[Dataset] Structural and functional profiling of starch-polymer nanoscaffolds enhanced with Ectocarpales-derived biogenic copper oxide nanoparticles

This dataset provides a detailed physicochemical and functional evaluation of starch-polymer nanoscaffolds integrated with biogenic copper oxide nanoparticles (CuO NPs) synthesized using Ectocarpales sp., a brown algal extract, as a sustainable reducing agent. The work employs UV-visible spectroscopy (UV-Vis) to confirm CuO NP synthesis and assess optical properties, while Fourier-transform infrared spectroscopy (FT-IR) identifies functional groups and interactions between the starch matrix and nanoparticles. X-ray diffraction (XRD) reveals the crystalline structure and phase purity of CuO NPs, complemented by scanning electron microscopy (SEM) imaging to visualize nanoscaffold morphology, porosity, and nanoparticle distribution. Thermal gravimetric analysis (TGA) evaluates the thermal stability and degradation profiles of the nanocomposite, and dynamic light scattering (DLS) characterizes nanoparticle hydrodynamic size and colloidal stability in suspension. The dataset highlights how Ectocarpales-mediated CuO NPs influence scaffold properties, including enhanced structural integrity, thermal resistance, and controlled particle dispersion. By merging eco-friendly synthesis with advanced material characterization, this resource underscores the potential of algal-derived nanoparticles in reinforcing biodegradable starch scaffolds for biomedical applications, such as tissue engineering or controlled drug delivery. Researchers can leverage this multidisciplinary dataset to correlate synthesis parameters with material performance, optimize nanoparticle loading, and design sustainable nanohybrid systems with tailored structural and functional attributes. The integration of green chemistry principles with robust analytical workflows offers a template for developing eco-conscious biomaterials.