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Now showing 1 - 8 of 8
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    A novel approach to fabricate load-bearing Ti6Al4V-Barium titanate piezoelectric bone scaffolds by coupling electron beam melting and field-assisted sintering
    (Amsterdam [u.a.] : Elsevier Science, 2022) Riaz, Abdullah; Polley, Christian; Lund, Henrik; Springer, Armin; Seitz, Hermann
    A critical-size bone defect in load-bearing areas is a challenging clinical problem in orthopaedic surgery. Titanium alloy (Ti6Al4V) scaffolds have advantages because of their biomechanical stability but lack electrical activity, which hinders their further use. This work is focused on the fabrication of Ti6Al4V-Barium Titanate (BaTiO3) bulk composite scaffolds to combine the biomechanical stability of Ti6Al4V with electrical activity through BaTiO3. For the first time, a hollow cylindrical Ti6Al4V is additively manufactured by electron beam melting and combined with piezoelectric BaTiO3 powder for joint processing in field-assisted sintering. Scanning electron microscope images on the interface of the Ti6Al4V-BaTiO3 composite scaffold showed that after sintering, the Ti6Al4V lattice structure bounded with BaTiO3 matrix without its major deformation. The Ti6Al4V-BaTiO3 scaffold had average piezoelectric constants of (0.63 ± 0.12) pC/N directly after sintering due to partial dipole alignment of the BaTiO3 tetragonal phase, which increased to (4.92 ± 0.75) pC/N after a successful corona poling. Moreover, the nanoindentation values of Ti6Al4V exhibited an average hardness and Young's modulus of (5.9 ± 0.9) GPa and (130 ± 14) GPa, and BaTiO3 showed (4.0 ± 0.6) GPa and (106 ± 10) GPa, respectively. It reveals that the Ti6Al4V is the harder and stiffer part in the Ti6Al4V-BaTiO3 composite scaffold. Such a scaffold has the potential to treat critical-size bone defects in load-bearing areas and guide tissue regeneration by physical stimulation.
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    A promising approach to low electrical percolation threshold in PMMA nanocomposites by using MWCNT-PEO predispersions
    (Oxford : Elsevier Science, 2016) Mir, Seyed Mohammad; Jafari, Seyed Hassan; Khonakdar, Hossein Ali; Krause, Beate; Pötschke, Petra; Taheri Qazvini, Nader
    Electrical conductive poly(methyl methacrylate) (PMMA) nanocomposites with low percolation threshold are very challenging to be prepared. Here, we show that the miscibility between poly(ethylene oxide) (PEO) as matrix for predispersions of multi-walled carbon nanotubes (MWCNTs) and PMMA represents an efficient approach to achieve very low electrical percolation threshold. PMMA/PEO-MWCNTs nanocomposites were prepared by a two-step solution casting method involving pre-mixing of MWCNTs with PEO and then mixing of PEO-MWCNTs with PMMA, resulting in a PMMA/PEO ratio of 80/20 wt%. The electrical percolation threshold (EPT) value was determined to be ~ 0.07 wt% which is significantly lower than most of the reported EPT values in the literature for PMMA/CNT composites. The very low electrical percolation threshold was attributed to the effectual role of PEO in self-assembly of secondary structures of nanotubes into an electrically conductive network. This was further confirmed by transmission electron microscopy and by comparing the obtained EPT value with the prediction of the excluded volume model in which statistical percolation threshold is defined based on uniform distribution of high-aspect ratio sticks in a matrix. Moreover, based on UV–Vis measurements and linear viscoelastic rheological measurements, optical and rheological percolation thresholds were obtained at nearly 0.01 wt% and 0.5 wt%, respectively.
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    Machine learning for additive manufacturing: Predicting materials characteristics and their uncertainty
    (Amsterdam [u.a.] : Elsevier Science, 2023) Chernyavsky, Dmitry; Kononenko, Denys Y.; Han, Jun Hee; Kim, Hwi Jun; van den Brink, Jeroen; Kosiba, Konrad
    Additive manufacturing (AM) is known for versatile fabrication of complex parts, while also allowing the synthesis of materials with desired microstructures and resulting properties. These benefits come at a cost: process control to manufacture parts within given specifications is very challenging due to the relevance of a large number of processing parameters. Efficient predictive machine learning (ML) models trained on small datasets, can minimize this cost. They also allow to assess the quality of the dataset inclusive of uncertainty. This is important in order for additively manufactured parts to meet property specifications not only on average, but also within a given variance or uncertainty. Here, we demonstrate this strategy by developing a heteroscedastic Gaussian process (HGP) model, from a dataset based on laser powder bed fusion of a glass-forming alloy at varying processing parameters. Using amorphicity as the microstructural descriptor, we train the model on our Zr52.5Cu17.9Ni14.6Al10Ti5 (at.%) alloy dataset. The HGP model not only accurately predicts the mean value of amorphicity, but also provides the respective uncertainty. The quantification of the aleatoric and epistemic uncertainty contributions allows to assess intrinsic inaccuracies of the dataset, as well as identify underlying physical phenomena. This HGP model approach enables to systematically improve ML-driven AM processes.
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    Laser powder bed fusion of a superelastic Cu-Al-Mn shape memory alloy
    (Amsterdam [u.a.] : Elsevier Science, 2021) Babacan, N.; Pauly, S.; Gustmann, T.
    Dense and crack-free specimens of the shape memory alloy Cu71.6Al17Mn11.4 (at.%) were produced via laser powder bed fusion across a wide range of process parameters. The microstructure, viz. grain size, can be directly tailored within the process and with it the transformation temperatures (TTs) shifted to higher values by raising the energy input. The microstructure, and the superelastic behavior of additively manufactured samples were assessed by a detailed comparison with induction melted material. The precipitation of the α phase, which inhibit the martensitic transformation, were not observed in the additively manufactured samples owing to the high intrinsic cooling rates during the fabrication process. Fine columnar grains with a strong [001]-texture along the building direction lead to an enhanced yield strength compared to the coarse-grained cast samples. A maximum recoverable strain of 2.86% was observed after 5% compressive loading. The first results of our approach imply that laser powder bed fusion is a promising technique to directly produce individually designed Cu-Al-Mn shape memory parts with a pronounced superelasticity at room temperature.
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    Controlled synthesis of mussel-inspired Ag nanoparticle coatings with demonstrated in vitro and in vivo antibacterial properties
    (Amsterdam [u.a.] : Elsevier Science, 2021) Wang, Xiaowei; Xu, Kehui; Cui, Wendi; Yang, Xi; Maitz, Manfred F.; Li, Wei; Li, Xiangyang; Chen, Jialong
    The in-situ formation of silver nanoparticles (AgNPs) via dopamine-reduction of Ag+ has been widely utilized for titanium implants to introduce antibacterial properties. In previous studies, the preparation of AgNPs has focused on controlling the feeding concentrations, while the pH of the reaction solution was ignored. Herein, we systematically determined the influence of various pH (4, 7, 10) and Ag+ concentrations (0.01, 0.1 mg/mL) on the AgNPs formation, followed by the evaluation of the antibacterial properties in vitro and in vivo. The results revealed that an alkaline environment was favourable for AgNP formation and resulted in more particles. Although the AgNPs bearing Ti had lower biocompatibilities, it was significantly improved after 7 days of mineralization in simulated body fluid. The outstanding antibacterial property of the AgNPs was well maintained after one day and seven days of implantation. Moreover, 3D micro-CT modelling showed that the pH 10/0.1 group exhibited remarkable osteogenesis, which may be due to their strong antibacterial properties and ability to promote mineralization. Therefore, we have demonstrated that the solution pH was as important as the feeding Ag+ concentration in determining AgNP formation, and it has paved the way for developing various AgNP-loaded surfaces that could meet different antibacterial needs.
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    Phase and grain size engineering in Ge-Sb-Te-O by alloying with La-Sr-Mn-O towards improved material properties
    (Oxford : Elsevier Science, 2020) Kraft, Nikolas; Wang, Guoxiang; Bryja, Hagen; Prager, Andrea; Griebel, Jan; Lotnyk, Andriy
    Ge-Sb-Te alloys are promising materials for non-volatile memory applications. Alloying of the materials with various elements is considered as prospective approach to enhance material properties. This work reports on the preparation and characterization of pure Ge-Sb-Te-O (GSTO) and alloyed with La-Sr-Mn-O (LSMO) thin films. Thermal heating of amorphous thin films to different temperatures show distinct crystallization behavior. A general trend is the decrease in the size of GSTO crystallites and the suppression in the formation of stable trigonal GSTO phase with increasing content of LSMO. Microstructural studies by transmission electron microscopy show the formation of metastable GSTO nanocrystallites dispersed in the amorphous matrix. Analysis of local chemical bonding by X-ray spectroscopy reveal the presence of different oxides in the GSTO-LSMO composites. Moreover, the composites with a high LSMO content exhibit higher crystallization temperature and significant larger sheet resistance in amorphous and crystalline phase, while a memory device made of GSTO-LSMO alloy reveals bipolar switching and synaptic behavior. In addition, the amount of LSMO in GSTO-LSMO thin films influences their optical properties and band gap. Overall, the results of this work reveal the highly promising potential of GSTO-LSMO nanocomposites for data storage and reconfigurable photonic applications as well as neuro-inspired computing.
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    Trade-off for survival: Microbiome response to chemical exposure combines activation of intrinsic resistances and adapted metabolic activity
    (New York, NY [u.a.] : Elsevier, 2022) Adi Wicaksono, Wisnu; Braun, Maria; Bernhardt, Jörg; Riedel, Katharina; Cernava, Tomislav; Berg, Gabriele
    The environmental microbiota is increasingly exposed to chemical pollution. While the emergence of multi-resistant pathogens is recognized as a global challenge, our understanding of antimicrobial resistance (AMR) development from native microbiomes and the risks associated with chemical exposure is limited. By implementing a lichen as a bioindicator organism and model for a native microbiome, we systematically examined responses towards antimicrobials (colistin, tetracycline, glyphosate, and alkylpyrazine). Despite an unexpectedly high resilience, we identified potential evolutionary consequences of chemical exposure in terms of composition and functioning of native bacterial communities. Major shifts in bacterial composition were observed due to replacement of naturally abundant taxa; e.g. Chthoniobacterales by Pseudomonadales. A general response, which comprised activation of intrinsic resistance and parallel reduction of metabolic activity at RNA and protein levels was deciphered by a multi-omics approach. Targeted analyses of key taxa based on metagenome-assembled genomes reflected these responses but also revealed diversified strategies of their players. Chemical-specific responses were also observed, e.g., glyphosate enriched bacterial r-strategists and activated distinct ARGs. Our work demonstrates that the high resilience of the native microbiota toward antimicrobial exposure is not only explained by the presence of antibiotic resistance genes but also adapted metabolic activity as a trade-off for survival. Moreover, our results highlight the importance of native microbiomes as important but so far neglected AMR reservoirs. We expect that this phenomenon is representative for a wide range of environmental microbiota exposed to chemicals that potentially contribute to the emergence of antibiotic-resistant bacteria from natural environments.
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    Phenomenology of ultrafine particle concentrations and size distribution across urban Europe
    (Amsterdam [u.a.] : Elsevier Science, 2023) Trechera, Pedro; Garcia-Marlès, Meritxell; Liu, Xiansheng; Reche, Cristina; Pérez, Noemí; Savadkoohi, Marjan; Beddows, David; Salma, Imre; Vörösmarty, Máté; Casans, Andrea; Casquero-Vera, Juan Andrés; Hueglin, Christoph; Marchand, Nicolas; Chazeau, Benjamin; Gille, Grégory; Kalkavouras, Panayiotis; Mihalopoulos, Nikos; Ondracek, Jakub; Zikova, Nadia; Niemi, Jarkko V.; Manninen, Hanna E.; Green, David C.; Tremper, Anja H.; Norman, Michael; Vratolis, Stergios; Eleftheriadis, Konstantinos; Gómez-Moreno, Francisco J.; Alonso-Blanco, Elisabeth; Gerwig, Holger; Wiedensohler, Alfred; Weinhold, Kay; Merkel, Maik; Bastian, Susanne; Petit, Jean-Eudes; Favez, Olivier; Crumeyrolle, Suzanne; Ferlay, Nicolas; Martins Dos Santos, Sebastiao; Putaud, Jean-Philippe; Timonen, Hilkka; Lampilahti, Janne; Asbach, Christof; Wolf, Carmen; Kaminski, Heinz; Altug, Hicran; Hoffmann, Barbara; Rich, David Q.; Pandolfi, Marco; Harrison, Roy M.; Hopke, Philip K.; Petäjä, Tuukka; Alastuey, Andrés; Querol, Xavier
    The 2017–2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.