Polymer Nanocomposite Containing Palladium Nanoparticles: Synthesis, Characterization, and Properties

Promising biomedical systems based on copper nanoparticles: Synthesis, characterization, and applications

Copper and copper oxide nanoparticles (CuNPs) have unique physicochemical properties that make them highly promising for biomedical applications. This review discusses the application of CuNPs in biomedicine, including diagnosis, therapy, and theranostics. Recent synthesis methods, with an emphasis on green approaches, are described, and the latest techniques for nanoparticle characterization are critically analyzed. CuNPs, including Cu2O, CuO, and Cu, have significant potential as anti-cancer agents, drug delivery systems, and photodynamic therapy enhancers, among other applications. While challenges such as ensuring biocompatibility and stability must be addressed, the state-of-the-art research reviewed here provides strong evidence for the efficacy and versatility of CuNPs. These multifunctional properties have been extensively researched and documented, showcasing the immense potential of CuNPs in biomedicine. Overall, the evidence suggests that CuNPs are a promising avenue for future research and development in biomedicine. We strongly support further progress in the development of synthesis and application strategies to enhance the effectiveness and safety of CuNPs for clinical purposes.

Nanocomposites Based on Polyethylene and Nickel Ferrite: Preparation, Characterization, and Properties

Composite materials based on NiFe2O4 nanoparticles and polyethylene matrix have been synthesized by thermal decomposition to expand the application area of high-pressure polyethylene by filling it with nanoscale particles. The synthesized compositions were obtained in the form of a dark gray powder and compressed for further study According to TEM, the average particle size in composites was 2, 3, and 4 nm in samples with a filling of 10%, 20% and 30%. The concentration dependences of the specific electrical resistivity ρV, dielectric permittivity ε, saturation magnetization MS and the parameters of reflection and attenuation of microwave power of the obtained composites were investigated. The threshold for percolation in such materials is found to be within a concentration range of 20…30%. The electronic and atomic structure of composites was studied by methods of Mössbauer spectroscopy, X-ray diffraction and X-ray absorption spectroscopy. The closest atomic environment of nickel and iron in nanoparticles is close to that of crystalline NiFe2O4. The dependence of the nanoparticles size as well as the dependence of the number of tetrahedral or octahedral iron positions in nickel ferrite nanoparticles to their content in polyethylene matrix is established. It is shown that composite materials based on NiFe2O4 nanoparticles and polyethylene matrix can be used as components of electromagnetic compatibility systems.

Automated Recognition of Nanoparticles in Electron Microscopy Images of Nanoscale Palladium Catalysts

Automated computational analysis of nanoparticles is the key approach urgently required to achieve further progress in catalysis, the development of new nanoscale materials, and applications. Analysis of nanoscale objects on the surface relies heavily on scanning electron microscopy (SEM) as the experimental analytic method, allowing direct observation of nanoscale structures and morphology. One of the important examples of such objects is palladium on carbon catalysts, allowing access to various chemical reactions in laboratories and industry. SEM images of Pd/C catalysts show a large number of nanoparticles that are usually analyzed manually. Manual analysis of a statistically significant number of nanoparticles is a tedious and highly time-consuming task that is impossible to perform in a reasonable amount of time for practically needed large amounts of samples. This work provides a comprehensive comparison of various computer vision methods for the detection of metal nanoparticles. In addition, multiple new types of data representations were developed, and their applicability in practice was assessed.