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Efficient Synthesis of Large Finite Patch Arrays for Scanning Wide-Angle Anomalous Reflectors
No full text| openaire: EC/H2020/956256/EU//META WIRELESSA design methodology for planar loaded antenna arrays is proposed to synthesize a perfect anomalous reflection into an arbitrary direction by optimizing the scattering characteristics of passively loaded array antennas. It is based on efficient and accurate prediction of the induced current distribution and the associated scattering for any given set of load impedances. For a fixed array of finite dimensions, the deflection angles can be continuously adjusted with proper tuning of each load. We study and develop anomalous reflectors as semi-finite (finite × infinite) and finite planar rectangular arrays comprising printed patches with a subwavelength spacing. Anomalous reflection into an arbitrary desired angle using purely reactive loads is numerically and experimentally validated. Owing to the algebraic nature of load optimization, the design methodology may be applied to the synthesis of large-scale reflectors of practical significance.Peer reviewe
The Emerging Energy Citizenship - User-Centred Approach for Seasonal Demand Response in Multi-Source Energy Houses
No full textFunding Information: This work has received funding from European Union Horizon 2020 programme under grant agreement No 856602 (FINEST TWINS). 979-8-3503-1258-4/23/$31.00 ©2023 IEEE | openaire: EC/H2020/856602/EU//FINEST TWINSThe production of significant amounts of renewable energy in a decentralized manner within the energy market is involving broader audiences. Citizens participate more actively in the energy markets. However, this happens through the production of relatively small amounts of energy at individual and distributed production sites. This brings benefits to the grids and energy system, but also makes the system more complex to manage. Citizens' motivations for such production differ a lot from the traditional industry-scale energy production. User-and prosumer-originating incentives introduce new aspects for modelling the development, construction, and governance of renewable small-scale units for the energy system. Individual and value-based aspects have a stronger role in the willingness and ability to participate in the green transformation of the energy system and markets. This paper introduces the user-based modelling and analysis of the role of a smart town house, which can have an active role in the power grids and energy markets. When such multi-source energy houses become more common and house fleets are interconnected to power grids, those can have significant impact to the development of energy markets.Peer reviewe
Concrete lamp design - Exploring the possibilities of waterjet cutting in concrete product design
No full textAbrasive Waterjet (AWJ) technology, currently under extensive research, stands out for its proficiency in cutting materials of varying thicknesses using high-pressure water streams. Achieving precise cuts on thick materials remains a significant focus in technology and engineering. Nonetheless, the versatility of AWJ technology in handling diverse materials presents opportunities for innovative design solutions. This study focuses on concrete, chosen for its accessibility, cost-effectiveness, and suitability for thick material applications. While casting is the conventional method for concrete product design, this research explores whether AWJ technology could offer new opportunities in this field. By investigating the potential applications of AWJ technology in concrete design, specifically in developing a concrete lamp from a designer's perspective, this study aims to uncover novel avenues for creative design approaches. The findings seek to leverage the unique capabilities of AWJ to push the boundaries of traditional concrete product design, offering new possibilities for innovation and functionality
Decarbonizing a national energy system through electrification by sector coupling power, district heat, transport and buildings
No full textPublisher Copyright: © 2025 The AuthorsThe energy sector is responsible for the majority of emitted carbon dioxide (CO2) emissions globally. This study examined the achievable CO2 emission reductions with electrification through sector coupling, in a national energy system. The analysis included electrification of district heat generation, passenger vehicle transport and building stock, while simultaneously the share of wind, solar photovoltaics and nuclear power were increased in power generation. With the increased emission free power generation and sector coupling of the electrified energy sectors, significant emission reductions were achieved, as the set 95 % emission reduction target of 1.77 megatons (Mt) CO2 was reached with several scenarios. This target was reached with and without increased nuclear power capacity, however, without increased nuclear power with 610 million euros higher annual costs. The least costly scenario to achieve this target had annual costs of 25.4 billion euros (14.2 for vehicles, 7.1 for electricity generation, 0.9 for district heat generation and 3.2 for the building stock). A 90 % emission reduction target was achieved with only 150 million euros lower annual costs. Without retrofits conducted in the building stock, or without electric vehicles, the 95 % reduction target was not achieved. In addition, required dispatchable reserve power capacity was significant, 14–41 % of peak load, whereas excess power generation varied between 6 % and 28 %. For district heating, thermal storage was found to be the least costly measure to obtain further emission reductions. Annual variations were great for both emissions (2.9 Mt. CO2) and the reserve power requirement (3 gigawatt).Peer reviewe
The Effect of Lead in Copper Electrorefining
No full textTo meet the rising copper demand, the industry decides to recycle secondary copper sources for copper production. It results in more impurities including lead appearing in the electrorefining process at the end of the copper production process. There are numerous studies that investigate the effects of some impurities like Ni, As, Sb, and Bi, but there are only a few studies that focuses on lead and its effects. As a result, this study explores the effects of lead in the copper electrorefining process and assess the risk of lead contamination in copper cathodes when copper anodes contain more impurities. This study finds that almost all of the lead impurities in copper anodes accumulate in the anode slime as PbSO4. It causes the anode slime to become thicker and more adhesive which results in passivation of the anodes and nodulations on copper cathodes. Consequently, it promotes lead and other impurities contamination in copper cathodes. Therefore, this study concludes that it can be a notable risk of lead contamination in copper cathodes when copper anodes contain high impurities content. However, the risk can be mitigated and controlled, so it should not pose much of a problem to the industry
Purification of Ionic Liquid [mTBDH][OAc] Utilizing the Short-Path Distillation Technique
No full textPublisher Copyright: © 2025 The Authors. Published by American Chemical SocietyThe Ioncell process is an innovative approach to producing sustainable textiles using an ionic liquid (IL) as a solvent, but this process generates side products and impurities that have negative effects on its solvent dissolution capability. Therefore, the purification of the IL is of utmost importance. 7-Methyl-1,5,7-triazabicyclo[4.4.0]dec-5-enium acetate, [mTBDH][OAc], is a suitable alternative to replace existing solvents for the application of cellulose dissolution in the Ioncell process. 7-Methyl-1,5,7-triazabicyclo(4.4.0)dec-5-ene (mTBD) is an expensive base, and consequently, a closed loop operation, without any losses, is desirable. Additionally, high recovery of the base and effective removal of the impurities from the IL are necessary for making the process sustainable. Understanding the interaction of the IL with impurities is essential to purify mTBD and, thereby, the IL. This study focuses on the purification of [mTBDH][OAc] in the presence of different impurities. KCl, NaCl, CaCl2, lactic acid, xylan, and the hydrolysis products, 1-[3-(methylammonio)propyl]-1,3-diazinan-2-onemium acetate (H-mTBD-1) and 1-(3-ammoniopropyl)-3-methyl-1,3-diazinan-2-onemium acetate (H-mTBD-2), were the impurities utilized to understand the IL-impurity interactions. Suitable conditions for purification were determined using a short path distillation (SPD) unit while varying the feed flow rate to investigate the recovery of the base mTBD at different mass fractions. SPD results indicated that the highest recovery fractions (0.97–1.00) were observed at the lowest flow rates(0.378 kg/h). Experimental results also confirmed that approximately 75–100% of the base mTBD can be recovered in most cases. Overall, the results of the experiments confirm that the impurities K, Na, Ca, xylan, and lactic acid can be removed from the feed using an SPD unit.Peer reviewe
Icosahedral Clusters [In@Tr12]10– :Synthesis, Characterization, and Electronic Structure Investigations of Na4A6Tr13 (A = Rb, Cs; Tr = In, Tl)
No full textPublisher Copyright: © 2025 The Author(s). European Journal of Inorganic Chemistry published by Wiley-VCH GmbH.While thallium forms several clusters in alkali metal thallides, indium clusters in related alkali metal indides are very rare. Here the mixing of the heavy trielides indium and thallium to approximate icosahedral entities present in Na4A6Tr13 (A = K, Rb, Cs; Tr = In, Tl) is reported. Experimental results prove that at least up to 76% indium can be introduced in this structure type. From the moment indium is provided, the central atom of the icosahedral unit changes from thallium to indium, while the vertices of the cluster are mixed occupied by both, thallium and indium. The bonding and energetics of the compounds are investigated with quantum chemical methods.Peer reviewe
“Please wait patiently”: When bureaucratic waiting becomes the service
No full textWaiting for citizenship is not just a delay but an experience influenced by uncertainty and limited information. This thesis examines how Finnish citizenship applicants navigate bureaucratic waiting through qualitative interviews and observations of online communities. It focuses on how individuals manage uncertainty, search for updates, cope with emotional strain, and maintain agency in a high-stakes service context. The study draws on public administration and service research to show how waiting becomes a lived and strategic part of the citizenship process.
Five response strategies are identified: Enduring, Connecting, Investigating, Escalating, and Disengaging. These themes reflect how applicants co-create value (and sometimes co-destruction) through peer support and advocacy while also showing the limits of co-creation under extreme power imbalances. The findings revel tensions between consumer behaviour literature, which often assumes short and voluntary waiting, and real-world bureaucratic delays that put people’s lives on hold.
This thesis contributes theoretical insights into value co-creation in public services and has practical implications for making bureaucratic waiting more humane. The thesis argues that treating applicants as partners and providing transparency and support can transform waiting from a period of despondency into a more managed service experience
Optimisation of disordered lattices
No full textLattice as a metamaterial has been used to customise macroscopic mechanical properties while reducing weight by lowering density. Localised damage limits mechanical property enhancement in periodic lattices. Therefore, disordered lattices have gained attention due to their effect on lowering localised damage. However, the correlation between disorder levels and macroscopic properties is missing. In addition, many disorder optimisation frameworks are based on advanced machine learning models. This thesis aims to provide a guideline and a framework. The guideline is based on the correlation between macroscopic mechanical properties and two disorders in coupled and decoupled conditions on a planar regular triangular lattice. The framework encompasses disordered design generation to disorder optimisation, which includes a Feedforward Neural Network (FNN) to enhance the original periodic design with disorders.
The disorder-property correlation is based on the perturbation process that introduces nodal position and thickness disorders on a periodic lattice, ranging from 0% to 40% of the original strut length and from 0% to 39% of the original strut thickness, respectively. Stiffness, maximum force, and fracture work are extracted from the force-displacement curves in 34000 simulations. The results show that increasing the disorder level in this planner triangular lattice tends to lose stiffness when the maximum force can be optimised to perform slightly better than the periodic design. However, fracture work can be improved significantly by around 25% on average when disorder optimisation is applied. In decoupled correlations, thickness disorder has less weakening effect than positional disorder. In the coupled correlations, all thickness disorders with positional disorders between 0% and 10% are showing good mechanical properties, while extreme cases (30–40% positional or 39% thickness disorders) should be avoided. Finally, suppose further selection is required to identify the disorder exhibiting optimal potential across all three mechanical properties. In that case, preference should be given to a disorder characterised by a 26% thickness disorder with no positional disorder.
An FNN learns the complex pattern among nodal positions, strut thicknesses, and three macroscopic mechanical properties from 34000 simulations. The network prediction reaches over 92% accuracy in all three properties. The optimisation follows a sample-based approach that uses the trained FNN to find three new disorder designs with similar or better properties than customised standards in 25 minutes. It is at least 24 times faster than using the Finite Element Method (FEM) with the exact 1000 design sampling
Yksisolusekvensointidatan hierarkinen annotaatio käyttäen suuria kielimalleja
No full textThis thesis investigates whether hierarchical clustering combined with large language models (LLMs) can improve cell type annotation in single-cell RNA sequencing (scRNA-seq) data. To this end, a pipeline named GPTree was developed. It implements recursive clustering followed by LLM-based interpretation of cluster marker genes, mimicking the hierarchical approach commonly used in manual annotation. GPTree was compared to GPTCelltype, an LLM-based annotation method, and SingleR, a reference-based tool, across multiple human tissue datasets. The performance was evaluated using accuracy scoring and match type percentages. Parameter sensitivity analysis confirmed the stability of the clustering algorithm. The results show that GPTree achieves similar or improved accuracy compared to GPTCelltype, particularly at broad cell type levels, and outperforms SingleR in most cases. These findings suggest that recursive clustering combined with LLM-based annotation offers a biologically intuitive and effective approach for automated cell type identification.Tässä työssä tutkittiin, parantaako hierarkinen klusterointimenetelmä suurten kielimallien (LLM) tuottamia solutyyppiannotaatioita yksisolusekvensointidatassa. Tutkimus suoritettiin laatimalla GPTree-niminen menetelmä. Se hyödyntää rekursiivista klusterointia, sekä suurta kielimallia klusterien markkerien tulkitsemiseen ja annotaatioon. Tämä lähestymistapa mimikoi yleisesti manuaalisessa annotaatiossa käytettyä hierarkista menetelmää. GPTree:tä verrattiin GPTCelltype:en, joka on myös suuriin kielimalleihin perustuva annotaatiotyökalu, sekä SingleR:ään, joka perustuu referenssidataan. Vertailussa käytettiin useita yksisolusekvensointidatasettejä erilaisista ihmiskudoksista. GPTree:n suorituskykyä arvioitiin käyttämällä tarkkuuspisteytystä sekä vastaavuusluokkia. Lisäksi herkkyysanalyysissä tarkasteltiin klusterointiparametrien vaikutusta tuloksiin. Tulokset osoittivat, että GPTree saavuttaa samankaltaisen tai paremman tarkkuuden kuin GPTCelltype erityisesti laajojen solutyyppien tasolla ja päihittää useimmiten SingleR:n. Tulokset viittaavat siihen, että rekursiivinen klusterointi yhdistettynä LLM-pohjaiseen annotaatioon tarjoaa biologisesti intuitiivisen ja tehokkaan lähestymistavan solutyyppien automaattiseen tunnistamiseen