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Propagation-based x-ray imaging (PBI) is a phase-contrast technique that is employed in high-resolution imaging by introducing some distance between sample and detector. PBI causes characteristic intensity fringes that have to be processed with appropriate phase-retrieval algorithms, which has historically been a difficult task for objects composed of several different materials. Spectral x-ray imaging has been introduced to PBI to overcome this issue and to potentially utilize the spectral nature of the data for material-specific imaging. We aim to explore the potential of spectral PBI in three-dimensional computed tomography (CT) imaging in this work. We demonstrate phase-retrieval for experimental high-resolution spectral propagation-based CT data of a simple two-component sample, as well as a multimaterial capacitor test sample. Phase-retrieval was performed using an algorithm based on the Alvarez-Macovski model. Virtual monochromatic (VMI) and effective atomic number images were calculated after phase-retrieval. Phase-retrieval results from the spectral data set show a distinct gray-level for each material with no residual phase-contrast fringes. Several representations of the phase-retrieved data are provided. The VMI is used to display an attenuation-equivalent image at a chosen display energy of 80 keV, to provide good separation of materials with minimal noise. The effective atomic number image shows the material composition of the sample. Spectral photon-counting detector technology has already been shown to be compatible with spectral PBI, and there is a foreseeable need for robust phase-retrieval in high-resolution, spectral x-ray CT in the future. Our results demonstrate the feasibility of phase-retrieval for spectral PBI CT.
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http://dx.doi.org/10.1117/1.JMI.9.3.031506 | DOI Listing |
Nanoscale Adv
August 2025
Microquanta Semiconductor Co. Ltd Hangzhou Zhejiang 311121 China.
Perovskite solar cells have made remarkable progress in laboratory-scale efficiency, positioning them as a promising next-generation photovoltaic technology. However, their long-term operational stability under real-world conditions remains a critical barrier to commercial deployment. This study presents a three-year outdoor field investigation of a micro power station composed of 20 perovskite sub-modules (FACsPbI-based, each measuring 30 cm × 40 cm), deployed in subtropical eastern China and fabricated using scalable, industry-compatible processes.
View Article and Find Full Text PDFNanoscale
August 2025
Department of Materials Science and Engineering, and Centre for Functional Photonics (CFP), City University of Hong Kong, Hong Kong SAR, 999077 P. R. China.
Metal halide perovskite nanoplatelets (NPls) exhibit attractive optical properties as a result of quantum and dielectric confinement effects. Their strong and narrow photoluminescence (PL), tunable over the entire visible spectral range, makes them highly promising for light-emission and lasing applications. In metal halide perovskites, partial cation substitution serves as an additional tool for fine-tuning their structure and optical properties.
View Article and Find Full Text PDFMagn Reson (Gott)
July 2025
Institute for Molecules and Materials, Radboud Universiteit, Heyendaalseweg 135, 6525 AJ Nijmegen, the Netherlands.
Nuclear quadrupole resonance (NQR), a technique related to nuclear magnetic resonance, is extremely sensitive to local crystal composition and structure. Unfortunately, in disordered materials, this sensitivity also leads to very large linewidths, presenting a technical challenge and requiring a serious time investment to get a full spectrum. Here, we describe our newly developed, automated NQR set-up to acquire high-quality wide-line spectra.
View Article and Find Full Text PDFNat Commun
July 2025
Department of Nuclear, Plasma and Radiological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
Identifying materials with optimal optoelectronic properties for targeted applications represents both a critical need and a persistent challenge in optoelectronic device engineering. Machine learning models often depend on extensive datasets, which are typically lacking in specialized research domains such as extreme ultraviolet (EUV) radiation detection. Here, we demonstrate a Cross-Spectral Response Prediction framework that leverages existing visible and ultraviolet (UV) photoresponse data to predict more efficient material's performance under EUV radiation.
View Article and Find Full Text PDFMolecules
June 2025
School of Energy and Environment Science, Yunnan Normal University, Kunming 650500, China.
First-principles calculations were conducted to examine the impact of three sulfonamide-containing molecules (HNOS, CHNOS, and CHNOS) adsorbed on the FAPbI(001) perovskite surface, aiming to establish a significant positive correlation between the molecular structures and their regulatory effects on the perovskite surface. A systematic comparison was conducted to evaluate the adsorption stability of the three molecules on the two distinct surface terminations. The results show that all three molecules exhibit strong adsorption on the FAPbI(001) surface, with CHNOS demonstrating the most favorable binding stability due to its extended frameworks and multiple electron-donating/withdrawing groups.
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