This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or The Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or The Regents of the University of California.
Extreme ultraviolet mask substrate surface roughness effects on lithographic patterning J. Vac. Sci. Technol. B 28, C6E23 (2010); 10.1116/1.3502436The effects of oxygen plasma on the chemical composition and morphology of the Ru capping layer of the extreme ultraviolet mask blanks Cleaning of extreme ultraviolet lithography optics and masks using 13.5 nm and 172 nm radiation Extreme UV ͑EUV͒ masks are expected to undergo cleaning processes in order to maintain the lifetimes necessary for high volume manufacturing. For this study, the impact of repetitive cleaning of EUV masks on imaging performance is evaluated. Two high quality industry standard EUV masks are used, with one of the masks undergoing repeated cleaning and the other one kept as a reference. Lithographic performance, in terms of process window analysis and line edge roughness, was monitored after every two cleans and was compared to the reference mask performance. Surface analysis by atomic force microscopy did not show changes in the midspatial frequency roughness measured after each clean. After a total of eight cleans, minimal degradation is observed in the lithographic performance of the mask. From these observations, the authors conclude that the cleaning cycles completed thus far did not damage the mask multilayer or the absorber structures. The cleaning cycles will be continued until significant loss in imaging fidelity is found.
For this paper, we evaluated the impact of repetitive cleans on a photomask that was fabricated and patterned for extreme ultraviolet lithography exposure. The lithographic performance of the cleaned mask, in terms of process window and line edge roughness, was monitored with the SEMATECH Berkeley micro-exposure tool (MET). Each process measurement of the cleaned mask was compared to a reference mask with the same mask architecture. Both masks were imaged on the same day in order to eliminate any process-related measurement uncertainties. The cleaned mask was periodically monitored with atomic force microscopy (AFM) measurements and pattern widths were monitored using scanning electron microscopy (SEM). In addition, reflectivity changes were also tracked with the aid of witness plate measurements. At the conclusion of this study, the mask under evaluation was cleaned 22 times; with none of the evaluation techniques showing any significant degradation in performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.