<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Line-edge-roughness characterization of photomask patterns and lithography-printed patterns</dc:title><dc:creator>Wang, Zhikun; Lin, Pengfei; Nguyen, Phuc; Wang, Jingyan; Lee, ChaBum</dc:creator><dc:corporate_author/><dc:editor/><dc:description>This paper presents the line-edge-roughness (LER) characterization of the photomask patterns and the
lithography-printed patterns by enhanced knife edge interferometry (EKEI) that measures the interferometric
fringe patterns occurring when the light is incident on the patterned edge. The LER is defined as a geometric
deviation of a feature edge from an ideal sharp edge. The Fresnel number-based computational model was
developed to simulate the fringe patterns according to the LER conditions. Based on the computational model,
the photomask patterns containing LER features were designed and fabricated. Also, the patterns were printed on
the glass wafer by photolithography. The interferometric fringe patterns of those two groups of patterns were
measured and compared with the simulation results. By using the cross-correlation method, the LER effects on
the fringe patterns were characterized. The simulation and experimental results showed good agreement. It
showed that the amplitude of the fringe pattern decreases as the LER increases in both cases: photomask patterns and printed wafer patterns. As a result, the EKEI and its analysis methods showed the potential to be used in photomask design and pattern metrology, and inspection for advancing semiconductor manufacturing processes.</dc:description><dc:publisher>Precision Engineering</dc:publisher><dc:date>2024-06-01</dc:date><dc:nsf_par_id>10552498</dc:nsf_par_id><dc:journal_name>Precision Engineering</dc:journal_name><dc:journal_volume>88</dc:journal_volume><dc:journal_issue>C</dc:journal_issue><dc:page_range_or_elocation>235 to 240</dc:page_range_or_elocation><dc:issn>0141-6359</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1016/j.precisioneng.2024.02.006</dc:doi><dcq:identifierAwardId>2124999</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>