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Environmental impact of material's supply chain disruption - The cases of Aluminium and Lithium
No full textThis report is a continuation of pilot studies initiated in 2023 to address the European Union's susceptibility to critical raw materials (CRMs) supply chain disruptions and subsequent their environmental implications. The report refines the analytical framework previously developed and proposes a practical tool designed to analyse the complex environmental impacts of specific materials. This tool identifies key variables, considers practical assumptions, and selects alternative supplying countries. It tests the framework's applicability to two materials, aluminium (Al) and lithium (Li). The findings indicate that shifting aluminium supply to domestic EU sources and enhancing recycling capacity can significantly reduce environmental impacts. For lithium, short-term shifts to alternative suppliers are complex, medium- and long-term measures, including increased recycling and expanded refining capacity within the EU, could prevent significant annual CO2 emissions. The report underscores the critical role of supply chain decisions, investment in recycling technologies, and domestic production in mitigating environmental impacts
Very-Large-Scale Integration-Friendly Method for Vital Activity Detection with Frequency-Modulated Continuous Wave Radars
No full textA simple algorithm for respiratory activity detection in data produced by Frequency-Modulated Continuous-Wave (FMCW) radars is presented in this paper. The proposed computational architecture can be directly mapped onto custom digital–analog VLSI hardware, which is a unique approach in research on intelligent FMCW sensor development, offering a potential energy-efficient data analysis solution for target applications, such as preventing human trafficking or providing life-sign detection under limited visibility. The algorithm comprises two main modules. The first one summarizes radar-produced data into a descriptor reflecting the amount of motion that occurs within appropriately determined time intervals. The second one classifies a sequence of the produced descriptors using a recurrent neural network composed of gated recurrent units. To ensure the algorithm’s implementation feasibility, an analog VLSI circuit comprising its main functional blocks has been designed, manufactured, and tested, providing constraints for neural model derivation. The adverse effects of the primary constraint, the severe restriction on admissible weight resolution, have been handled by introducing a novel training loss component and a simple mechanism for diversifying the effective weight sets of different network neurons. Experimental evaluation of the presented method, performed using the dataset of indoor recordings, indicates that the proposed simple, hardware implementation-friendly algorithm provides over 94% human detection accuracy and similar F1 scores.</p
Deformation and adiabatic heating of single crystalline and nanocrystalline Ni micropillars at high strain rates
No full textThe deformation behavior of single crystal and nanocrystalline nickel were studied using in situ micropillar compression experiments from quasi-static to high strain rates up to 103 s−1. Deformation occurred by dislocation slip activity in single crystal nickel whereas extensive grain boundary sliding was observed in nanocrystalline nickel with a shift towards more inhomogeneous, localized deformation above 1 s−1. The strain rate sensitivity exponent was found to change at higher strain rates for both single crystal and nanocrystalline nickel, while the overall strain rate sensitivity was observed to be of the same value for both. With increasing high strain rate micropillar compression tests being reported, the issue of adiabatic heating in micropillars becomes important. We report crystal plasticity based finite element modeling to estimate the adiabatic heating, spatially resolved within the micropillar, at the highest tested strain rates. The simulations predicted a significant temperature rise of up to 200 K in nanocrystalline nickel at the grain boundaries, and 20 K in single crystalline nickel due to strain localization. Transmission Kikuchi Diffraction analysis of nanocrystalline nickel micropillar post compression at 103 s−1 did not show any grain growth.</p
Intermetallic dispersion-strengthened ferritic superalloys with exceptional resistance to radiation-induced hardening
No full textIntermetallic dispersion-strengthening (IDS) using nano-scale coherent intermetallic precipitates offers a potent strategy to produce high-strength and radiation-resistant steels, whilst addressing the manufacturability challenges of analogous oxide dispersion-strengthened (ODS) steels. However, their performance with intermetallic stability under irradiation damage, such as radiation-induced hardening (RIH), whilst hypothesised, is undemonstrated. Here, we report on a model IDS α(A2) + α’(L21) Fe-Ni-Al-Ti ferritic superalloy, which exhibits exceptional resistance to RIH with near-zero hardening after irradiation at 300°C 1 dpa, in contrast to significant RIH in a counterpart coarse precipitate alloy (increase in nano-hardness of 1.0 GPa) and Eurofer97 (0.7 GPa). This irradiation resistance is attributed to the high density of semi-coherent precipitate-matrix interfaces, and partial-disordering L21->B2 which causes a decrease in anti-phase boundary energy. High interface density with localised interfacial strain offers effective sinks, suppressing defect populations compared to the counterpart with lower interface density. Meanwhile, atomic resolution spectroscopy and irradiation with in-situ transmission electron microscopy show that the disordering stems from Al-rich and Ti-rich sublattices mixing in the initial L21-Ni2AlTi structure below 500°C, forming metastable B2-Ni(Al,Ti). Combined, the high interface density and radiation-induced intermetallic disordering underpin the remarkable radiation tolerance, demonstrating the IDS concept as a promising radiation-resistant materials design strategy
Forest Height and Volume Mapping in Northern Spain with Multi-Source Earth Observation Data:Method and Data Comparison
No full textAccurate forest monitoring is critical for achieving the objectives of the European Green Deal. While national forest inventories provide consistent information on the state of forests, their temporal frequency is inadequate for monitoring fast-growing species with 15-year rotations when inventories are conducted every 10 years. However, Earth observation (EO) satellite systems can be used to address this challenge. Remote sensing satellites enable the continuous acquisition of land cover data with high temporal frequency (annually or shorter), at a spatial resolution of 10-30 m per pixel. This study focused on northern Spain, a highly productive forest region. This study aimed to improve models for predicting forest variables in forest plantations in northern Spain by integrating optical (Sentinel-2) and imaging radar (Sentinel-1, ALOS-2 PALSAR-2 and TanDEM-X) datasets supported by climatic and terrain variables. Five popular machine learning algorithms were compared, namely kNN, LightGBM, Random Forest, MLR, and XGBoost. The study findings show an improvement in R2 from 0.24 when only Sentinel-2 data are used with MultiLinear Regression to 0.49 when XGboost is used with multi-source EO data. It can be concluded that the combination of multi-source datasets, regardless of the model used, significantly enhances model performance, with TanDEM-X data standing out for their remarkable ability to provide valuable radar information on forest height and volume, particularly in a complex terrain such as northern Spain.</p
Traffic-related diesel pollution particles impair the lysosomal functions of human iPSC-derived microglia
No full textExposure to air pollution is associated with neurological diseases. Traffic is a major source of air pollution, consisting of a complex mixture of ultrafine particles, that can invade the brain and induce a microglia-mediated inflammatory response. However, the exact mechanisms of how traffic-related particles impact human microglia remain poorly understood. This study investigates the effects of diesel exhaust particles (DEPs) on human induced pluripotent stem cell-derived microglia-like cells (iMGL). We exposed iMGLs to three different DEPs and studied the impact on the iMGL transcriptome and functionality, focusing on cytokine secretion, mitochondrial respiration, lysosomal function, and phagocytosis. A20 particles were collected from a heavy-duty engine run with petroleum diesel. For A0, the same engine was run with renewable diesel. E6 was produced with a modern 2019 model diesel passenger car run with renewable diesel. RNAseq revealed activation of the cytokine storm pathway and inhibition of the autophagy pathway in iMGLs after exposure to particles derived from older diesel emission technology (A20, A0). Particles from the modern diesel engine technology (E6) did not alter microglial transcriptome after 24 h exposure. A20 and A0 exposure led to impaired lysosomal functions in iMGLs. In contrast, E6 did not cause major alterations in microglia functions. In addition, we show that response to particles is more pronounced in human iMGLs compared to mouse primary microglia. To conclude, particles from older emission technology impair phago-lysosomal functions of iMGLs, but modern alternatives with filtration do not induce drastic changes in the functionality of iMGLs.</p
One year of high-frequency monitoring of groundwater physico-chemical parameters in the Weierbach experimental catchment, Luxembourg
No full textThe critical zone (CZ) is the skin of the Earth, where rock, water, air, and life interact, playing a pivotal role in sustaining ecological processes and life-supporting resources. Understanding these interactions, especially in forested headwater catchments, is essential to manage water resources, predict environmental responses, and assess human impacts. Here, we present a novel dataset from the Weierbach experimental catchment in Luxembourg, derived from a year-long high-frequency monitoring campaign focused on groundwater physico-chemical parameters. Through rigorous data collection and quality control, parameters such as electrical conductivity, dissolved oxygen, oxidation–reduction potential, and pH were measured, providing insights into the CZ’s hydrological and biogeochemical dynamics. Although the 1-year dataset offers valuable observations, it represents an initial step toward understanding long-term patterns. The data highlight the interaction between redox reactions, pH, and seasonal hydrological variability, although these interpretations are limited by the temporal scope of the study. By offering a detailed snapshot of the response of the catchment to hydrological variations, this dataset contributes to addressing key gaps in CZ research and serves as a foundation for advancing our understanding of hydro-biogeochemical processes at the catchment scale. Despite the limited observation period, the dataset provides insights that can be integrated with long-term monitoring efforts. Researchers and practitioners can use these data to refine models, inform land management decisions, and improve our understanding of the biogeochemistry of the catchment. Researchers and practitioners can use these data to refine models, inform land management decisions, and improve our understanding of the biogeochemistry of the catchment.</p
Tieliikenneturvallisuuden indikaattoritiedot: Trendline-tutkimushanke
Get PDFEuroopan komission osarahoittamassa Trendline-hankkeessa 25 EU-maata keräsi tietoa yhteensä kahdeksasta tieliikenneturvallisuuden indikaattorista. Suomessa kerättiin tiedot kuudesta indikaattorista, joiden tulokset kuvataan tässä raportissa. Lisäksi esitellään kolme kokeellista indikaattoria (enintään 30 km/h nopeusrajoitettujen teiden osuus, liikennevalvonta ja vaihtoehtoiset ylinopeusindikaattorit), joiden kehittämiseen ja kokeiluun Suomi osallistui.Tiedonkeruu Suomessa toteutettiin kuudesta indikaattorista, joiden päätulokset olivat:• Nopeusrajoitusta noudattavien vapaiden ajoneuvojen osuus: henkilö- ja pakettiautoista 42 % ja kuorma-autoista 30 % (vuonna 2023).• Turvavyötä käyttävien ajoneuvomatkustajien (ml. kuljettajat) osuus: Yhteensä 97 %, moottoritiellä 98 %, maantiellä 96 %, taajamatiellä 97 %, arkipäivisin 96 % ja viikonloppuisin 98 % (vuonna 2024).• Kypärää käyttävien polkupyöräilijöiden osuus: Yhteensä 70 %, taajaman ulkopuolella 77 %, taajamassa 66 %, arkipäivisin ja viikonloppuisin molempina 70 % (vuonna 2024).• Henkilöautokuljettajien osuus, joiden veren alkoholipitoisuus ei ylittänyt sallittua rajaa: Matkaperusteisen kyselyn (satunnainen matka, vastaajien oma arvio) mukaan 99,5 % ja aikaperusteisen kyselyn (edellisen 30 päivän aikana, vastaajien oma arvio) mukaan 89,8 % (vuonna 2024). Poliisin R-tutkimuksen aineiston perusteella vastaava osuus oli 99,8 % (syksy 2023 ja kevät 2024).• Ajoneuvokannan turvallisuus: uusista henkilöautoista 89 % sai Euro NCAP -luokituksessa vähintään 4 tähteä ja 75 % henkilöautoista sai 5 tähteä (vuonna 2023).• Vasteaika tieliikenneonnettomuuksissa: henkilövahinko-onnettomuuksien jälkeen pelastushenkilöstö saapui onnettomuuspaikalle 95 % tapauksista 24 minuutissa ja 50 sekunnissa tai nopeammin (vuonna 2023).Suomessa osallistuttiin myös kolmen kokeellisen indikaattorin kehittämiseen ja kokeiluun. Vaihtoehtoisten ylinopeusindikaattoreiden tulosten mukaan ylinopeus on henkilö- ja pakettiautoilla tyypillisesti 1–10 km/h (43,1 %). Enintään 30 km/h nopeusrajoitettujen taajamateiden pituuden osuuden indikaattorin puitteissa kehitettiin menetelmä, joka kuvaa jalankulkijoille ja polkupyöräilijöille turvallisten teiden osuutta huomioiden nopeusrajoituksen lisäksi tieosuudet, joiden rinnalla kulkee fyysisesti eroteltu jalankulun ja pyöräilyn väylä. Tulosten mukaan jalankulkijoille ja polkupyöräilijöille turvallisten taajamateiden osuus on Suomessa noin 60 %. Puolestaan liikennevalvontaindikaattori tarjoaa kokonaiskuvaa liikennevalvonnan toteutuksesta Suomessa ja sen seuraaminen voi tulevaisuudessa tukea valvontajärjestelmän kehittämistä.Trendline-hankkeessa kerätyt indikaattoritulokset antavat kuvan Suomen liikenneturvallisuuden tilasta ja kehitystarpeista.<br/
Understanding interactions of pharmaceutical pollutants with cellulosic materials
Get PDFThis research examines the interaction mechanisms of pharmaceutical pollutants ibuprofen (IBP) and naproxen (NPR) (anti-inflammatory compounds), and 17α-ethinyl estradiol (EE2) (estrogenic compound) with cellulosic materials via adsorption studies utilizing Surface Plasmon Resonance (SPR) technique. The goal was to identify the key factors affecting the affinity between cellulose materials and pollutants in a systematic fashion with real-time adsorption monitoring to support the development of sustainable water purification technologies. The anti-inflammatory and estrogenic compounds were adsorbed on ultrathin films (thickness ~ 10-20 nm) of nanocellulose with varying surface charge (mechanically disintegrated cellulose nanofibrils (CNF) and TEMPO-oxidized cellulose nanofibers (TCNF)), and polymeric cellulose with varying degree of hydrophobicity (regenerated cellulose (RC), cellulose triacetate (CTA) and trimethylsilyl cellulose (TMSC)). Highly hygroscopic and negatively charged nanocellulose surfaces showed low affinity for drugs, while regenerated cellulose exhibited higher adsorption capacity probably due to its amphiphilic nature. Indeed, the hydrophobic character of cellulose derivatives was found to significantly impact pharmaceutical adsorption, especially in case of EE2. Hydrophobic TMSC and CTA films demonstrated adsorption for hormonal pollutant, with nearly ten-fold higher adsorption than anti-inflammatory compounds. Pharmaceuticals were detectable on hydrophobized cellulose surfaces at trace concentrations of 0.1–1 µg/mL. Langmuir adsorption model showed the highest adsorption coefficient for EE2 on TMSC, emphasizing its efficacy at capturing hormonal pollutants at low concentrations. Adsorption was mostly irreversible after rinsing, highlighting the need for specific modifications to cellulose to achieve desired selectivity and efficiency for pollutant removal. These findings aid in designing efficient membrane and sensor systems for capturing and purifying pharmaceutical-contaminated water streams
EMPIR 18SIB08 ComTraForce - Final Publishable Report
Get PDFInternationally competitive high-tech products use highly efficient materials including carbon fibre, high strength steels and high strength concrete. Thus, European industry needs an improved scientific infrastructure, which covers a large range of different construction types, to measure their performance for safety and ecological use. Prior to the start of this project, calibration for material testing was done statically and did not only disregard time and frequency influences but also lacked traceability. This project developed methods and transfer standards for static, continuous, and dynamic force calibration traceable to the SI in the range of 1 N to 1 MN. In accordance with the requirements of industry 4.0, force measuring devices were also developed and described by extended theoretical models resulting in digital replicas. This software can be potentially implemented in calibration procedures and extended for use in manufacturing machines. Further to this, the outputs from the project were made available to force metrology services, such as accredited calibration laboratories, for use with their force transducers and testing machines in both quality control and science