Optimal surface roughness of Ti6Al4V alloy for the adhesion of cells with osteogenic potential
Source abstract
Abstract
The effect of surface roughness of cold-wrought Ti-6Al-4V (VT6) alloy on the adhesion of mouse MC3T3-pre-osteoblasts cells has been studied. The array of linear grooves has been produced on the substrate surface with the aid of abrasive SiC papers with grit sizes of 220, 400, 600, 800, 1000, 1200, 2000, and 4000 (number of grains per cm2), as well as different diamond pastes with grain sizes 6, 3, and 1 μm. The grain size of this array of abrasive papers and diamond pastes monotonously decreases from 68 μm (for 220 grit paper) to 1 μm for the finest diamond paste. The adhesion of the mouse MC3T3-pre-osteoblast cells to the samples with different roughness has been measured by fluorescence microscopy. The size and morphology of adhered cells were measured by the light microscopy. The relative fraction of adhered cells behaves non-monotonously with the abrasive grain size. It is about 0.35 for grain size of 1 μm, increases up to 0.95 for grain size of 7 μm, and then slowly decreases down to 0.55 for abrasive grain size of 68 μm. The surface roughness parameters of Ti–6Al–4V (VT6) alloy correlate with the depth and width of grooves produced on the initially flat surface of the alloy. The surface ground with a grinding media corresponding to the grain size of about 10 μm exhibited highest cell adhesion. This grain size corresponding to maximum cells adhesion is comparable with the dimension of MC3T3-pre-osteoblasts cells (~ 14 μm). Thus, the variation of surface roughness opens the way to control and tailor the fraction of adhered cells, depending on the demand of medical techniques.Graphical abstract
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Bone Tissue Engineering Materials · Additive Manufacturing and 3D Printing Technologies · Additive Manufacturing Materials and Processes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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