98%
921
2 minutes
20
Atomically precise metal nanoclusters (NCs) and metal-organic frameworks (MOFs) possess distinct properties that can present challenges in certain applications. However, integrating these materials to create new composite functional materials has gained significant interest due to their unique characteristics through a range of applications, particularly in catalysis. Considering MOFs as hosts and NCs as guests, several synergistic effects have been observed in composites, particularly in environmental catalytic reactions. However, the precise role of encapsulated NCs within the MOF pore structure is still in its infancy. Besides, stabilizing NCs, whether through intact ligands or without ligands the MOF host, presents challenges that are currently being investigated. This feature article reviews recent advancements in the synthesis of NC@MOF composites, focusing on cutting-edge strategies for selecting MOFs and the roles of NC ligands, as well as characterization and catalytic applications.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1039/d4cc05255b | DOI Listing |
Adv Mater
September 2025
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China.
Van der Waals (vdW) layered materials have gained significant attention owing to their distinctive structure and unique properties. The weak interlayer bonding in vdW layered materials enables guest atom intercalation, allowing precise tuning of their physical and chemical properties. In this work, a ternary compound, NiInSe (x = 0-0.
View Article and Find Full Text PDFPhys Chem Chem Phys
September 2025
State Key Laboratory of Materials for Integrated Circuits, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Selenium, as an important semiconductor material, exhibits significant potential for understanding lattice dynamics and thermoelectric applications through its thermal transport properties. Conventional empirical potentials are often unable to accurately describe the phonon transport properties of selenium crystals, which limits in-depth understanding of their thermal conduction mechanisms. To address this issue, this study developed a high-precision machine learning potential (MLP), with training datasets generated molecular dynamics simulations.
View Article and Find Full Text PDFNanoscale
September 2025
Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
A crack-free and residue-free transfer technique for large-area, atomically-thin 2D transition metal dichalcogenides (TMDCs) such as MoS and WS is critical for their integration into next-generation electronic devices, either as channel materials replacing silicon or as back-end-of-line (BEOL) components in 3D-integrated nano-systems on CMOS platforms. However, cracks are frequently observed during the debonding of TMDCs from their growth substrates, and polymer or metal residues are often left behind after the removal of adhesive support layers wet etching. These issues stem from excessive angular strain accumulated during debonding and the incomplete removal of support layers due to their low solubility.
View Article and Find Full Text PDFNanoscale Horiz
September 2025
School of Biomedical Engineering, University of Sydney, Darlington 2008, New South Wales, Australia.
Entropy-driven drying-mediated self-assembly of plasmonic nanocrystals (termed "plasmonic atoms") has emerged as a general strategy for fabricating plasmene nanosheets from a wide range of monodisperse nanocrystals. However, extending this approach to binary systems remains challenging due to the complex nanoscale interactions between dissimilar nanocrystal shapes. Here, we introduce a combined enthalpy- and entropy-driven strategy to achieve an orderly mixed two-dimensional (2D) binary nanoassemblies from complementary reacting polymer-ligated nanocrystals.
View Article and Find Full Text PDFMed Phys
September 2025
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
Background: Dual-energy computed tomography (DECT) enhances material differentiation by leveraging energy-dependent attenuation properties particularly for carbon ion therapy. Accurate estimation of tissue elemental composition via DECT can improve quantification of physical and biological doses.
Objective: This study proposed a novel machine-learning-based DECT (ML-DECT) method to predict the physical density and mass ratios of H, C, N, O, P, and Ca.