Cargando…

Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study

Femtosecond laser-assisted material surface modification is a rapidly growing field with numerous applications, including tribology, micromechanics, optofluidics, and medical implant treatment. For many of these applications, precise control of surface roughness after laser treatment is crucial, as...

Descripción completa

Detalles Bibliográficos
Autores principales: Kažukauskas, Evaldas, Butkus, Simas, Jukna, Vytautas, Paipulas, Domas, Sirutkaitis, Valdas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10096257/
https://www.ncbi.nlm.nih.gov/pubmed/37049082
http://dx.doi.org/10.3390/ma16072788
_version_ 1785024290507194368
author Kažukauskas, Evaldas
Butkus, Simas
Jukna, Vytautas
Paipulas, Domas
Sirutkaitis, Valdas
author_facet Kažukauskas, Evaldas
Butkus, Simas
Jukna, Vytautas
Paipulas, Domas
Sirutkaitis, Valdas
author_sort Kažukauskas, Evaldas
collection PubMed
description Femtosecond laser-assisted material surface modification is a rapidly growing field with numerous applications, including tribology, micromechanics, optofluidics, and medical implant treatment. For many of these applications, precise control of surface roughness after laser treatment is crucial, as it directly affects the final properties of the work surface. However, achieving low mean surface roughness values (<100 nm) is challenging due to the fundamental principles of laser light–matter interactions. The complex physical processes that occur during laser material interactions make it difficult to achieve the desired surface roughness, and only advanced scanning methods can potentially solve this issue. In our study, we analyzed laser scanning algorithms to determine the optimal method for producing surfaces with minimal roughness. We investigated how scanning parameters such as the overlap of modifications, the amount of successive line shift, and laser-scanner synchronization impact surface roughness. Using a numerical model, we obtained results that showed good agreement with experimentally acquired data. Our detailed theoretical and experimental analysis of different scanning methods can provide valuable information for the future optimization of minimal-roughness micromachining.
format Online
Article
Text
id pubmed-10096257
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100962572023-04-13 Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study Kažukauskas, Evaldas Butkus, Simas Jukna, Vytautas Paipulas, Domas Sirutkaitis, Valdas Materials (Basel) Article Femtosecond laser-assisted material surface modification is a rapidly growing field with numerous applications, including tribology, micromechanics, optofluidics, and medical implant treatment. For many of these applications, precise control of surface roughness after laser treatment is crucial, as it directly affects the final properties of the work surface. However, achieving low mean surface roughness values (<100 nm) is challenging due to the fundamental principles of laser light–matter interactions. The complex physical processes that occur during laser material interactions make it difficult to achieve the desired surface roughness, and only advanced scanning methods can potentially solve this issue. In our study, we analyzed laser scanning algorithms to determine the optimal method for producing surfaces with minimal roughness. We investigated how scanning parameters such as the overlap of modifications, the amount of successive line shift, and laser-scanner synchronization impact surface roughness. Using a numerical model, we obtained results that showed good agreement with experimentally acquired data. Our detailed theoretical and experimental analysis of different scanning methods can provide valuable information for the future optimization of minimal-roughness micromachining. MDPI 2023-03-30 /pmc/articles/PMC10096257/ /pubmed/37049082 http://dx.doi.org/10.3390/ma16072788 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kažukauskas, Evaldas
Butkus, Simas
Jukna, Vytautas
Paipulas, Domas
Sirutkaitis, Valdas
Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study
title Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study
title_full Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study
title_fullStr Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study
title_full_unstemmed Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study
title_short Scanning Algorithm Optimization for Achieving Low-Roughness Surfaces Using Ultrashort Laser Pulses: A Comparative Study
title_sort scanning algorithm optimization for achieving low-roughness surfaces using ultrashort laser pulses: a comparative study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10096257/
https://www.ncbi.nlm.nih.gov/pubmed/37049082
http://dx.doi.org/10.3390/ma16072788
work_keys_str_mv AT kazukauskasevaldas scanningalgorithmoptimizationforachievinglowroughnesssurfacesusingultrashortlaserpulsesacomparativestudy
AT butkussimas scanningalgorithmoptimizationforachievinglowroughnesssurfacesusingultrashortlaserpulsesacomparativestudy
AT juknavytautas scanningalgorithmoptimizationforachievinglowroughnesssurfacesusingultrashortlaserpulsesacomparativestudy
AT paipulasdomas scanningalgorithmoptimizationforachievinglowroughnesssurfacesusingultrashortlaserpulsesacomparativestudy
AT sirutkaitisvaldas scanningalgorithmoptimizationforachievinglowroughnesssurfacesusingultrashortlaserpulsesacomparativestudy