Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Optimization study of the femtosecond laser-induced forward-transfer process with thin aluminum films

Not Accessible

Your library or personal account may give you access

Abstract

The parameters for an effective laser-induced forward-transfer (LIFT) process of aluminum thin films using a femtosecond laser are studied. Deposited feature size as a function of laser fluence, donor film thickness, quality of focus, and the pulse duration are varied, providing a metric of the most desirable conditions for femtosecond LIFT with thin aluminum films.

© 2007 Optical Society of America

Full Article  |  PDF Article
More Like This
Production of 70-nm Cr dots by laser-induced forward transfer

Vahit Sametoglu, Vincent T. K. Sauer, and Ying Y. Tsui
Opt. Express 21(15) 18525-18531 (2013)

Influence of optical standing waves on the femtosecond laser-induced forward transfer of transparent thin films

David P. Banks, Kamal Kaur, and Robert W. Eason
Appl. Opt. 48(11) 2058-2066 (2009)

Dynamic spatial pulse shaping via a digital micromirror device for patterned laser-induced forward transfer of solid polymer films

Daniel J Heath, Matthias Feinaeugle, James A Grant-Jacob, Ben Mills, and Robert W Eason
Opt. Mater. Express 5(5) 1129-1136 (2015)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (12)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.