Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642802
Title: Efficient critical area extraction for photolithographically defined patterns on ICs
Author: Chia, Mark P. C.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2002
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Abstract:
The IC industry is developing at a phenomenal rate where smaller and denser chips are being manufactured. The yield of the fabrication process is one of the key factors that determine the cost of a chip. The pattern transfered onto silicon is not a perfect representation of the mask layout, and for an SRAM cell this results in a difference of 3 % between the average number of faults calculated from the mask layout and the aerial image. This thesis investigates methods that are capable of better estimating the yield of an IC during their design phase which can efficiently and accurately estimate the critical area (CA) without the need to directly calculate the aerial image. The initial attempt generates an equivalent set of parallel lines from the mask layout which is then used to estimate the CA after pattern transfer. To achieve this EYE, Depict and WorkBench were integrated with in-house software. Benchmarking on appropriate layouts resulted in estimates within 0.5 - 2.5 % of the aerial image compared with 1.5 -3.5 % for the mask layout. However, for layouts which did not lend themselves to representation by equivalent parallel lines, this method resulted in estimates that were not as accurate as those obtained using the mask layout. The second approach categorises CA curves into different groups based on physical characteristics of the layout. By identifying which group a curve belongs to, the appropriate mapping can be made to estimate the pattern transfer process. However, due to the large number of track combinations it proved too difficult to reliably classify layouts into an appropriate group. Another method proposed determines a track length and position using a combination of AND and OR operations with shifting algorithms. The limitation of this approach was that it was not robust and only proved to work with certain layout types. The fourth method used a one dimensional algorithm to categorise layouts. The estimated CA was within 0.2 % of the aerial image as compared to the mask layout CA of 2.2 %. The disadvantage of this method is that it can only classify parallel tracks. The next approach built upon the above method and can categorise a layout in two dimensions, not being limited to parallel tracks. A variety of designs were used as benchmarks, and for these layouts this method resulted in estimates that were within 0 - 10.7 % of the aerial image compared with 0.5 - 13.4 % for the mask layout.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.642802  DOI: Not available
Share: