Kla Tencor Corporation

Kla Corporation

Mikhail M Sushchik

Leonid Poslavsky

Natalia Malkova

Shankar Krishnan

Lanhua Wei

Hidong Kwak

Dawei Hu

Paul Aoyagi

John F Lesoine

Malik Sadiq

Hanyou Chu

Alexander Kuznetsov

Houssam Chouaib

Liequan Lee

Mark Allen Neil

Philip D Flanner, Iii

Carlos L Ygartua

Peilin Jiang

Jonathan Iloreta

Phillip Atkins

Manh Nguyen

Jeffrey Chard

A parameterized geometric model of a structure can be determined based on spectra from a wafer metrology tool. The structure can have geometry-induced anisotropic effects. Dispersion parameters of the structure can be determined from the parameterized geometric model. This can enable metrology techniques to measure nanostructures that have geometries and relative positions with surrounding structures that induce non-negligible anisotropic effects. These techniques can be used to characterize process steps involving metal and semiconductor targets in semiconductor manufacturing of, for example, FinFETs or and gate-all-around field-effect transistors.

Measurement methodology of advanced nanostructures

Methods and systems for estimating values of parameters of interest from optical measurements of a sample early in a production flow based on a multidimensional optical dispersion (MDOD) model are presented herein. An MDOD model describes optical dispersion of materials comprising a structure under measurement in terms of parameters external to a base optical dispersion model. In some examples, a power law model describes the physical relationship between the external parameters and a parameter of the base optical dispersion model. In some embodiments, one or more external parameters are treated as unknown values that are resolved based on spectral measurement data. In some embodiments, one or more external parameters are treated as known values, and values of base optical dispersion model parameters, one or more external parameters having unknown values, or both, are resolved based on spectral measurement data and the known values of the one or more external parameters.

Multi-dimensional model of optical dispersion

Methods and systems for matching measurement spectra across one or more optical metrology systems are presented. The values of one or more system parameters used to determine the spectral response of a specimen to a measurement performed by a target metrology system are optimized. The system parameter values are optimized such that differences between measurement spectra generated by a reference system and the target system are minimized for measurements of the same metrology targets. Methods and systems for matching spectral errors across one or more optical metrology systems are also presented. A trusted metrology system measures the value of at least one specimen parameter to minimize model errors introduced by differing measurement conditions present at the time of measurement by the reference and target metrology systems. Methods and systems for parameter optimization based on low-order response surfaces are presented to reduce the compute time required to refine system calibration parameters.

Metrology system calibration refinement

A metrology system includes a controller coupled to a detector to generate a detection signal based on the reflection of an illumination beam from a multilayer film stack. The multilayer film stack may include one or more zones with a repeating pattern of two or more materials. The controller may generate a model of reflection of the illumination beam by modeling the zones as thick films having zone thicknesses and effective permittivity values using an effective medium model relating the effective permittivity values of the zones to permittivity values and volume fractions of constituent materials. The controller may further determine values of the zone thicknesses and the volume fractions using a regression of the detection signal based on the effective medium model and further determine average thickness values of the constituent materials based on the number of films, the zone thicknesses, the volume fractions, and the effective permittivity values.

Multilayer film metrology using an effective media approximation

Provided are optimized scatterometry techniques for evaluating a diffracting structure. In one embodiment, a method includes computing a finite-difference derivative of a field matrix with respect to first parameters (including a geometric parameter of the diffracting structure), computing an analytic derivative of the Jones matrix with respect to the field matrix, computing a derivative of the Jones matrix with respect to the first parameters, and computing a finite-difference derivative of the Jones matrix with respect to second parameters (including a non-geometric parameter). In one embodiment, a method includes generating a transfer matrix having Taylor Series approximations for elements, and decomposing the field matrix into two or more smaller matrices based on symmetry between the incident light and the diffracting structure.

Techniques for optimized scatterometry

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Castro Valley, CA, United States of America

Mikhail M Sushchik