Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/36479 |
Resumo: | 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. |
id |
RCAP_7a97f1ca9d971721bd878014ad1fea51 |
---|---|
oai_identifier_str |
oai:ria.ua.pt:10773/36479 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applicationsLaser surface texturingNd: YAG laserTi6Al4VPredictive modelsSurface roughnessImplantsLaser 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.Elsevier2023-03-06T15:51:21Z2022-01-01T00:00:00Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/36479eng10.1016/j.surfin.2022.102466Melo-Fonseca, FranciscaGuimarães, BrunoGasik, MichaelSilva, Filipe S.Miranda, Georginainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:09:49Zoai:ria.ua.pt:10773/36479Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:07:05.258334Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
title |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
spellingShingle |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications Melo-Fonseca, Francisca Laser surface texturing Nd: YAG laser Ti6Al4V Predictive models Surface roughness Implants |
title_short |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
title_full |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
title_fullStr |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
title_full_unstemmed |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
title_sort |
Experimental analysis and predictive modelling of Ti6Al4V laser surface texturing for biomedical applications |
author |
Melo-Fonseca, Francisca |
author_facet |
Melo-Fonseca, Francisca Guimarães, Bruno Gasik, Michael Silva, Filipe S. Miranda, Georgina |
author_role |
author |
author2 |
Guimarães, Bruno Gasik, Michael Silva, Filipe S. Miranda, Georgina |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Melo-Fonseca, Francisca Guimarães, Bruno Gasik, Michael Silva, Filipe S. Miranda, Georgina |
dc.subject.por.fl_str_mv |
Laser surface texturing Nd: YAG laser Ti6Al4V Predictive models Surface roughness Implants |
topic |
Laser surface texturing Nd: YAG laser Ti6Al4V Predictive models Surface roughness Implants |
description |
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. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01T00:00:00Z 2022 2023-03-06T15:51:21Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/36479 |
url |
http://hdl.handle.net/10773/36479 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.surfin.2022.102466 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799137726475272192 |