[Dataset] Physiochemical characterization of fabricated starch-based nanoscaffolds incorporated with Pocockiella variegata extract-mediated green synthesised copper oxide nanoparticles
Description
This dataset presents a comprehensive physicochemical characterization of starch-based nanoscaffolds integrated with copper oxide nanoparticles (CuO NPs) synthesized via a green approach using Pocockiella variegata algal extract. The study focuses on evaluating the structural, morphological, and functional properties of these nanocomposite scaffolds, which combine biodegradable starch polymers with eco-friendly CuO NPs for potential biomedical applications. Key analytical techniques include scanning (SEM) for assessing nanoscaffold porosity and nanoparticle dispersion, X-ray diffraction (XRD) for crystallinity analysis of CuO NPs, and Fourier-transform infrared spectroscopy (FTIR) to identify chemical interactions between starch matrices and nanoparticles. Additional data on thermal stability (via TGA) are provided to assess scaffold durability. By merging natural polymer scaffolds with green-synthesized nanoparticles, this work highlights sustainable strategies for developing advanced biomaterials. The findings are relevant to tissue engineering, wound dressings, or drug delivery systems, emphasizing eco-friendly alternatives to conventional synthetic nanomaterials. Researchers can leverage this dataset to optimize nanoparticle loading, scaffold architecture, and functional performance for targeted biomedical uses.