Tandem Industry Academia (2021)
Towards improved weather forecasting
Project title: Harnessing ceilometer network for operational aerosol type and cloud/precipitation phase classification to enhance forecasting
Approved funding: 194 715 €
Applicant: Finnish Meteorological Institute
Industrial partner: Vaisala
“The project, its results and outcomes will benefit the business partner, the academic world and society as a whole,” says principal investigator Mika Komppula.
Monitoring the composition of atmospheric particles and the phase of clouds and precipitation is an integral part of preparing for exceptional weather and air quality problems. To improve these monitoring capacities the Finnish Meteorological Institute and Vaisala have joined forces to develop a new CL61 ceilometer or cloud height indicator and to develop new algorithms to ensure the new instrument and the global measurement network can be put to the best possible use in the characterization of atmospheric aerosols and clouds. This will further improve the forecasting and observation of hazardous weather conditions, for example. The data collected will be visualized in real time, giving meteorologists up-to-date information on atmospheric conditions.
Closer insights into how forests can curb climate change
Project title: Decision making system for the future reforestation plans on a global scale
Approved funding: 172 028 €
Applicant: University of Helsinki
Industrial partner: Satellio Company
“This is a groundbreaking project: our aim is to provide a more solid foundation for informed decision-making on reforestation by exploring the climate effects of forests. If we’re successful, we will also gain more knowledge about climate change and bolster Finnish industry,” says researcher Sara Alibakhshi.
Climate change is continuing to accelerate and greenhouse gas emissions are reaching alarming levels. Forests play a crucial role in curbing climate change, but there is also research evidence which suggests that forests have a warming effect. The properties of both trees and the environment impact upon the way that forests interact with the climate.
In a project led by professor Petri Pellikka researchers from the University of Helsinki have joined forces with Satellio Company and are using the tools of machine learning to produce more accurate information about forests with a view to supporting more informed decision-making. The project is also working to develop software that will allow ordinary people to understand what kind of trees should be planted in what kind of areas so that forests can have a cooling effect on the climate.
Machine learning to boost pharmaceuticals production
Project title: Optimizing synthesis of pharmaceuticals by machine learning
Approved funding: 222 000 €
Applicant: University of Helsinki
Industrial partner: Orion Corporation, Orion Pharma
“FRIF funding means we can proceed with our research which has definite impact potential. In a best case scenario the funding scheme can also pave the way to wider cooperation,” says principal investigator Jari Yli-Kauhaluoma.
What happens when synthetic organic chemistry, medicinal chemistry, catalysis research and machine learning are brought together? This question will be answered by a joint project where University of Helsinki researchers are working with Orion Pharma research teams to combine these different areas to meet the needs of the pharmaceuticals industry. The aim of this pioneering project is to make use of machine learning and the latest advances in chemistry to optimize the process of pharmaceuticals synthesis and to identify improved synthetic routes to drugs.
Professor Jari Yli-Kauhaluoma has assembled an experienced team of five leading industrial and academic researchers. The project will also lay the foundation for the training of the next generation of chemists, ensuring that they are familiar with the latest methods of machine learning and chemical synthesis. The new technologies are integrated into the curriculum as skills and competencies evolve.
Contaminant-repellent coatings can meet the needs of many branchesc
Project title: Surfaces that stay clean in challenging conditions: the case of a medical application and beyond (CLEAN)
Approved funding: 198 722 €
Applicant: Aalto University
Industrial partner: GE Healthcare Finland Oy (GE Healthcare)
“Nature has ingenious ways of keeping surfaces clean, from mud-repellent lotus flower leaves to dew-repellent butterfly wings. Our aim is to develop a completely novel type of repellent surface coating that has application not only in the field of medicine but more widely,” says principal investigator Robin Ras.
Just about every surface material is liable to become contaminated, especially in challenging conditions. Dirt and other contaminants adversely affect the technical performance and uses of surface coatings, for instance in medical equipment, sensors and cameras. In this project researchers from Aalto University are working closely with GE Healthcare to develop a new kind of super-repellent coating for medical applications. The researchers drew their inspiration for the project from nature.
Artificial intelligence to boost quality and efficiency in the sawmill industry
Project title: Artificial intelligence for timber industry: virtual sawing via multi-modal domain translation (TimberAI)
Approved funding: 185 956 €
Applicant: Lappeenranta-Lahti University of Technology LUT
Industrial partner: Finnos Oy
“The new methods will open up new opportunities not only to current developers of measurement equipment and process control solutions to the sawmill industry, but also to new start-ups,” says principal investigator Tuomas Eerola.
Artificial intelligence has a role to play even in the sawmill industry. A joint project
undertaken by the Lappeenranta-Lahti University of Technology (LUT) and Finnoss Oy will be making use of AI methods that can accurately predict the output from cutting logs of certain dimensions in a certain way. This information will make it possible to optimize the sawmill process and ensure the highest possible output quality.
New insights into the carbon footprint of dairy production
Project title: Mitigating grassland N2O emissions – towards carbon neutral milk production (MiNiMi)
Approved funding: 232 690 €
Applicant: University of Helsinki
Industrial partner: Valio
“The Finnish Research Impact Foundation was the most natural choice for funding agency in this project, which is a close collaboration between academia and industry and producing not only scientific knowledge but also evidence for informed decision-making,” says principal investigator Mari Pihlatie.
Nitrous oxide (N20) emissions from grasslands contribute significantly to the carbon footprint of dairy production. N20 is a powerful greenhouse gas but so far little is known about the climate effects of grass cultivation or the dairy production chain. In collaboration with other academic and business partners (FMI, LUKE, Valio, Yara, Vaisala, Soil Scout), this joint project between the University of Helsinki and Valio is measuring N20 emissions from Valio grasslands and the temporal and spatial variability of emission levels.
The project is using new portable measurement technology that can simultaneously provide readings for all three greenhouse gases, i.e. CO2, CH4 and N2O. This makes it possible to determine emission levels for the most critical gases in the same environmental conditions.
Laser technology to bring enhanced impact in several fields
Project title: New-generation mid-infrared ultrafast fiber lasers
Approved funding: 201 575 €
Applicant: Aalto University
Industrial partner: nLIGHT Oy
“I was very excited about this new funding model that includes one year at the university and one year in industry. It’s a unique and different kind of funding system compared to other Finnish and European mechanisms and just right for our needs,” says principal investigator Zhipei Sun.
Mid-infrared ultrafast fibre lasers play an important role in various new and emerging areas of laser technology application, such as sensing, imaging and medicine. The aim of this multidisciplinary project is to combine Aalto University’s unique expertise in nanotechnologies with the know-how of nLight Oy in optical fibre and laser technologies and to develop long-awaited high-performance mid-infrared fibre lasers. The joint project will also aim to encourage practical applications of these lasers for instance in the fields of health and datacommunications where lasers have potentially high academic, industrial and societal impact. The Tandem funding model provides the ideal platform for this kind of project geared to achieving wide-ranging impact.
Aiming for cheaper and environmentally friendlier electricity
Project title: Optimal Control for Maximizing the Effectiveness of Power Electronic Systems (OPT4MAX)
Approved funding: 197 710 €
Applicant: Tampere University
Industrial partner: Danfoss Drives/Vacon
“Traditional control methods are unable to deal with the whole system but concentrate on one dimension at a time. That’s why systems aren’t able to put their potential to full use. In this project we are creating a control method that can simultaneously take account of multiple objectives. This will help to lower the costs of the whole electrical system and increase service life,” says principal investigator Petros Karamanakos.
Around half of all electricity is consumed by electrical variable speed drives (VSDs). However, conventional control solutions fail to extract their maximum performance. VSDs are therefore often oversized, which drives up electricity consumption and system costs. This joint project between Tampere University and Danfoss is working to develop a novel control method for VSDs and so to pave the way to more cost effective, sustainable and environmentally friendly electricity consumption.
Individual and earlier treatment for osteoarthritis
Project title: Organ-on-chip platform for in situ detection of osteoarthritis biomarkers (OASIS)
Approved funding: 213 958 €
Applicant: University of Oulu
Industrial partner: Finnadvance
“We’re creating a petri dish that includes osteoarthritis patients’ unhealthy cells. The unique aspect about the project is that based on the sensor we have created, it will be possible to analyse whether or not a certain medicine will be effective and cure unhealthy cells,” says principal investigator Gabriela S. Lorite.
Human bodies are at once both rather similar to each other and highly individual. That’s why the same medical treatment does not always work for all people. The aim of this joint project between the University of Oulu and Finnadvance is to develop individual medical treatments for osteoarthritis and at the same to create a method for testing individual treatments that could also be used for other conditions and serve as a practical tool for pharmaceutical companies and practising doctors. The model is based on Finnadvance’s successful biomimetic bone marrow in vitro model.
The project will help to advance the development of predictive diagnostics and reduce the economic burden from osteoarthritis globally.
Faster testing methods in quantum technology
Project title: Bolometers as a versatile toolkit for cryogenic circuit characterization
Approved funding: 171 664 €
Applicant: Aalto University
Industrial partner: Bluefors oy
“This funding will facilitate the university’s collaboration with business partners through the individual appointed to the position. This is why it’s an ideal way of exporting results produced in academic research out into business companies’ products,” says principal investigator Mikko Möttönen.
The development of quantum technology involves a wide range of exciting applications, such as fast computing and secured communications. In this joint project scientists at Aalto University and Bluefors Oy are working to develop a new type of measuring device that will speed up the testing of different components used in quantum computers and in quantum technology more generally. It will therefore accelerate the development of quantum computers and computers already under construction. The project contributes to quantum research in two ways. Firstly, real-time microwave pulses are detected using bolometers, which paves the way to bolometric quantum bit or ‘qubit’ readout. Secondly, the project will introduce a new tool to achieve power calibration and spectrum analysis at cryogenic temperatures.
Sweat-reading smartwatch could even assess suitability of medication
Project title: Development of a Wearable Lab-in-a-watch Optical Sensor for Label-free and Real-time Monitoring of Sweat Glucoses on Human Skin
Approved funding: 189 346 €
Applicant: University of Oulu
Industrial partner: Polar Electro Oy
“A smartwatch could monitor sweat molecules and produce non-invasive information about the user’s health,” says principal investigator Jian-An Huang.
Today’s smartwatches and other wearable devices can monitor their users’ heart rate and other physical, kinetic values such as temperature and body gestures, steps and location. It would add tremendous value if they could also identify and quantify health factors. The joint project between the University of Oulu and Polar Electro Oy is interested to explore whether an electro-plasmonic chip integrated in an optical watch could be used to monitor perspiration and on this basis provide more detailed health information than previous instruments. Sweat provides significant information on the individual’s health and can be used to measure blood sugar levels, for example. It can also help to evaluate the suitability of a person’s current medication for health conditions.
This information could be used to predict and prevent health risks. Overall the impacts at societal level could be significant indeed.
