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Effect of Proximity of Features on the Damage Threshold during Submicron Additive Manufacturing via Two-Photon Polymerization

[+] Author and Article Information
Sourabh K. Saha

Materials Engineering Division Lawrence Livermore National Laboratory Livermore, CA, USA
saha5@llnl.gov

Chuck Divin

Materials Engineering Division Lawrence Livermore National Laboratory Livermore, CA, USA
divin1@llnl.gov

Jefferson A. Cuadra

Materials Engineering Division Lawrence Livermore National Laboratory Livermore, CA, USA
cuadra1@llnl.gov

Robert M. Panas

Materials Engineering Division Lawrence Livermore National Laboratory Livermore, CA, USA
panas3@llnl.gov

1Corresponding author.

ASME doi:10.1115/1.4036445 History: Received August 05, 2016; Revised March 24, 2017

Abstract

Two-photon polymerization (TPP) is a laser writing process that enables fabrication of millimeter scale 3D structures with submicron features. In TPP, writing is achieved via nonlinear two-photon absorption that occurs at high laser intensities. Thus, it is essential to carefully select the incident power to prevent laser damage during polymerization. Currently, the feasible range of laser power is identified by writing small test patterns at varying power levels. Herein, we demonstrate that the results of these tests cannot be generalized because the damage threshold power depends on the proximity of features and reduces by as much as 47% for overlapping features. We have identified that this reduction occurs primarily due to an increase in the single-photon absorptivity of the resin after curing. We have captured the damage from proximity effects via X-ray 3D computed tomography images of a non-homogenous part that has varying feature density. Part damage manifests as internal spherical voids that arise due to boiling of the resist. We have empirically quantified this proximity effect by identifying the damage threshold power at different writing speeds and feature overlap spacings. In addition, we present a first-order analytical model that captures the scaling of this proximity effect. Based on this model and the experiments, we have identified that the proximity effect is more significant at high writing speeds; therefore it adversely affects scalability of manufacturing. The scaling laws and the empirical data generated here can be used to select the appropriate TPP writing parameters.

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