ArticleIranian journal of basic medical sciences2026
Fabrication and analysis of a PVP-carboxymethyl chitosan/forsterite nanocomposite scaffold with stainless steel base via freeze-drying and neural network techniques.
Article in Iranian journal of basic medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Multi-source information fusion using CNN-LSTM-Attention for bone layer recognition in robotic orthopedic grinding.Medical & biological engineering & computing · 2026Article
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Authors and funding
4 authors.
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Abstract
Objectives: This study aims to design and fabricate innovative polymer-ceramic-metal scaffolds for bone tissue engineering, utilizing 3D printing and freeze-drying techniques to enhance bone repair. Materials and Methods: Stainless steel scaffolds were produced via selective laser melting (SLM) and coated with varying weight percentages (0, 5, 10, 15) of polyvinylpyrrolidone (PVP), carboxymethyl chitosan (CMC), and forsterite using freeze-drying. The scaffolds were characterized through Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) to assess functional groups, phase purity, porosity, and pore size. Biological assessments included bioactivity, ion emission tests (ICP-AES), and wettability evaluations. Artificial neural networks (ANN) were employed to predict mechanical and biological properties. Results: The analysis revealed that scaffolds with 15% forsterite exhibited optimal mechanical and biological performance, enhancing the scaffold's potential for clinical applications in bone repair. Conclusion: This study introduces a novel scaffold design that significantly improves bone tissue regeneration processes. The integration of advanced materials and predictive modeling through ANN paves the way for future research in the field of bone tissue engineering.
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