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.

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.

Contact

Publications

For a complete list of all our publications visit Diva.

2024

Shun Kashiwaya, Yuchen Shi, Jun Lu, Davide Giuseppe Sangiovanni, Grzegorz Greczynski, Martin Magnuson, Mike Andersson, Johanna Rosén, Lars Hultman (2024) Synthesis of goldene comprising single-atom layer gold Nature Synthesis (Article in journal) Continue to DOI
Silvia Casalinuovo, Alessio Buzzin, Antonio Mastrandrea, Marcello Barbirotta, Donatella Puglisi, Giampiero de Cesare, Domenico Caputo (2024) Questioning Breath: A Digital Dive into CO2 Levels
Guillem Domènech-Gil, Donatella Puglisi (2024) Machine Learning for Enhanced Operation of UnderperformingSensors in Humid Conditions
Jens Eriksson, Donatella Puglisi, Christer Borgfeldt (2024) Electronic Nose for Early Diagnosis of Ovarian Cancer
Guillem Domènech-Gil, Thanh Duc Nguyen, J. Jakob Wikner, Jens Eriksson, Donatella Puglisi, David Bastviken (2024) Efficient Methane Monitoring with Low-Cost Chemical Sensorsand Machine Learning

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

EU-logotype with text
nor economically viable in meat production and no reliable or practically implementable method for pre-hatch gender identification of eggs up until recently has existed, no other option but culling has been available. This project therefore aims at the further improvement of a non-invasive method for pre-hatch egg sexing, first developed at Linköping University, in order to facilitate commercialization of a product by which the ethical problem of culling can be alleviated, and the poultry business provided with a cost-efficient alternative to culling. 

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).

A carton of white eggs in front of a computer screen. A sensor is attached to one of the eggs in the carton.

Education

Education

Our unit is involved in teaching at all levels and we always welcome students who wish to do diploma work with us.

Teaching

Undergraduate courses

•TFMT14 – Measurement Technology

TFMT19 – Chemical Sensor Systems

•TFTB38 – Imaging and ubiquitous biosensing

•TFYA46 – CDIO Year 1

•TFYA99 – CDIO Year 5 

•8FG074 – Sustainable Development

 

 

PhD courses 

•6FIFM66  Leadership Principles and Agile Management 

•Scanning Probe Microscopy

Thesis projects

We always welcome interested students to do a diploma work with us or together with our collaborators. Feel free to contact us to discuss your own exiting idea or the projects we currently offer.

Our topics usually include different sensor systems (SiC-FETs, 2D-material based sensors and metal-oxide nanoparticle based sensors), various applications fields (air quality monitoring, combustion control, water quality monitoring, egg sexing...) and other related research questions.