Kla Tencor Corporation

Kla Corporation

Jonathan Iloreta

Leonid Poslavsky

Liequan Lee

John Josef Hench

Thaddeus Gerard Dziura

Qiang Zhao

Andrei Veldman

Antonio Arion Gellineau

Houssam Chouaib

Yin Xu

Aaron J Rosenberg

Kaiwen Xu

Abhi Gunde

Hanyou Chu

Torsten Rudolf Kaack

Lie-Quan Lee

Paul Aoyagi

Hong Qiu

Philip D Flanner, Iii

Peilin Jiang

Mikhail M Sushchik

Matthew A Laffin

Jeffrey Chard

A semiconductor metrology tool inspects an area of a semiconductor wafer. The inspected area includes a plurality of instances of a 3D semiconductor structure arranged periodically in at least one dimension. A computer system generates a model of a respective instance of the 3D semiconductor structure based on measurements collected during the inspection. The computer system renders an augmented-reality or virtual-reality (AR/VR) image of the model that shows a 3D shape of the model and provides the AR/VR image to an AR/VR viewing device for display.

Visualization of three-dimensional semiconductor structures

A semiconductor metrology tool inspects an area of a semiconductor wafer. The inspected area includes a plurality of instances of a 3D semiconductor structure arranged periodically in at least one dimension. A computer system generates a model of a respective instance of the 3D semiconductor structure based on measurements collected during the inspection. The computer system renders an image of the model that shows a 3D shape of the model and provides the image to a device for display.

A system, method, and computer program product are provided for automatically determining a parameter causing an abnormal semiconductor metrology measurement. In use, an abnormal semiconductor metrology measurement measured from a fabricated semiconductor component is received. At least one parameter of the fabricated semiconductor component causing the abnormal semiconductor metrology measurement is then automatically determined by one or more hardware processors. In particular, the one or more hardware processors determine a subset of parameters of the fabricated semiconductor component as potential sources of the abnormal semiconductor metrology measurement, rank the parameters in the determined subset of parameters, select an Nth number of the parameters in the determined subset of parameters in accordance with the ranking, and then analyze each of the selected parameters to identify one or more of the selected parameters as the at least one parameter of the fabricated semiconductor component causing the abnormal semiconductor metrology measurement.

System, method, and computer program product for automatically determining a parameter causing an abnormal semiconductor metrology measurement

Methods and tools for generating measurement models of complex device structures based on re-useable, parametric models are presented. Metrology systems employing these models are configured to measure structural and material characteristics associated with different semiconductor fabrication processes. The re-useable, parametric sub-structure model is fully defined by a set of independent parameters entered by a user of the model building tool. All other variables associated with the model shape and internal constraints among constituent geometric elements are pre-defined within the model. In some embodiments, one or more re-useable, parametric models are integrated into a measurement model of a complex semiconductor device. In another aspect, a model building tool generates a re-useable, parametric sub-structure model based on input from a user. The resulting models can be exported to a file that can be used by others and may include security features to control the sharing of sensitive intellectual property with particular users.

Semiconductor device models including re-usable sub-structures

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

Growing community of inventors

Menlo Park, CA, United States of America

Jonathan Iloreta