Page 208 - DCAP601_SIMULATION_AND_MODELING

Simulation and Modelling

Notes 12.1 Experimental Layout

Validation of design rules taking into account fine details such as line-edge roughness, and full
chip layout simulation for design inconsistencies, before actual fabrication, are among the main
objectives of current software assisted metrology tools. Line-edge roughness quantification
should accompany Critical Dimension (CD) measurements since it could be a large fraction of
the total CD budget. A detailed simulation and metrology approach of line-edge roughness
quantification versus the length scales in a layout are presented in this work using a combination
of electron beam simulation for the exposure part, and stochastic simulations for the modeling
of resist film, postexposure bake, and resist dissolution. The method is applied also on a test
layout with critical dimension of 200 nm and the resulted simulation and scanning electron
microscopy images are compared with the aid of a pattern matching algorithm which enables
the identification of the desired layout for metrology on a complex layout containing many
printed features.

12.2 Validation

It starts with a short review of arguments used in the simsoc mailing list discussion on theory,
simulation and explanation a few months ago, deals with the use of quantitative and qualitative
computational models to make quantitative and qualitative predictions or rather to draw
conclusions from complex antecedents, and then discusses different types of explanation and
prediction (and the relation between these two), It closes with an overview of topics in validity
and validation from the point of view of the structuralist programme in the philosophy of
science.
A few months ago, the simsoc mailing list experienced a longish discussion1 which originated
from Thomas Kron’s question “about the relation of computer simulation and explanation,
especially sociological explanation”. More than fifty contributions to this discussion followed
within less than three weeks, and contributors discussed the role of simulation in theory building
(mostly, but not only) in the social, economic and management sciences—as well as the relation
between observation on one hand and computer-assisted theory building (Hanneman 1988) on
the other. Scott Moss came back to his presidential address at the 1st conference of the European
Social Simulation Association, Groningen, September 2003, in which he said “that if social
simulation with agents is to be anything other than another in the long line of failed approaches
to social science, it will be a positive departure only because it facilitates the dominance of
observation over theory” and continued that the great successful scientists (outside the social
sciences) built their generalisations around observation, developing new theoretical structures
based on and validated by new evidence (quoted from his contribution to the simsoc mailing
list as of November 14, 2003). Well in the line of this trait of thinking is the role of simulation or
computational modeling which can be found in Gilbert and Troitzsch 1999 which was recently
extended by Alexis Drogoul (Drogoul et al. 2003: 5) and can be seen in Figure 12.1.

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