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hAIdrogen safety sensors

Reference number
Coordinator Chalmers Tekniska Högskola AB - Institutionen för fysik
Funding from Vinnova SEK 6 998 979
Project duration October 2021 - October 2024
Status Ongoing
Venture AI - Leading and innovation
Call AI in the service of the climate 2

Purpose and goal

In order to reduce greenhouse gas emissions, large investments in hydrogen technology are a key factor and robust and fast hydrogen safety sensors are a key technology, since hydrogen-air mixtures are flammable. However, no currently existing sensor technology meets the stringent requirements for safety and process monitoring sensors set by actors in, e.g., the automotive, energy or steel manufacturing industries. The goal of this project is therefore to radically improve the performance of plasmonic hydrogen sensors in demanding environments using artificial intelligence.

Expected effects and result

After the implementation of the project, we expect to have created plasmonic hydrogen sensors with a response time of well below a second that can be used in chemically challenging environments, such as very high humidity or high pressure, and which have a greatly reduced need for calibration that is made possible by the AI-driven software that we have developed. The greater consequence will be that a radically new generation of hydrogen sensors enters the market and contributes to a faster implementation of hydrogen technology that reduces CO2 emissions.

Planned approach and implementation

The project is a collaboration between Chalmers University of Technology, Göteborgs Universitet and Insplorion AB, where the university partners are responsible for the development of an AI-designed sensor chip with multiplex function and an AI-driven software for sensor signal processing. Insplorion AB is responsible for their integration into a functional sensor prototype with AI-based sensor signal processing and performance that meets the requirements of the most important actors in the hydrogen energy sector.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 29 October 2021

Reference number 2021-02760

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