Michael Kotelyanskii - Chatham NJ, US Xueping Ru - Washington NJ, US Robert G. Wolf - Hackettstown NJ, US Yue Yang - Millburn NJ, US
International Classification:
G06F 17/50
US Classification:
703 1
Abstract:
A method includes accessing a structure model defining a cross-sectional profile of a structure on a sample. The cross-sectional profile is at least partially defined using a set of blocks. Each of the blocks includes a number of vertices. One or more of the vertices are expressed using one or more algebraic relationships between a number of parameters corresponding to the structure. Information is evaluated from the structure model to produce expected metrology data for a scatterometry-based optical metrology. The expected metrology data is suitable for use for determining one or more of the number of parameters corresponding to the structure. Apparatus are also disclosed.
Non-Destructive Acoustic Metrology For Void Detection
- Denver CO, US Michael KOTELYANSKII - Chatham NJ, US Todd W. MURRAY - Golden CO, US Robin MAIR - West Chicago IL, US Priya MUKUNDHAN - Lake Hopatcong NJ, US Jacob D. DOVE - Boulder CO, US Xueping RU - Flanders NJ, US Jonathan COHEN - Flanders NJ, US Timothy KRYMAN - Flanders NJ, US
Assignee:
The Regents of the University of Colorado - Denver CO
Advanced interconnect technologies such as Through Silicon Vias (TSVs) have become an integral part of 3-D integration. Methods and systems and provided for laser-based acoustic techniques in which a short laser pulse generates broadband acoustic waves that propagate in the TSV structure. An optical interferometer detects the surface displacement caused by the acoustic waves reflecting within the structure as well as other acoustic waves traveling near the surface that has information about the structure dimensions and irregularities, such as voids. Features of voids, such as their location, are also identified based on the characteristics of the acoustic wave as it propagates through the via. Measurements typically take few seconds per site and can be easily adopted for in-line process monitoring.