Data Imaging and XRD analyses for characterization of magnetic nanoparticles and nanostructures

Ferromagnetic Fe, Co, and Ni core-shell nanoparticles embedded in varies carbon-based matrixes have attracted huge interest as a rapidly growing class of materials for many applications. Different experimental, theoretical techniques and algorithms have been developed to characterize the size, crystal structure, elemental composition, and a variety of chemical and physical properties of synthesized magnetic nanoparticles. We unveil groundbreaking advancements towards an innovative algorithm designed to process SEM, HR-STEM images and seamlessly map these with PXRD elemental analysis. This intricate process of pattern recognition harnesses the power of traditional filtration techniques, from Fourier transforms to mathematical tools and the cutting-edge reconnection algorithm. Our primary objective is to categorize the morphology nanostructures based on size parameters - length for nanotubes or nanosheets and radius of nanoparticles. We describe the main characteristics of the techniques by providing various examples of their use for analysis delves deep into characterization the degree of porosity, layer sizes, and their subsequent influence on magnetic properties and insights into the role of graphitization and amorphism. A diverse range of layered nanostructures, nanoparticles, including metal and metal-free phthalocyanine and porphyrin, to name a few, synthesized by pyrolysis and annealing and tested under the PPMS to ascertain their magnetic attributes to bridge the correlation between observed magnetic properties of core-shell and layered structures of synthesized nanostructures.