journal article·2015-07

Injectability of calcium phosphate pastes: Effects of particle size and state of aggregation of β-tricalcium phosphate powders

P.M.C. Torres, S. Gouveia, S. Olhero, A. Kaushal, J.M.F. Ferreira

Acta Biomaterialia· Volume 21
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Abstract

The present study discloses a systematic study about the influence of some relevant experimental variables on injectability of calcium phosphate cements. Non-reactive and reactive pastes were prepared, based on tricalcium phosphate doped with 5 mol% (Sr-TCP) that was synthesised by co-precipitation. The varied experimental parameters included: (i) the heat treatment temperature within the range of 800-1100°C; (ii) different milling extents of calcined powders; (iii) the liquid-to-powder ratio (LPR); (iv) the use of powder blends with different particle sizes (PS) and particle size distributions (PSD); (v) the partial replacement of fine powders by large spherical dense granules prepared via freeze granulation method to simulate coarse individual particles. The aim was contributing to better understanding of the effects of PS, PSD, morphology and state of aggregation of the starting powders on injectability of pastes produced thereof. Powders heat treated at 800 and 1000°C with different morphologies but with similar apparent PSD curves obtained by milling/blending originated completely injectable reactive cement pastes at low LPR. This contrasted with non-reactive systems prepared thereof under the same conditions. Hypotheses were put forward to explain why the injectability results collected upon extruding non-reactive pastes cannot be directly transposed to reactive systems. The results obtained underline the interdependent roles of the different powder features and ionic strength in the liquid media on determining the flow and injectability behaviours.
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Research context

OpenAlex topics: Bone Tissue Engineering Materials · Advanced materials and composites · Magnesium Oxide Properties and Applications

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

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