Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications

Francisca Melo-Fonseca*, Bruno Guimarães, Michael Gasik, Filipe S. Silva, Georgina Miranda

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
46 Downloads (Pure)

Abstract

Laser surface texturing (LST) is a powerful technique for creating high quality micro-textured patterns with different shapes and sizes on metallic biomaterials. Textured surfaces may improve the interaction between bone and implant by increasing the surface contact area and thus promoting bone regeneration. The goal of this study was to explore Nd:YAG laser potential for texturing micro-scale pillars with pyramid geometry, with dimensions in a selected range, in a reproducible way. First, the design and texture of grooves were addressed, then proceeding to pillars. Two laser machining and marking strategies were investigated, and the consecutive laser processing strategy and continuous marking mode were selected due to the resultant smoother grooves. Then, a cross-hatched pattern was designed to texture a pillar pattern with targeted dimensions. Given the direct effect of the LST drawing and laser parameters on the texture dimensions, three mathematical models, one for each texture dimension (groove width, pillar width and pillar depth) were developed. These models are accurate tools for predicting the texture dimensions in the selected range and this LST approach was effective on creating well-defined, uniform and equally spaced surface textures on Ti6Al4V parts, in a reproducible way. A combination of drawing and laser parameters was selected for the target dimensions, also considering suitable wettability and roughness for biomedical applications.

Original languageEnglish
Article number102466
Number of pages14
JournalSurfaces and Interfaces
Volume35
Early online date13 Nov 2022
DOIs
Publication statusPublished - Dec 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Implants
  • Laser surface texturing
  • Nd:YAG laser
  • Predictive models
  • Surface roughness
  • Ti6Al4V

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