2025-07-05 06:16 |
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2025-07-05 06:16 |
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2025-07-05 06:16 |
Fully bio-based composite and modular metastructures
/ da Silva, Rodrigo José (CERN ; Sao Joao del-Rei Fed. U. ; U. Bristol (main)) ; de Resende, Bárbara Lana (Sao Joao del-Rei Fed. U.) ; Comandini, Gianni (U. Bristol (main)) ; Lavazza, Jacopo (U. Bristol (main)) ; Camanho, Pedro P (Porto U.) ; Scarpa, Fabrizio (U. Bristol (main)) ; Panzera, Túlio Hallak (Sao Joao del-Rei Fed. U. ; Porto U.)
Abstract
The reliance on fossil-derived components in the design of metamaterials and metastructures presents sustainability and environmental challenges, prompting the development of alternative solutions. In response, this study proposes a fully bio-based and modular metastructure composed of rods extracted from the giant bamboo (Dendrocalamus asper) and plant-based polymeric joints derived from soybean (Glycine max) and castor oil (Ricinus communis), aiming to offer a sustainable alternative for load-bearing structural components [...]
2025 - 46 p.
- Published in : Adv. Comp. Hybr. Mat. 8 (2025) 288
Fulltext: PDF; External links: Fulltext; Fulltext
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2025-07-03 11:24 |
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2025-07-02 06:32 |
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2025-07-02 06:32 |
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2025-07-02 06:32 |
Advancements in resistive MPGD: From μ-RWELL technology to high performance Hybrid Layouts
/ Bencivenni, G (Frascati) ; De Lucia, E (Frascati) ; De Oliveira, R (CERN) ; De Robertis, G (INFN, Bari) ; Debernardis, F (INFN, Bari) ; Felici, G (Frascati) ; Gatta, M (Frascati) ; Giovannetti, M (Frascati) ; Licciulli, F (INFN, Bari) ; Morello, G (Frascati) et al.
Future high-energy and nuclear physics experiments require advanced particle gaseous detectors with exceptional tracking and timing performance, capable of operating in harsh environments. The μ-RWELL, a single-stage resistive Micro-Pattern-Gaseous-Detector (MPGD), developed by some of the authors in 2014, achieves gas gains of ∼2×104, ∼100μm spatial resolution, and 5–6ns time resolution. [...]
2025 - 5 p.
- Published in : Nucl. Instrum. Methods Phys. Res., A 1080 (2025) 170623
In : 17th Vienna Conference on Instrumentation (VCI2025), Vienna, Austria, 17 - 21 Feb 2025, pp.170623
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2025-07-02 04:11 |
Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders
/ Mokhtar, Farouk (UC, San Diego) ; Pata, Joosep (NICPB, Tallinn) ; Garcia, Dolores (CERN) ; Wulff, Eric (CERN) ; Zhang, Mengke (UC, San Diego) ; Kagan, Michael (SLAC) ; Duarte, Javier (UC, San Diego)
We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the model on a large full simulation dataset from one detector design, and subsequently fine-tune the model on a sample with a different collider and detector design. [...]
arXiv:2503.00131.-
2025-05-01 - 20 p.
- Published in : Phys. Rev. D
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2025-07-02 04:08 |
Chaos indicators for nonlinear dynamics in circular particle accelerators
/ Montanari, C.E. (Manchester U. ; CERN) ; Appleby, R.B. (Manchester U.) ; Bazzani, A. (Bologna U. ; INFN, Bologna) ; Fornara, A. (Manchester U. ; CERN) ; Giovannozzi, M. (CERN) ; Redaelli, S. (CERN) ; Sterbini, G. (CERN) ; Turchetti, G. (Bologna U.)
The understanding of non-linear effects in circular storage rings and colliders based on superconducting magnets is a key issue for the luminosity the beam lifetime optimisation. A detailed analysis of the multidimensional phase space requires a large computing effort when many variants of the magnetic lattice, representing the realisation of magnetic errors or configurations for performance optimisation, have to be considered. [...]
arXiv:2504.12741.-
2025-06-27 - 23 p.
- Published in : Eur. Phys. J. Plus 140 (2025) 603
Fulltext: 2504.12741 - PDF; document - PDF;
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2025-07-02 04:06 |
DataPix4: A C++ framework for Timepix4 configuration and read-out
/ Cavallini, Viola (U. Ferrara (main) ; INFN, Ferrara) ; Biesuz, Nicolò Vladi (INFN, Ferrara) ; Bolzonella, Riccardo (U. Ferrara (main) ; INFN, Ferrara) ; Calore, Enrico (INFN, Ferrara) ; Fiorini, Massimiliano (U. Ferrara (main) ; INFN, Ferrara) ; Gianoli, Alberto (INFN, Ferrara) ; Llopart Cudie, Xavier (CERN) ; Schifano, Sebastiano Fabio (U. Ferrara (main) ; INFN, Ferrara)
DataPix4 (Data Acquisition for Timepix4 Applications) is a new C++ framework for the management of Timepix4 ASIC, a multi-purpose hybrid pixel detector designed at CERN. Timepix4 consists of a matrix of 448×512 pixels that can be connected to several types of sensors, to obtain a pixelated detector suitable for different applications. [...]
arXiv:2503.01609.-
2025-05-09 - 12 p.
- Published in : Comput. Phys. Commun. 314 (2025) 109658
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