AFM nano-IR for photomask in-line defect characterization

Mitchell First; Elba Gomar-Nadal; Jeff Hsiao; Farhood Rasouli; Malahat Tavassoli; Chunzeng Li; Cassandra Phillips; Jason Osborne; Peter De Wolf

doi:10.1117/12.3037631

12 November 2024 AFM nano-IR for photomask in-line defect characterization

Mitchell First, Elba Gomar-Nadal, Jeff Hsiao, Farhood Rasouli, Malahat Tavassoli, Chunzeng Li, Cassandra Phillips, Jason Osborne, Peter De Wolf

Author Affiliations +

Proceedings Volume 13216, Photomask Technology 2024; 132160W (2024) https://doi.org/10.1117/12.3037631
Event: SPIE Photomask Technology + EUV Lithography, 2024, Monterey, California, United States

Abstract

As high-volume manufacturing (HVM) of photomasks of various types and processes expands, defects and their origin are of particular concern. Organic materials are present in many aspects of a photomask's lifecycle, from carriers and tool hardware to resists and chemical residues. Characterization of organic materials to determine their origin and mitigate their yield impact is quintessential to throughput time (TPT). With the emergence of atomic force microscopy-infrared spectroscopy (AFM-IR) failure analysis techniques, distinguishing organic defects and thin films with high resolution is limited only by the size of the AFM probe. Using the AFM-IR lab instrument, we collect IR spectra of many common materials found in our process to build a database, allowing future defects to be matched to our known materials and general external IR databases. To expand our capabilities, an in-line automated AFM with spectra acquisition capability is required, with cleanliness and recipe reliability required for factory use. Supporting this automated toolset, an automated reporting function has been developed to quickly provide customers with a complete picture of a defect, from AFM scan to IR spectra, complete with IR imaging at wavelengths of interest. This paper seeks to decode the nature of AFM Nano-IR and its place as a critical in-line defect analysis technique to increase yield and proactively prevent excursions in the HVM environment.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mitchell First, Elba Gomar-Nadal, Jeff Hsiao, Farhood Rasouli, Malahat Tavassoli, Chunzeng Li, Cassandra Phillips, Jason Osborne, and Peter De Wolf "AFM nano-IR for photomask in-line defect characterization", Proc. SPIE 13216, Photomask Technology 2024, 132160W (12 November 2024); https://doi.org/10.1117/12.3037631

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