JOURNAL ARTICLE
Comparison of Al- and Hf-based hybrid photoresists grown by molecular layer deposition for extreme ultraviolet lithography.
Published In: Journal of Vacuum Science & Technology: Part A-Vacuums, Surfaces & Films, 2024, v. 42, n. 6. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Ravi, Ajay; Than, Long Viet; Lewis, Jacqueline; Shi, Jingwei; Werbrouck, Andreas; Han, Jingyi; Mattinen, Miika; Bent, Stacey F. 3 of 3
Abstract
This article focuses on the development and characterization of aluminum-based hybrid "alucone" thin films synthesized via molecular layer deposition (MLD) for use as negative-tone resists in extreme ultraviolet (EUV) lithography. Two types of alucone films—standard and oxygen-rich—were compared in terms of composition, sensitivity, and resolution, with electron-beam lithography serving as a proxy for EUV exposure. Oxygen-rich alucone exhibited higher sensitivity (4800 μC/cm²) than standard alucone (>18,000 μC/cm²), while both achieved a resolution of approximately 20 nm, surpassing the 50 nm resolution of previously studied hafnium-based "hafnicone" films. Differences in resist performance between alucone and hafnicone were attributed to the oxophilicity of the metal atoms, with hafnium’s higher oxophilicity leading to greater sensitivity but lower resolution due to nanoparticle formation dynamics. These findings enhance understanding of how MLD film chemistry influences irradiation response, informing the optimization of resist materials for advanced microelectronics fabrication.
Additional Information
- Source:Journal of Vacuum Science & Technology: Part A-Vacuums, Surfaces & Films. 2024/12, Vol. 42, Issue 6, p1
- Document Type:Article
- Subject Area:Physics
- Publication Date:2024
- ISSN:07342101
- DOI:10.1116/6.0003975
- Accession Number:181207934
- Copyright Statement:Copyright of Journal of Vacuum Science & Technology: Part A-Vacuums, Surfaces & Films is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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