Analysing the impact of Dy dopants on Zn-based hydroxyapatites: modelling and characterization perspectives
Source abstract
Abstract
This study is aimed to investigate the effects of introducing dysprosium (Dy) into Zn-based hydroxyapatite (HAp) at various concentrations (0.45, 0.90, 1.35 and 1.80%). The structural and optical properties of pure and doped HAp were thoroughly examined through theoretical and empirical analyses, including X-ray diffraction, Raman spectroscopy and Fourier transform infrared (FTIR) studies. The results confirmed the successful incorporation of Dy into the HAp lattice without significantly affecting its thermal stability or stoichiometry. The introduction of Dy into Zn-based HAp led to notable alterations in several material parameters. The lattice parameters, crystallinity, lattice stress, strain and anisotropic energy density varied with different Dy concentrations. In comparison with undoped HAp, all Dy-doped Zn-based HAps exhibited reduced crystallite size values, indicating a change in the microstructure. Furthermore, the material density increased from 3.159 to 3.228 g cm-3 with Dy doping. The band gap (BG), an important parameter for optical applications, is consistently decreased from 4.6 to 3.9 eV as the Dy concentration increased. This decrease in BG suggests the potential for improved photocatalytic or optoelectronic properties in Dy-doped Zn-based HAp. Additionally, the linear absorption coefficient (LAC) increased, indicating enhanced light absorption. Overall, this study provides a comprehensive understanding of structural and optical modifications induced by Dy doping in Zn-based HAp. These findings contribute to the potential application of Dy-doped Zn-based HAp in various fields, including biomedicine, photocatalysis and optoelectronics.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Bone Tissue Engineering Materials · Dental materials and restorations · Extraction and Separation Processes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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