Phone: +41 58 765 4610

Quick Access

The latest EmpaQuarterly:
Focus: Energy revolution