We are an international group of scientists with multidisciplinary backgrounds in physics, chemistry, biology, materials science, and engineering. Our areas of expertise include sensors, materials for sensing and sensor system integration including the use of 3D-printing technology. Our main research focus is on sensors for different applications spanning from indoor air quality control, ambient monitoring, emission control and preventive conservation of cultural heritage materials to bio-analytical sensing and diagnostic tools, food quality and safety, and sustainable development. We work closely together with several collaborators within both academia and industry at local, national and international levels.
Applied Sensor Science
The Applied Sensor Science unit has their research focus on the detection of gaseous, liquid or biological analytes with tailored sensors for various applications.
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Publications
For a complete list of all our publications visit Diva.
2025
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Collaboration and projects
Notable projects
H2020-NMBP-ST-IND – SensMat 2019-2022
VINNOVA – Cloud-Based Indoor Climate Station Embedded in Active Plant Screen 2019-2021
COST Action CA17136 – INDAIRPOLLNET 2018-2022
VINNOVA – 2018-03308 Sensor for faster, cheaper, and easier determination of dioxins in the environment 2018-2019
H2020-MSCA-ITN – FoodSmartphone 2017-2020
SFF GMT14-0077 – Epitaxial graphene for metrology, sensors and electronics 2016-2022
SFF RMA15-0024 – New two-dimensional systems from growth to applications 2015-2021
EU FP7 – SENSIndoor 2014-2016
COST Action TD1105 – EuNetAir 2012-2016
Collaborations
The unit has many local, national and international collaborations from small projects to large scale EU projects. Our main collaborators are:
Chalmers University, Sweden – Department of Microtechnology and Nanoscience
CNR, Italy – National Research Council
ENEA-Brindisi, Italy
Max IV Lund
Università "La Sapienza", Italy
University of Brescia, Italy
University of Oulu, Finland – Microelectronics Research Unit
Saarland University, Germany – Lab for Measurement Technology
DANSiC AB, Sweden
Envic-Sense AB, Sweden
Ford in Dearborn, USA
Graphensic AB, Sweden
SAAB AB, Sweden
SenSiC AB, Sweden
Sensorbee, Sweden
Featured project
Sensor based sex sorting of eggs
Globally, about 7 billion day-old male chicks are annually culled in conjunction with the breeding of egg-laying hens. As the male chicks are neither useful for egg production
The basis for the method is identification and measurement of specific, naturally occurring differences in the molecular composition between eggs of different gender. As these differences have been shown to be present already prior to the start of the hatching process, gender-based sorting of eggs should be possible already before the eggs are entered into the incubators for hatching. Since no embryo at that moment has started to develop, and thereby no nerve cells, the method offers guaranteed painless ‘disposal’ of the male eggs (the male chicks to be). Furthermore, as incubation is quite energy intensive, the hatching costs per egg-laying hen is markedly reduced when no male eggs are required to go through the hatching process and no manual post-hatch sorting is required. On the contrary, the male eggs can be directly utilized as food or go into food production, why the egg sexing method under development also may contribute to an improvement in resource utilization related to food industry.
The final aim of the project is the development of a method and a product design which will allow general egg sexing, independent of the type and age of the egg-laying hen, feed, and of any other factors (e.g. environmental) which otherwise might influence the accuracy, and which will be easy to integrate with already existing egg handling infrastructure. Presently, an accuracy of about 80-85% in the determination of egg gender has been achieved and the measurement time reduced to less than a minute per egg (the required measurement time has been estimated to approximately 20 seconds), allowing the sorting of 40 000 eggs per day (assuming measurements on 30 eggs in parallel, based on current infrastructure).
This project is a collaboration between Linköping University, DANSiC AB, Swedfarm, and Svenska Ägg and is, besides the partner companies/ institutions, largely financed by the European Innovation Partnership for Agricultural Productivity and Sustainability (spec. Europeiska jordbruksfonden för landsbygdsutveckling) through the Swedish Board of Agriculture (Jordbruksverket).