The ever increasing pattern densities and design complexities make the tuning of optical proximity correction (OPC) recipes very challenging. One known method for tuning is genetic algorithm (GA). Previously GA has been demonstrated to fine tune OPC recipes in order to achieve better results for possible 1D and 2D geometric concerns like bridging and pinching. This method, however, did not take into account the impact of excess segmentation on downstream operations like fracturing and mask writing.
This paper introduces a general methodology to significantly reduce the number of excess edges in the OPC output, thus reducing the number of flashes generated at fracture and subsequently the write time at mask build. GA is used to reduce the degree of unwarranted segmentation while ensuring good OPC quality. An Objective Function (OF) is utilized to ensure quality convergence and process-variation (PV) plus an additional weighed factor to reduce clustered edge count.
The technique is applied to 14nm metal layer OPC recipes in order to identify excess segmentation and to produce a modified recipe that significantly reduces these segments. OPC output file sizes is shown to be reduced by 15% or more and overall edge count is shown to be reduced by 10% or more. At the same time overall quality of the OPC recipe is shown to be maintained via OPC Verification (OPCV) results.
The ever increasing pattern densities and design complexities make the tuning of optical proximity correction (OPC)
recipes more challenging. There are various recipe tuning methods to meet the challenge, such as genetic algorithm
(GA), simulated annealing, and OPC software vendor provided recipe optimizers. However, these methodologies usually
only consider edge placement errors (EPEs). Therefore, these techniques may not provide adequate freedom to solve
unique problems at special geometries, for example bridge, pinch, and process variation band related violations at
complex 2D geometries.
This paper introduces a general methodology to fix specific problems identified at the OPC verification stage and
demonstrates its successful application to two test-cases. The algorithm and method of the automatic scoring system is
introduced in order to identify and prioritize the problems that need to be fixed based on severity, with the POR recipe
score used as the baseline reference. A GA optimizer, whose objective function is based on the scoring system, is
applied to tune the OPC recipe parameters to optimum condition after generations of selections. The GA optimized
recipe would be compared to existing recipe to quantify the amount of improvement.
This technique was subsequently applied to eliminate certain chronic OPC verification problems which were
encountered in the past. Though the benefits have been demonstrated for limited test cases, employing this technique
more universally will enable users to efficiently reduce the number of OPC verification violations and provide robust
OPC solutions.
The utilization of a cut-mask in semiconductor patterning processes has been in practice for logic devices since the inception of 32nm-node devices, notably with unidirectional gate level printing. However, the microprocessor applications where cut-mask patterning methods are used are expanding as Self-Aligned Double Patterning (SADP) processes become mainstream for 22/14nm fin diffusion, and sub-14nm metal levels. One common weakness for these types of lithography processes is that the initial pattern requiring the follow-up cut-mask typically uses an extreme off-axis imaging source such as dipole to enhance the resolution and line-width roughness (LWR) for critical dense patterns. This source condition suffers from poor process margin in the semi-dense (forbidden pitch) realm and wrong-way directional design spaces. Common pattern failures in these limited design regions include bridging and extra-printing defects that are difficult to resolve with traditional mask improvement means. This forces the device maker to limit the allowable geometries that a designer may use on a device layer.
This paper will demonstrate methods to expand the usable design space on dipole-like processes such as unidirectional gate and SADP processes by utilizing the follow-up cut mask to improve the process window. Traditional mask enhancement means for improving the process window in this design realm will be compared to this new cut-mask approach. The unique advantages and disadvantages of the cut-mask solution will be discussed in contrast to those customary methods.
Optimization of OPC recipes is not trivial due to multiple parameters that need tuning and their correlation. Usually, no standard methodologies exist for choosing the initial recipe settings, and in the keyword development phase, parameters are chosen either based on previous learning, vendor recommendations, or to resolve specific problems on particular special constructs. Such approaches fail to holistically quantify the effects of parameters on other or possible new designs, and to an extent are based on the keyword developer’s intuition. In addition, when a quick fix is needed for a new design, numerous customization statements are added to the recipe, which make it more complex.
The present work demonstrates the application of Genetic Algorithm (GA) technique for optimizing OPC recipes. GA is a search technique that mimics Darwinian natural selection and has applications in various science and engineering disciplines. In this case, GA search heuristic is applied to two problems: (a) an overall OPC recipe optimization with respect to selected parameters and, (b) application of GA to improve printing and via coverage at line end geometries. As will be demonstrated, the optimized recipe significantly reduced the number of ORC violations for case (a). For case (b) line end for various features showed significant printing and filling improvement.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.