By employing graphene quantum dots (GQDs), we have achieved a high efficiency of 16.55% in n-type Si heterojunction solar cells. The efficiency enhancement is based on the photon downconversion phenomenon of GQDs to make more photons absorbed in the depletion region for effective carrier separation, leading to the enhanced photovoltaic effect. The short circuit current and the fill factor are increased from 35.31 to 37.47 mA/cm(2) and 70.29% to 72.51%, respectively. The work demonstrated here holds the promise for incorporating graphene-based materials in commercially available solar devices for developing ultrahigh efficiency photovoltaic cells in the future.
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http://dx.doi.org/10.1021/acs.nanolett.5b03814 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
Grupo de Investigación Materiales Con Impacto (Mat&Mpac), Facultad de Ciencias Básicas, Universidad de Medellín, Carrera 87 No. 30-65, 050026, Medellín, Colombia.
This study shows the efficiency of WH-C450, an adsorbent obtained from water hyacinth (WH) biomass, in the removal of sulfamethoxazole (SMX) from aqueous solutions. The process involves calcination of WH at 450 °C to produce an optimal adsorbent material capable of removing up to 73% of SMX and maximum SMX adsorption capacity of 132.23 mg/g.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Leiden University Medical Center (LUMC), Leiden, the Netherlands.
Rising computed tomography (CT) workloads require more efficient image interpretation methods. Digitally reconstructed radiographs (DRRs), generated from CT data, may enhance workflow efficiency by enabling faster radiological assessments. Various techniques exist for generating DRRs.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St., Philadelphia, PA, 19104, USA.
Integration of artificial intelligence (AI) into radiology practice can create opportunities to improve diagnostic accuracy, workflow efficiency, and patient outcomes. Integration demands the ability to seamlessly incorporate AI-derived measurements into radiology reports. Common data elements (CDEs) define standardized, interoperable units of information.
View Article and Find Full Text PDFSports Med Open
January 2025
Department of Physical Education and Sport Sciences, National Taiwan Normal University, 162, Section 1, Heping E. Road, Taipei, 106, Taiwan.
Background: Concurrent exercise (CE), an emerging exercise modality characterized by sequential bouts of aerobic (AE) and resistance exercise (RE), has demonstrated acute benefits on executive functions (EFs) and neuroelectric P3 amplitude. However, the effect of acute CE on inhibitory control, a sub-component of EFs, and P3 amplitude remains inconclusive. Moreover, exploring the mechanisms underlying the effects of acute exercise on EFs contributes to scientific comprehension, with lactate recognized as a crucial candidate positively correlated with EFs.
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