Yield estimation of metallic layers in integrated circuits
Wang Jun-Ping(王俊平)†, Hao Yue(郝跃), and Zhang Jun-Ming(张俊明)
Microelectronics Institute, Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, Xidian University, Xi'an 710071, China
Abstract In the existing models of estimating the yield and critical area, the defect outline is usually assumed to be circular, but the observed real defect outlines are irregular in shape. In this paper, estimation of the yield and critical area is made using the Monte Carlo technique and the relationship between the errors of yield estimated by circular defect and the rectangle degree of the defect is analysed. The rectangular model of a real defect is presented, and the yield model is provided correspondingly. The models take into account an outline similar to that of an original defect, the characteristics of two-dimensional distribution of defects, the feature of a layout routing, and the character of yield estimation. In order to make the models practicable, the critical area computations related to rectangular defect and regular (vertical or horizontal) routing are discussed. The critical areas associated with rectangular defect and non-regular routing are developed also, based on the mathematical morphology. The experimental results show that the new yield model may predict the yield caused by real defects more accurately than the circular model. It is significant that the yield is accurately estimated using the proposed model for IC metals.
Received: 08 August 2006
Revised: 09 January 2007
Accepted manuscript online:
PACS:
85.40.Bh
(Computer-aided design of microcircuits; layout and modeling)
Fund: Project supported by Xi'an
Applied Materials Innovation Fund (Grant No XA-AM-200601) and
National Laboratory on Machine Perception of Peking University
Fund (Grant No 0604).
Cite this article:
Wang Jun-Ping(王俊平), Hao Yue(郝跃), and Zhang Jun-Ming(张俊明) Yield estimation of metallic layers in integrated circuits 2007 Chinese Physics 16 1796
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.