journal article·2021-10

Piezoelectric calcium/manganese-doped barium titanate nanofibers with improved osteogenic activity

Tianyi Zheng, Han Zhao, Yiqian Huang, Chenyuan Gao, Xuehui Zhang, Qing Cai, Xiaoping Yang

Ceramics International· Volume 47· Issue 20
Publisher page

Abstract

Abstract The piezoelectric nature of natural bone tissue makes the use of piezoelectric biomaterials in promoting bone regeneration to be a feasible and attractive strategy. Barium titanate (BaTiO3) is well-known for its high piezoelectricity and widely studied as bone repairing bioceramic, but its lacking of bioactive ions may compromise its contribution to osteogenesis. Calcium is the richest metallic element in bone mineral, and manganese is an important doping element for hydroxyapatite, therein, Ca2+ and Mn4+ were individually or co-doped into BaTiO3 nanofibers via sol-gel/electrospinning/calcination technique in this study. Compared to pure BaTiO3 nanofibers, though the piezoelectric coefficient (d33) of Ca2+ and/or Mn4+-doped BaTiO3 nanofibers decreased with increase in ion doping amount, it could maintain approx. 0.9–3.7 pC/N and comparable to that of native bone (0.7–2.3 pC/N) at an optimized content. Under the synergistic effect of the released bioactive ions and the material piezoelectricity, the BaTiO3 nanofibers co-doped with Mn4+ (2 mol%) and Ca2+ (10 mol%) (i.e., the sample 2Mn10Ca-BT) achieved the strongest capacity in enhancing the osteogenic differentiation of bone marrow mesenchymal stromal cells (BMSCs), while showing no cytotoxicity. In summary, bioactive ions-doped BaTiO3 nanofibers are promising scaffolds for bone tissue engineering, thanks to their acceptable biocompatibility, appropriate piezoelectricity, and improved osteogenic activity.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Bone Tissue Engineering Materials · Electrospun Nanofibers in Biomedical Applications · Advanced Sensor and Energy Harvesting Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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