Critical dimension measurements with gaseous adsorption

Abstract

Methods and systems for performing optical measurements of geometric structures filled with an adsorbate by a gaseous adsorption process are presented herein. Measurements are performed while the metrology target under measurement is treated with a flow of purge gas that includes a controlled amount of fill material. A portion of the fill material adsorbs onto the structures under measurement andfills openings in the structural features, spaces between structural features, small volumes such as notches, trenches, slits, contact holes, etc. In one aspect, the desired degree of saturation of vaporized material in the gaseous flow is determined based on the maximum feature size to be filled. In one aspect, measurement data is collected when a structure is unfilled and when the structure is filled by gaseous adsorption. The collected data is combined in a multi-target model based measurement to reduce parameter correlations and improve measurement performance.

Description

[0001] Cross References to Related Applications [0002] This patent application is asserted under 35 U.S.C. §119 U.S. Provisional No. 62 / 330,751, filed May 2, 2016, entitled "Porosity and Critical Dimension Measurements Using Gaseous Adsorption" priority to the patent application, the subject matter of which is hereby incorporated by reference in its entirety. technical field [0003] The described embodiments relate to metrology systems and methods, and more particularly to methods and systems for improved measurement of structures fabricated in the semiconductor industry. Background technique [0004] Semiconductor devices such as logic and memory devices are typically fabricated by a series of processing steps applied to samples. Various features and various structural levels of semiconductor devices are formed by these processing steps. For example, photolithography is a semiconductor manufacturing process that involves creating patterns on semiconductor wafers. Add...

AI Technical Summary

Problems solved by technology

Although fixing the values ​​of several parameters can improve computation speed and reduce the influence of parameter dependencies, it also leads to errors in the estimation of parameter values

[0008] Currently, solutions to complex multi-parameter measurement models often require unsatisfactory trade-offs

Current model reduction techniques are sometimes not able to arrive at a measurement model that is both computationally tractable and sufficiently accurate

Also, complex multi-parameter models make it difficult or impossible to optimize system parameter selection for each parameter of interest (e.g., wavelength, angle of incidence, etc.)

Images