Data · dataset · 2025
[Dataset] Eco-friendly nanocomposite scaffolds: physicochemical analysis of starch matrices integrated with Turbinaria ornata-mediated CuO nanoparticles
Listed in Teesside University Research Data Repository
This dataset comprehensively characterizes starch-based nanocomposite scaffolds reinforced with copper oxide nanoparticles (CuO NPs) synthesized using Turbinaria ornata, a brown algae, as a green reducing and stabilizing agent.
Description
The study employs UV-visible spectroscopy (UV-Vis) to verify CuO NP formation via absorbance peaks and monitor reaction kinetics. Fourier-transform infrared spectroscopy (FT-IR) identifies functional groups in the algal extract and elucidates interactions between starch polymers and nanoparticles, such as hydrogen bonding or electrostatic forces.
X-ray diffraction (XRD) confirms the crystalline phase and purity of biosynthesized CuO NPs, while scanning electron microscopy (SEM) reveals the scaffold’s porous architecture, surface topography, and homogeneous nanoparticle dispersion. Thermal gravimetric analysis (TGA) evaluates the nanocomposite’s thermal stability and decomposition behavior, highlighting the reinforcing effect of CuO NPs on starch matrices. Dynamic light scattering (DLS) measures nanoparticle hydrodynamic size, polydispersity, and colloidal stability in suspension, critical for assessing biocompatibility.
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The dataset underscores the synergy between eco-friendly synthesis (using Turbinaria ornata extract) and enhanced scaffold functionality, such as improved mechanical strength, thermal resistance, and controlled degradation. These insights advance sustainable biomaterial design, particularly for tissue engineering, wound healing, or drug delivery, where biodegradable starch-algae nanocomposites offer alternatives to synthetic counterparts.
Researchers can utilize this integrated analytical approach to optimize algal-mediated nanoparticle synthesis, tailor scaffold properties, and validate eco-conscious strategies for developing high-performance nanohybrid systems. The work bridges green chemistry principles with material science, emphasizing scalability and environmental safety in nanotechnology applications.
Links
Where it is published
- DOI doi.org/10.17632/tgxw2g4stx.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science
- Inferred from text
- Microscopy 75%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/tgxw2g4stx.1 | 23 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:microscopy | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |