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Recent Submissions

Access status: Open Access ,
Current progress in the development of an ECR plasma source for atmosphere-breathing electric propulsion system
(Springer Nature, 2026-01-27) Šťastný, Marek; Mrózek, Kryštof; Juřík, Karel; Drexler, Petr; Sedlář, Jan; Havlíček, Lukáš; Novotný, Michal; Obrusník, Adam
Abstract This contribution reports on the experimental demonstration of plasma ignition in an electron-cyclotron-resonance atmosphere-breathing electric propulsion source at pressures representative of very low Earth orbit. Using a MHz-range birdcage resonator in combination with a tailored magnetic field, we achieved sustained plasma discharge at pressures consistent with conditions expected after intake compression at altitudes near 200 km. The scalability of the birdcage resonator with increasing forward power is explored, revealing the potential for future improvement regarding power scaling of the thruster. These findings identify both the feasibility of electrodeless ignition at VLEO pressures, and the engineering limits imposed by resonator heating. We further discuss quantitative links between measured ion currents, estimated thrust, and extraction efficiency. Our results establish critical design insights for scaling ABEP technology toward flight-ready operation.
Access status: Open Access ,
Lunar regolith simulant-based triboelectric nanogenerators: Toward sustainable energy harvesting from resources on the moon
(Elsevier, 2026-02-01) Yohannan, Alex; Vaghasiya, Jayraj V.; Sonigara, Kevalkumar Kishorbhai; Pumera, Martin
The exploration of extraterrestrial materials for energy harvesting, generation and storage is important for futuristic material evolution and use. Thus, study and use of extraterrestrial materials simulants becomes straightforward way to identify potential of those materials. Such as Lunar Regolith Simulants are tested as reference material to explore suitability for construction, solar cell components and beyond. However, aiming futuristic space exploration, on-site energy generator development from Lunar regolith materials is unexplored and necessary to unveil it. In this work, we introduce a lightweight, flexible triboelectric nanogenerator (TENG) that uses lunar regolith simulant particles (LRPs) embedded in polydimethoxysilane (PDMS) to harvest mechanical energy as first proof-of-concept. Under cyclic contact-separation, the optimized device containing 30 wt % of
Access status: Open Access ,
Limits of analytical models of sandwich structures for optimization
(Elsevier, 2026-01-27) Hostinský, Vladimír; Sodja, Jurij; Jebáček, Ivo; Navrátil, Jan
Current advances in the structural optimization of aircraft structures have led to the introduction of sandwich panels into the optimization process. This study attempts to extend the possibilities of sandwich optimization by proposing an analytical model which predicts the homogenized properties of a sandwich panel with a honeycomb core and CFRP skins. The model is based on a combination of Classical laminate theory and a 1-D beam model of the honeycomb core. The finite-element equivalent of tensile and shear tests is used to validate the proposed model on a broad range of core geometries with different combinations of core thickness, wall angle, cell elongation, and cell wall thickness. The results of 425 different geometries showed the overall precision of the proposed model, highlighted effects in the behavior of the core that drive the sandwich properties further from the predicted values, and suggested which parts of the model are suitable for optimization and where are their limits of applicability.
Access status: Open Access ,
Dataset for the assessment of NOx emissions from the combustion of various nitrogen-rich agricultural residues
(2026-02-01) Sobotková, Julie; Zlevorová, Tereza; Lachman, Jakub; Kintl, Antonín; Baláš, Marek; Lisý, Martin; Elbl, Jakub
The presented set of data contains experimental results from the combustion of various solid biofuels in a small-scale boiler. The biofuels were prepared from agricultural plant residues that included: 4 samples of Melilotus albus, 3 samples of Papaver somniferum, 1 sample of Medicago lupulina, Medicago sativa and Sinapis alba. The residues were processed into 8 mm pellets. Standardized spruce pellets were used as a reference material. The dataset includes basic fuel properties (moisture, ash and volatile matter content and LHV) and elemental composition (C, H, N, S, O). Compared to spruce pellets, the agricultural residues contain considerable amounts of nitrogen, and their combustion thus presents a potential environmental hazard. The combustion tests were carried out on an automatic pellet boiler with a bottom-feed retort burner. The emissions of NOxwere closely monitored and evaluated. The dataset serves primarily for the assessment of NOxemissions from burning nitrogen-rich biofuels; however, other important parameters are included as well: CO, TOC emissions, O2 content, flue gas temperature and boiler power output. (c) 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)
Access status: Open Access ,
On Combining Animal Re-Identification Models to Address Small Datasets
(Springer Nature, 2026-01-30) Algasov, Aleksandr; Nepovinnykh, Ekaterina; Zolotarev, Fedor; Eerola, Tuomas; Kälviäinen, Heikki Antero; Stewart, Charles V.; Otarashvili, Lasha; Holmberg, Jason A.
Recent advancements in the automatic re-identification of animal individuals from images have opened up new possibilities for studying wildlife through camera traps and citizen science projects. Existing methods leverage distinct and permanent visual body markings, such as fur patterns or scars, and typically employ one of two approaches: local features or end-to-end learning. The end-to-end learning-based methods outperform local feature-based methods given a sufficient amount of good-quality training data, but the challenge of gathering such datasets for wildlife animals means that local feature-based methods remain a more practical approach for many species. In this study, we aim to achieve two goals: (1) to obtain a better understanding of the impact of training-set size on animal re-identification, and (2) to explore ways to combine various methods to leverage the advantages of their approaches for re-identification. In the work, we conduct comprehensive experiments across six different methods and six animal species with various training set sizes. Furthermore, we propose a simple yet effective combination strategy and show that a properly selected method combinations outperform the individual methods with both small and large training sets up to 30%. Additionally, the proposed combination strategy offers a generalizable framework to improve accuracy across species and address the challenges posed by small datasets, which are common in ecological research. This work lays the foundation for more robust and accessible tools to support wildlife conservation, population monitoring, and behavioral studies.