Investigating the impact of heteroatom alloying extents on regulating the cluster structures is crucial for the fabrication of cluster-based nanomaterials with customized properties. Herein, two structurally comparable PdAu ( = 1, 2) nanoclusters with a uniform surface environment but completely distinct kernel configurations were controllably synthesized and structurally determined. The single Pd-alloyed Pd1Au12 nanocluster retained an icosahedral metal framework, while the Pd2Au12 nanocluster with two Pd heteroatoms exhibited a unique toroidal configuration. The additional Pd heteroatom not only led to significant changes in the cluster frameworks but also profoundly affected their electrocatalytic CO reduction performance. The Pd1Au12 nanocluster demonstrated enhanced catalytic performance, exhibiting a higher current density, a lower onset potential, and greater CO faradaic efficiency compared to the Pd2Au12 nanocluster. This work offers new insights into the customization of the structures and properties of gold nanoclusters by regulating the doping degree of Pd heteroatoms.
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http://dx.doi.org/10.1039/d4nr05222f | DOI Listing |
Front Oral Health
January 2025
Doctoral School of Health Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary.
Background: In recent years, dental clusters and networks have been established in primary care in many countries to improve access to services for the population and develop cooperation between providers. In Hungary, the first dental clusters were established in 2021, and currently, one-third of dental practices have already joined a cluster. The study aimed to gather and analyze early experiences regarding the motivation of participation in primary care dental clusters and experiences of implementation.
View Article and Find Full Text PDFNatl Sci Rev
February 2025
Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310000, China.
Tumor heterogeneity plays a pivotal role in tumor progression and resistance to clinical treatment. Single-cell RNA sequencing (scRNA-seq) enables us to explore heterogeneity within a cell population and identify rare cell types, thereby improving our design of targeted therapeutic strategies. Here, we use a pan-cancer and pan-tissue single-cell transcriptional landscape to reveal heterogeneous expression patterns within malignant cells, precancerous cells, as well as cancer-associated stromal and endothelial cells.
View Article and Find Full Text PDFSmall
January 2025
College of Physical Science and Technology, Xiamen University, Xiamen, 361005, P. R. China.
Twisted bilayer graphene (TBG) has drawn considerable attention due to its angle-dependent electrical, optical, and mechanical properties, yet preparing and identifying samples at specific angles on a large scale remains challenging and labor-intensive. Here, a data-driven strategy that leverages Raman spectroscopy is proposed in combination with deep learning to rapidly and non-destructively decode and predict the twist angle of TBG across the full angular range. By processing high-dimensional Raman data, the deep learning model extracts hidden information to achieve precise twist angle identification.
View Article and Find Full Text PDFSmall
January 2025
State Key Laboratory of Green Pesticide, International Joint Research Center for Intelligent Biosensing Technology and Health, College of Chemistry, Central China Normal University, Wuhan, 430079, P. R. China.
The severe environmental and human health hazards posed by organophosphorus compounds underscore the pressing need for advancements in their degradation and detection. However, practical implementation is impeded by prolonged degradation durations and limited efficiency. Herein, an effective interfacial modification approach is proposed involving the integration of photoactive Au nanoparticles (NPs) onto metal-organic frameworks, resulting in the synthesis of UiO-66/Au NPs exhibiting enhanced hydrolysis activity under light excitation.
View Article and Find Full Text PDFCytometry A
January 2025
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Cytometry is a single cell, high-dimensional, high-throughput technique that is being applied across a range of disciplines. However, many elements alongside the data acquisition process might give rise to technical variation in the dataset, called batch effects. CytoNorm is a normalization algorithm for batch effect removal in cytometry data that was originally published in 2020 and has been applied on a variety of datasets since then.
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