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"Methods for comparative extraction of OPC response"

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SPIE Advanced Lithography 2007 Conference 01-Mar-2007

http://spie.org/Conferences/programs/07/al/

Download Pre-Print: 

Method_for_ExtractingOPC_Response_SPIE6520-64.pdf

Contact TEA Systems for Demonstration

Throw out your old Process Window Analysis to Improve Photomask Design!

• Process Window calculations have been used for over 30 years with no significant change.

• Process behavior models can extract true reticle feature response across the full exposure field and process-space.

• A simpler and more cost effective approach to optimized design selection is presented in techniques that can compare the performance of critical-feature design alternatives and model their robustness to a user’s unique capabilities. This ability to generate process and design-specific Process Behavioral Models provides the opportunity to evaluate the full spectrum of design alternatives, photomask-manufacturing signatures and device-manufacture process capabilities to select an optimum set of patterns from the basic design alternatives of the reticle.

• The result is a photomask that works best for each specific process and exhibits superior tolerance to process variations while minimizing the hassle involved in the complex techniques currently used to control illumination characteristics on the exposure tool

Abstract

The current ITRS roadmap details the growing complexity of device design and the latest device-manufacturer’s techniques for tuning their process for each new design generation. In spite of the current desire to incorporate techniques termed “Design for Manufacture” (DFM) into the sequence, simulations and the design cycle do little more than optimize feature quality for ideal exposure conditions while testing for shorts, opens and overlay problems over process variations. Testing in the DFM simulation is performed by the adaptation of a technique unchanged in the last 30 years, the Process Window analysis. With this, mediocre successes seen in chip-design have not taken their share of the burden of technology advancement. Consequently, process adaptation to each new design has fallen to increasingly complex setup procedures of the exposure toolsets that customize scanner performance for each new device.

Design optimization by simulation focuses on feature layout optimization for resolution. Design solutions that take advantage of the full potential spectrum of mask-feature alternatives to increase functional process-space and simplify setup in manufacturing do not exist since there is no method of feedback. A mechanism is needed that can quantify design performance robustness, with mask-contributions, to variations in the user’s specific manufacturing process.

In this study, a Process Behavior Model methodology is presented for the analysis of feature profiles and films to derive the relative robustness of response to process variations for alternative OPC designs. Analysis is performed without regard to the specific mechanics of the design itself. The design alternatives of each OPC feature are shown to be strong contributors not only to resolution and depth-of-focus but also to the stability of final image response; that is the ability of the feature profile to remain at optimum under varying conditions of process exposure excursion.

Several different, 70 nm multi-pitch OPC designs are compared for their response stability to fluctuations of the process. The optimal process corrections on the reticle are shown to be dependent upon not only the final image size at some optimal exposure point but also on the ability of the design to maintain feature size within tolerance across an increasingly large process-space of the target production process.  The failure of the classic Process Window analysis to anticipate or provide corrective insight for performance improvement under these conditions is illustrated.

Models are presented that allow the extraction of the nonlinear but systematic interactions of several OPC designs with the normal fluctuations experienced across the process exposure space plus those introduced by the toolset and film-stack variation.  A method of extracting the systematic component of each feature’s design-iteration is derived providing the ability to quantify the specific OPC response sensitivity to changes in the exposure and process films as well as drift introduced by the tools of the exposure set.

TEA Systems

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