Three-dimensional (3D) printing allows for the construction of complex structures. However, 3D-printing vertical structures with a high aspect ratio remains a pending challenge, especially when a high lateral resolution is required. Here, to address this challenge, we propose and demonstrate micro-3D sculptured metastructures with deep trenches of 1:4 (width:height) aspect ratio for sub-10 µm resolution. Our construction relies on two-photon polymerization for a 3D-pattern with its trenches, followed by electroplating of a thick metal film and its dry etching to remove the seed layer. To test the proposed fabrication process, we built up three-dimensional RF metastructures showcasing the depth effect as the third dimension. Using the numerical solutions, we custom-tailored these metastructure resonators to fall within a specific resonance frequency range of 4-6 GHz while undertaking comparative analyses regarding overall footprint, quality factor, and resonance frequency shift as a function of their cross-sectional aspect ratio. The proposed process flow is shown to miniaturize metal footprint and tune the resonance frequency of these thick 3D-metastructures while increasing their quality factor. These experimental findings indicate that this method of producing trenches via 3D-printing provides rich opportunities to implement high-aspect-ratio, complex structures.
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http://dx.doi.org/10.1038/s41378-025-00888-5 | DOI Listing |
Infez Med
March 2025
Microbiology Laboratory, Azienda Ospedaliero-Universitaria SS. Antonio e Biagio e Cesare Arrigo, Alessandria, Italy.
Aims: The aim of this study was to assess the possible use of time to positivity (TTP) of blood cultures (BCs) collected at the Emergency Department (ED) to estimate the probability of pyogenic streptococci versus other Gram positive cocci in pairs and chains, such as , other viridans group streptococci or enterococci.
Methods: All patients 18 years of age or older evaluated at the ED from whom BCs were collected and were positive for Gram positive cocci in pairs and chains at the microscopic examination, were included in the study. The BCs included were collected by venipuncture, were mono-microbial and were the first bottles that flagged positive in each set.
Water Environ Res
March 2025
School of Civil and Environmental Engineering, Cornell University, Ithaca, New York, USA.
This study reported a successful mainstream B-stage nitritation reactor with sludge granulation that incorporated a side-stream anaerobic reactor to treat municipal wastewater A-stage effluent. With influent COD/N and COD/P ratios of 2.60 and 27.
View Article and Find Full Text PDFJ Phys Chem Lett
March 2025
School of Nuclear Science & Technology, Southwest University of Science and Technology, Mianyang 621010, P. R. China.
Metal-organic frameworks (MOFs) have emerged as promising templates and precursors that can be converted to a series of functional materials. Probing the dynamic conversion processes within individual MOF crystal particles in real-time is key to understanding the structure-activity relationship, but this remains challenging, particularly for anisotropic MOF crystals. Here, using dark-field optical microscopy, we visually image and quantify the dynamic oxidation conversion of a single bismuth-based metal-organic framework (Bi-MOF) into bismuth oxides by NaClO.
View Article and Find Full Text PDFNutr Metab (Lond)
March 2025
Unit of Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Acute intermittent porphyria (AIP) is a rare metabolic disorder characterized by acute attacks often triggered by porphyrinogenic drugs and a low-glucose diet. According to recent findings, chronic symptoms persist in AIP patients. To avoid the symptoms, patients often adopt preventive strategies such as increasing glucose intake, suggesting that nutrition is a crucial aspect of disease management.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
March 2025
Furtwangen University of Applied Sciences, Furtwangen, Germany.
Background: In the future, more medical devices will be based on machine learning (ML) methods. In general, the consideration of risks is a crucial aspect for evaluating medical devices. Accordingly, risks and their associated costs should be taken into account when assessing the performance of ML-based medical devices.
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