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Hierarchical Self-Assembly of SnO Nanoparticles into Porous Microspheres: Exceptionally Selective Ammonia Sensing at Ambient.
ACS Appl Mater Interfaces
January 2025
Nanomaterials Laboratory, Department of Polymers and Functional Materials, CSIR-Indian Institute of Chemical Technology, Uppal Road, Tarnaka, Hyderabad 500 007, India.
Herein, porous SnO microspheres in a three-dimensional (3D) hierarchical architecture were successfully synthesized via a facile hydrothermal route utilizing d-(+)-glucose and cetyltrimethylammonium bromide (CTAB), which act as reducing and structure-directing agents, respectively. Controlled adjustment of the CTAB to glucose mole ratio, reaction temperature, reaction time, and the calcination parameters all provided important clues toward optimizing the final morphologies of SnO with exceptional structural stability and reasonable monodispersity. Electron microscopy analysis revealed that microspheres formed were hierarchical self-assemblies of numerous primary SnO nanoparticles of ∼3-8 nm that coalesce together to form nearly monodispersed and ordered spherical structures of sizes in the range of 230-250 nm and are appreciably porous.
View Article and Find Full Text PDFHydrophobic dual-polymer-reinforced graphene composite aerogel for efficient water-oil separation.
RSC Adv
January 2025
Hainan Provincial Key Laboratory of Natural Rubber Processing, Agricultural Products Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences Zhanjiang 524001 P. R. China
Addressing the environmental challenges posed by oil spills and industrial wastewater is critical for sustainable development. Graphene aerogels demonstrate significant potential as highly efficient adsorbents due to their high specific surface area, excellent structural tunability and outstanding chemical stability. Among available fabrication methods, the hydrothermal self-assembly technique stands out for its low cost, high tunability and good scalability.
View Article and Find Full Text PDFHierarchically aligned heterogeneous core-sheath hydrogels.
Nat Commun
January 2025
Institute of Innovative Materials, Department of Chemistry, College of Science, Southern University of Science and Technology, Shenzhen, China.
Natural materials with highly oriented heterogeneous structures are often lightweight but strong, stiff but tough and durable. Such an integration of diverse incompatible mechanical properties is highly desired for man-made materials, especially weak hydrogels which are lack of high-precision structural design. Herein, we demonstrate the fabrication of hierarchically aligned heterogeneous hydrogels consisting of a compactly crosslinked sheath and an aligned porous core with alignments of nanofibrils at multi-scales by a sequential self-assembly assisted salting out method.
View Article and Find Full Text PDFStress-induced self-assembly of hierarchically twisted stripe arrays.
Sci Bull (Beijing)
December 2024
Department of Chemistry, Laboratory of Advance Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, State Key Laboratory of Molecular Engineering of Polymers, and iChEM, Fudan University, Shanghai 200433, China. Electronic address:
Hierarchical organization is prevalent in nature, yet the artificial construction of hierarchical materials featuring asymmetric structures remains a big challenge. Herein, we report a stress-induced self-assembly strategy for the synthesis of hierarchically twisted stripe arrays (HTSAs) with mesoporous structures. A soft and thin mesostructured film assembled by micelles and TiO oligomers is the prerequisite.
View Article and Find Full Text PDFHierarchically Engineered Self-Adaptive Nanoplatform Guided Intuitive and Precision Interventions for Deep-Seated Glioblastoma.
ACS Nano
January 2025
Shanghai Frontiers Science Center of Drug Target Identification and Delivery, School of Pharmaceutical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China.
Glioblastoma multiforme (GBM), particularly the deep-seated tumor where surgical removal is not feasible, poses great challenges for clinical treatments due to complicated biological barriers and the risk of damaging healthy brain tissue. Here, we hierarchically engineer a self-adaptive nanoplatform (SAN) that overcomes delivery barriers by dynamically adjusting its structure, surface charge, particle size, and targeting moieties to precisely distinguish between tumor and parenchyma cells. We further devise a AN-uided ntuitive and recision ntervention (SGIPi) strategy which obviates the need for sophisticated facilities, skilled operations, and real-time magnetic resonance imaging (MRI) guidance required by current MRI-guided laser or ultrasound interventions.
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