Projects

Projekt OptimaMind keskendub ajapiiranguga söömisele, et parandada aju tervist ja võidelda vananemisega kaasnevate väljakutsetega. Ajalooliselt oli inimeste juurdepääs toidule sageli juhuslik, muutes vahelduva paastumise (teise nimega aeg-restrikteeritud söömise (TRE)) elu loomulikuks osaks. See ajalooline kontekst loob aluse TRE võimalike eeliste mõistmiseks tänapäeval, eriti kognitiivse tervise kontekstis. On näidatud, et TRE kutsub esile adaptiivseid molekulaarseid muutusi, mis kaitsevad rakuressursse, parandades samal ajal füüsilist ja kognitiivset jõudlust. Sellised muutused hõlmavad süsteemse põletiku vähenemist ja raku antioksüdantide potentsiaali suurenemist. Üks TRE mõju näidetest on beeta-hüdroksübutüraadi (BHB), ketoonkeha, mis parandab kognitiivseid funktsioone, tootmine. Maksas toodetud BHB on oluline energiasubstraat, millel on võrreldes teiste energiaallikatega kasulikumaid omadusi. Ja vastupidi, sagedane toidutarbimine ja vähene füüsiline aktiivsus võivad pärssida BHB tootmist, vähendades seega selle positiivset mõju. Projekti OptimaMind eesmärk on uurida erinevate meetodite abil TRE mõju kognitiivsete funktsioonide biomarkeritele, eriti vananevas elanikkonnas. Kavandatavas projektis kasutatakse Euroopas olemasolevaid biopankade proove ja erinevaid paastuprotokolli kohordi andmeid, et uurida neuroprotektiivseid biomarkereid erinevates populatsioonides. Oodatavad tulemused hõlmavad uusi teadmisi TRE-st kui mittefarmakoloogilisest strateegiast kognitiivse pikaealisuse suurendamiseks ja dementsuse ennetamiseks. Projekti eesmärk on ka teavitada tervishoiuteenuse osutajaid ja avalikkust praktilistest tõenduspõhistest strateegiatest aju tervise säilitamiseks. OptimaMind mõjutab rahvatervise soovitusi, kliinilisi tavasid ja heaolutööstust, mille eesmärk on lõpuks parandada kognitiivset tervist ja elukvaliteeti vananevas elanikkonnas.

The importance of antimicrobial membranes has significantly grown during the recent COVID pandemic era. Nanofibrous antimicrobial membranes have seen novel applications in biomedicine, such as face masks against viral threats or wound dressings used in chronic patient care. Composite electrospun nanofiber meshes are convenient to use as antimicrobial membranes. At present, the lack of automated, inline quality control limits both the pilot and large scale production of multi-material multilayer composite membranes. The alternative, manual re-calibration greatly limits production throughput and thus commercial viability. The goal of this R&D activity is to create technology for scalable inline quality control of electrospun nanofiber meshes. Using cognitive electronics, the system will be capable of continuous multiparameter monitoring and electrospinning process control to maintain optimal product quality and distribution.

Customization requirements in modern manufacturing demand a closer collaboration between operators and automated technologies, leading to a novel Human-Robot Collaboration (HRC) and interaction (HRI) paradigm aimed at augmenting human capabilities in the workplace. Digital Twin (DT) and Immersive technologies (XR) support the inclusion of the human operator in simulation-based interfaces intended for safe, efficient, multimodal, and adaptive HRI. The design and implementation of these interfaces are not yet adequately addressed. This project aims to define what is the current approach to the requirement definition for DT and XR by analyzing the potentials and challenges of the adoption of DT interfaces and other types of input methods in the HRC context, their allocation in the Human-Computer Interaction (HCI), and the state of current experimental research in this field as bringing the human back to the loop bring us the Industry 5.0 concept within industrial and healthcare domains.

For the development of the field of human-robot cooperation, a development and test laboratory for collaborative robotics and process-adaptive devices will be created based on the Virumaa Innovation Centre of Digitalisation and Green Technologies, Virumaa College, and Taltech's headquarters. In the created laboratory, it will be possible to study the psychological aspects of human-machine co-creation, workplace design, etc. In addition, adaptability of equipment/physical systems to production processes. All this in both real and digital (augmented reality) environments, based on the Industry X.0 concept.

Cellulose is the most common biopolymer in the world, which can replace fossil-based plastics and fibers. However, cellulose-based plastics only account for 0.2% and man-made fibers for 1% of the world's production of plastics and non-natural textile fibers. Cellulose needs chemical modification to make these products. Until now, industry has been limited by environmental impact and cost of the process. Cellulose is also the most important biomaterial for Estonia, but industrial cellulose chemistry is limited here. At the same time, this industry gives the highest added value to cellulose. As the biorefineries, output of which is cellulose, are vigorously developing in Estonia, this project develops technology of reactive extrusion, with which cellulose can be valorized in a sustainable manner using residues from production of vegetable oils. The project strengthens cooperation between companies and academy, increases competence in the field, and contributes to academic succession.

The project aims to revolutionise biosensors and point-of-care testing devices by developing sensor arrays using Molecularly Imprinted Polymers (MIPs) as biomimetic receptors for multiplex and/or simultaneous detection of targets that are of significant interest to clinical and environmental health. MIPs offer several advantages over traditional biological recognition elements in being more stable, cost-effective, and reproducible, making them ideal for low-cost and fast recognition of clinically relevant biomarkers and environmental pollutants in complex matrices. We will develop novel synthesis approaches for MIP-based sensor arrays that are affordable and scalable, allowing for the production of large quantities of sensors at low cost. Our innovative approach has the potential to establish a new generation of analytical tools that will significantly improve public health and safety, particularly in critical industries such as healthcare and environmental monitoring.

TIRAMISU “Training and Innovation in Reliable and Efficient Chip Design for Edge AI” is a European HORIZON MSCA Doctoral Network project. The general research objective of TIRAMISU is a practical methodology for reliable and energy-efficient Edge AI hardware backbone design and innovation management. The action will provide strong interdisciplinary training for future European engineers and researchers driving the innovation for reliable and energy-efficient Edge AI chips. The consortium is strategically designed to foster cross-disciplinary synergies, by seamlessly integrating innovation management research with the technical aspects of Edge AI design. The non-academic sector is represented by a European flagship R&D hub for nanoelectronics - IMEC, a global leader in industrial electronics and the largest semiconductor manufacturer in Germany - Infineon, a trusted automotive solutions provider - Dumarey, the worldwide leader in EDA tools development - Cadence. The academic excellence is established by the top ICT and Technology Innovation engineering universities and Europe's largest application-oriented research organisation - Fraunhofer.

This project is based on the new paradigm of "flow as information", a groundbreaking approach for underwater sensing of multiscale flows in Nature. It will lead to new, optimized devices and methods to measure, classify and explore the underwater environment when traditional methods are too expensive or simply do not work. Flow as information is inspired by aquatic animals who have evolved advanced sensory systems which combine sensing and information processing into a single framework. The proposal will advance TalTech's underwater sensing technologies from working prototypes (TRL3 to TRL5) to tests in relevant operational environments (TRL6), and support technology transfer to Estonian and international firms. These devices and methods will provide researchers, industry and authorities with new and reliable sources of flow data during extreme climate and weather events where conventional devices fail and when critical infrastructure is at risk, such as during storm surges and floods.

Data has become the most valuable resource for the automation and optimization of tasks arising both in the private and public spheres. The proposed research area/project aims at strengthening both the synergy and quality of the current research of Taltech in this area, while significantly enhancing the capabilities of Uni to cooperate with Estonian industry and public sphere by joint work, consultations, continuous and regular education. The focus of the project is on using machine learning for data science: ML, in particular deep learning, has shown the most promise in advancing the capabilities of future software systems and empowering the whole business of software development. The concrete goal is to increase the manpower and competence in machine learning, while enhancing and cooperating with the existing areas of data science like data and rule mining, data semantics and knowledge representation, natural language data queries, data integration, statistics and data management.

The overall goal of the project is to increase the number of healthy life years of the population. Currently, Estonia has recorded one of the lowest number of healthy life years at birth in the EU. To achieve this goal, three closely related areas of digital health are researched, developed and piloted. We use the standardized data exchange environment and digital data of the Estonian health information system (EHIS) to develop applications that increase the use of data collected by the person for health promotion, prevention and control of chronic conditions. Second, we focus on sensors and digital applications supported by artificial intelligence (AI) to allow a person to collect both biosignals and textual data in machine-readable form. With this, we speed up the detection of health risks and reduce the healthcare workload. Thirdly, we develop various AI methods by combining the data in EHIS and the Health Insurance Fund's database, as well as the data collected by the person.

The Xpanding Innovative Alliance (XiA) project is dedicated to advancing interoperability within the healthcare sector, particularly in anticipation of the European Health Data Space (EHDS) regulation. Through a comprehensive educational initiative, XiA aims to address the skills gap in advanced digital health interoperability standards among healthcare providers, digital health solution providers, and individuals. By developing high-quality educational materials and courses, XiA seeks to equip stakeholders with the necessary skills to embrace EHDS-related standards and foster a culture of interoperability.

Field of Research: Develops eco-friendly, nonthermal processing methods (HIPEF, HHP) to enhance food safety, nutrient retention, and probiotic viability in plant-based juices, with emphasis on industrial scalability. Specialty: • Primary: Integration of nonthermal technologies (HIPEF+HHP) to achieve synergistic effects—enzyme inactivation, release of bound bioactives (e.g., carotenoids), and stabilization of probiotics in acidic, nutrient-rich juices. • Secondary: Application of in vitro digestion models to evaluate bioactive absorption and optimization of processes for industry-scale adoption. Contributions: Leads experimental design and process trials with HIPEF+HHP, and performs detailed HPLC/MS analysis of bioactive release and digestive stability. Bridges laboratory research with sustainable food processing, supporting nutrient-rich, waste-reducing, and consumer-friendly innovations.

As the concentrations of CO2 in the atmosphere continue to rise, methods for alleviation are desperately needed. Instead of a greenhouse gas, CO2 can also be a valuable resource, but this requires technology to split it up. Among the proposed technologies to split CO2 is its capture and electrolysis in molten salts, turning CO2 into solid carbon and gaseous oxygen. This project aims to further this technology by looking closely at the processes taking place and creating new ways of valorizing the products to create a financial incentive for scaling. Smart utilization of this powerful technology will allow us to not only directly reduce the amount of CO2 in the atmosphere, but also to limit future emissions by empowering CO2-free energy conversion devices such as fuel cells, batteries, and supercapacitors. To keep the CO2 equivalents low and to not offset the positive effect of CO2 capture and utilization, the effect of green chemistry principles and their utilization will also be studied.

The efficient utilisation of bio-based resources is essential for achieving a sustainable, carbon-neutral society. AGRI-WASTE2H2 will focus on straw-derived cellulose – an abundant but underexploited agricultural side-product – as feedstock in an advanced electrochemical process, tailored for enhanced efficiency in the production of green hydrogen with significantly reduced energy consumption compared to standard water electrolysis. At the same time, the process will concurrently produce valuable platform chemicals and materials. AGRI-WASTE2H2 relies on the combined expertise of researchers in three Nordic-Baltic countries – Finland, Sweden and Estonia. The Synthetic Flow Chemistry group at Tallinn University of Technology, Estonia, will focus on transferring the electrochemical oxidation of cellulose into the flow regime, aiming to achieve high efficiency and productivity of the developed transformation. The scaling-up process in flow is a key step for a successful industrial application. AGRI-WASTE2H2 capitalises on the abundance of renewable electricity and agricultural side-streams in the Nordic-Baltic area to produce fuel and chemicals, thereby alleviating the region’s dependence on import of fossil feedstocks. As such, the project will result in tools for reduced CO2 emissions and increased regional resilience, while spurring the growth of new green industries of particular benefit for rural areas. The collaboration between researchers three Nordic-Baltic countries will enable results beyond what the individual partner can achieve alone and promote regional mobility and new collaborations. By leveraging our specialised know-how, we aim to drive innovation tailored to our regional needs and strengths.