Projects

Wood is the most abundant form of biomass used by industry and is the source of the three major biolpolymers in nature – cellulose, hemicellulose and lignin. While cellulose is responsible for about 40-50% of the dry weight of wood, lignin content varies from 10% to about 35% across species. For decades, lignin has been seen as a bothersome side-product that needs removal at all cost. However, in the last decade, due to its polyphenolic nature, lignin has emerged to the focus of attention as a renewable alternative to crude oil based chemistry. The project aims to develop technologies for the extaction and fractionation of lignin and cellulose derived from low valorization level bleached chemi-thermomechanical pulp or industrial wood-waste. The goal of the project is to develop practical and environmentally friendly functional materials (e.g. thermo isolators and surfactants). Also, the project will identify and characterize novel industrial enzymes from extreme thermophilic organisms.

Development of adaptable supramolecular chirality sensors is important for the industry and academia. Chiral molecules, in nform of enantiomers, are commonly used in the pharmaceutical, food, perfume, cosmetic, and agricultural industries. In biological ecosystems, chiral molecules are metabolized, absorbed, and excreted selectively, and their biological effects can vary significantly. Therefore, the environmental impact of different stereoisomers can be radically different. Standard analysis methods that do not distinguish the chirality of molecules may underestimate the effects of these compounds. In this project, we designed and synthesized new receptor molecules through both supramolecular interactions and covalent bonding. By investigating the structure, optical, and supramolecular properties of the obtained receptor molecules, we reached several new compounds with the potential to be applied for separation, isolation, and detection of bioactive compounds and environmental pollutants. We developed environmentally friendly mechanosynthesis methods to reduce waste production during the synthesis process of organic compounds. Additionally, we studied formation of oligomeric macrocyclic receptors and developed methods for obtaining both mono- and multifunctional macrocyclic compounds. We initiated research on the creation of supramolecular materials and demonstrated that materials for enantioselective electronic noses can be easily prepared using porphyrins and chiral hemicucurbiturils. We also investigated the correlation between the circulardichroism signal generation and molecular orbitals and geometries modelled by quantum chemical methods. We also showed that the signal of the studied optically active sensor molecules can be amplified via interaction with inorganic chiral materials. The results of the project were published in number of research articles and two patents were applied for.

Prolonging the shelf life of food is important to reduce food losses in supply chain and consumption as well as enable products to be marketed longer distance. Measures to extend the shelf life are directly related to food safety and quality; however, its sensory properties are best within a certain optimal shelf life. Although human sensory receptors are set by nature to identify food safety risks, good taste does not necessarily guarantee food safety and vice versa. Safety risks are particularly high for unpasteurised products with neutral pH. The temperature of 2-6°C used in the supply chain does not prevent the growth of spoilage, including pathogenic, bacteria and thus limits the shelf life. This project explores various technical options for extending the shelf life of food without sacrificing safety and quality: incl. aseptic production, rapid cooling, use of ice binding proteins and storage temperatures of -2...0°C as well as control of essential flavor components.

The basic structure and dynamics of Estonian energy and transport systems can be traced back to Western industrial states in the interwar era. Currently both systems produce large negative environmental impacts: furthermore, unequal distribution of these impacts intensifies social inequality. Estonia's success in the field of information technology might help to alleviate these tendencies. However, studies show that careless application of ICT-s might lead to worsening environmental and social conditions. The project focuses on three Estonian systems – energy, transport, communications – aiming to analyse their history and to design interventions for shaping their development onto sustainable and just path without repeating the past mistakes of industrial societies in developing, applying and regulating technologies. It is based on a novel Deep Transitions framework, conceptualizing the evolution of industrial society through the interactions of socio-technical systems.

The most significant findings are related to development of the novel wireless closed-loop patient support system i) energy-efficient protocols for body area networks and ii) fast computing methods for the real-time gait analysis. These novel contributions are relevant for the electrical stimulation of the muscles of the patients suffering from neurological diseases (e.g., multiple sclerosis), in particular assisting them with daily life activities. The outcomes of the project are significantly relevant to society because they directly enhance the state-of-the-art assistive devices. The project has created a wider impact in the following ways: 1- ETSI SmartBAN Standard: “Applying SmartBAN MAC (ETSI TS 103 325) for various use-cases”, Work Item Reference, DTR/SmartBAN-0014, Rapporteur, Muhammad Mahtab Alam, -- ETSI SmartBAN is a specific standard for the low-power body area networks and this project usecase is introduced in this workitem which motivated the needs for the future standard compliant devices. 2- Invention: System and method for self-assessment of physical capabilities and condition changes; Owners: Tallinn University of Technology, Motionmon OÜ; Authors: Alar Kuusik, Katrin Gross-Paju, Muhammad Mahtab Alam; Priority number: US16/268134; Priority date: 5.02.2019. 3- Collaboration with Hospitals: We had a positive collaboration with i) East Tallinn Central hospital and ii) West Tallinn Central hospital with specific neurological departments. The methods developed in this project and future devices (beyond this project) comply with the needs of the patients and this will enable enhanced comfortable and effective non-invasive electrical stimulation devices to be used by the patients. Overall, the project yielded significant research output in terms of numbers of scientific publications including 9 Journal and 13 conferences of high quality and impact. So far, these papers are strongly cited by the relevant research community (h-index=9, h-10=9).

In the course of the project, the possibilities of using various materials produced by the chemical valorization of cellulose for the collection of electrical energy using the triboelectric method are investigated. In the Laboratory of Biopolymer Technology of Tallinn University of Technology, cellulose derivatives are prepared and nanofibrous non-woven materials are produced from them by electrospinning. The main physical properties of non-woven materials are determined. Project partner RISE constructs triboelectric devices from the non-woven materials and evaluates their ability to produce electricity.

This collaborative project is an integrated fundamental study to (i) elaborate and tune approaches for fast detection of the CWA and their transformation products and (ii) propose decontamination formulation(s) for fast and irreversibly decontamination with as lowest impact to the personnel and the environment as possible. The versatile portable and user-friendly all-weather and all-terrain kits for certified First Responders and spontaneous volunteers are to design. The methods and formulations to be developed are based on the recent research developments and designed in accordance with the requirements of green and sustainable chemistry, including green chemistry metrics approach.

The main aim of the study is to review the published scientific data and, based on the analysis, to develop the expert opinion by the Estonian scientific community about the possible health effects caused by nonionizing radiation, including 5G generation mobile communication. Based on the analyses, the recommendations for modification of the nonionizing radiation safety requirements will be proposed. The additional aim of the study is to measure the actual levels of radiofrequency radiation and to determine the worst case in the sufficient number of points in areas close to base stations, including 5G base stations, for analyzing the radiofrequency situation in the public environment in Estonia. As the result of the study, the conclusions will be drawn up in radiofrequency EMF health effects and possible modification will be proposed for the regulations for health protection of the general population.

Chiral pollution is an environmental topic of crucial importance, considering that a large number of chemicals spreading into the environment, for example pesticides, are chiral substances. However, usually the stereoisomerism of contaminants is not considered, although the biological activity of enantiomers is significantly different, making their recognition critical for environmental control. Enantiomeric excess is currently determined by off-site analysis, requiring collection, transportation, eventual pre-treating of the sample, and expensive instrumentations and specifically trained staff. Thus, providing devices able to allow for rapid on site detection and chiral discrimination of target analytes would have a dramatic impact in all the fields of environmental control with significant economic benefits. The development of chemical sensors has been conceived to bypass restrictions related to classical analytical protocols and supports the use of conventional laboratory techniques for environmental control. While the technological foundation for chemical sensors already exists, it has been difficult to apply them to chiral discrimination and analysis, due to the lack of suitable solid state receptors. The main aims of the project are: a) the development of novel molecular receptors, mainly based on porphyrin derivatives, b) integration of the receptors with different nanostructures and characterization of their solid state organization, c) deposition of the structures onto transducer surfaces, d) testing and validation of the new chemical sensor devices with enantiomeric pairs of model analytes. The synergistic complementary know-how of six academic units and two private companies will allow a breakthrough development through delivery of sensing probes ranging from the synthesis of macrocyclic molecular receptors to the building and testing of analytical and electronic parts for final, field-capable devices.

The project is focused on developing molecular diagnostics tools for early detection of schizophrenia. The research program of SZ_TEST will include three interrelated lines of research: 1: Deciphering molecular mechanisms of schizophrenia. 2: Identifying molecular biomarkers for early detection of schizophrenia. 3: Developing reliable protocols for diagnostic use of newly identified biomarkers in clinical settings.

Drug Hunter is a portable analyzer for the detection of narcotics in saliva. The project's goal was to integrate machine learning methods into an expert system for substance detection to reduce the competence required of the analyzer's user to interpret the results and thereby reduce errors in substance detection. Various machine learning methods based on supervised learning - artificial neural networks - were tested during the project. In order to prepare (annotate) the data necessary for training the neural network, a cloud service was created, where the technical parameters of all analyzes and the obtained electropherograms, on which the substances to be analyzed were marked, were stored. The best results in detecting electrophoretic patterns were obtained using a convolutional neural network (CNN). The analyzer was tested in cooperation with Estonian Police at roadside drug testing raids in Estonia.

Wireless biomedical sensors should dramatically reduce the costs and risks associated with personal health care while being more and more exploited by telemedicine and efficient e-health systems. However, because of the large power consumption of continuous wireless transmission, the battery life of the sensors is reduced for long-term use. Sub-Nyquist continuous-time discrete-amplitude (CTDA) sampling approaches using level-crossing analogto- digital converters (ADCs) have been developed to reduce the sampling rate and energy consumption of the sensors. However, traditional machine learning techniques and architectures are not compatible with the non-uniform sampled data obtained from levelcrossing ADCs. This project aims to develop analog algorithms, circuits, and systems for the implementation of machine learning techniques in CTDA sampled data in wireless biomedical sensors. This “near-sensor computing” approach, will help reduce the wireless transmission rate and therefore the power consumption of the sensor. The output rate of the CTDA is directly proportional to the activity of the analog signal at the input of the sensor. Therefore, artificial intelligence hardware that processes CTDA data should consume significantly less energy. For demonstration purposes, a prototype biomedical sensor for the detection and classification of sleep apnea will be developed using integrated circuit prototypes and a commercially available analog front-end interface. The sensor will acquire electrocardiogram and bioimpedance signals from the subject and will use data fusion techniques and machine learning techniques to achieve high accuracy.

New viral species and strains are continuously emerging over time around the world. They can originate either from fully unknown taxa or related to known viruses that evolve changing their geographical distribution and/or ecological niche. Cereals are the most important crops for human food and animal feed. Therefore, there is a paramount need to monitor carefully viruses able to jump on cereals and to investigate in detail the mechanisms of viral emergence. In this project, our aim is to understand how cereal sobemoviruses and common ancestors emerged from wild plants and diverged to different viral species with different host ranges. Investigating the evolvability of cereal sobemoviruses, we will contribute to evaluate the risk of host jumps and viral emergence on cereals. To fulfill this aim, we plan to implement two parallel approaches: (i) a comparative one using taxonomy analyses based on protein structure alignments in addition to sequence alignments and (ii) an experimental one searching for a common host plant for different sobemoviruses and assessing viral fitness of each species.