This will count as one of your downloads.
You will have access to both the presentation and article (if available).
This idea was advanced to account for pinching and bridging print contour constraints in the paper "Controlling Bridging and Pinching with Pixel-based Mask for Inverse Lithograph'' by S. Kobelkov and others in 2015.
The present paper extends this approach further for solving the enclosure print image constraints, getting maximum common depth of focus, and obtaining uniform PV-bands.
Namely, we suggest several objective functions that express penalty for constraint violations. Their minimization with gradient descent methods is considered. A number of applications have been tested with ILTbased pxOPC tool for DUV metal, contacts, and EUV metal layouts; results are discussed showing benefits of each approach.
In realistic designs, the same implantation shape may be found in a vertical or in a rotated horizontal orientation. This creates two types of relationships between the critical dimension (CD) and FinFET, namely parallel to and perpendicular to the fins. The measurement data shows that CDs differ between these two orientations. This discrepancy is also revealed by our Rigorous Optical Topography simulator. Numerical experiments demonstrate that the shape orientation may introduce CD differences of up to 45 nm with a 248 nm illumination for 14 nm technology. These differences are highly dependent on the enclosure (distance between implantation shape and active area). One of the major causes of the differences is that in the parallel orientation the shape is facing solid sidewalls of fins, while the perpendicular oriented shape “sees” only perforated sidewalls of the fin structure, which reflect much less energy.
Meticulously stated numerical experiments helped us to thoroughly understand anisotropic behavior of CD measurement. This allowed us to more accurately account for FinFET-related topography effects in the compact implantation modeling for optical proximity corrections (OPC). This improvement is validated against wafer measurement data.
Chemo, and grapho epitaxy of lines and space structures are now routinely inspected at full wafer level to understand the defectivity limits of the materials and their maximum resolution. In the same manner, there is a deeper understanding about the formation of cylinders using grapho-epitaxy processes. Academia has also contributed by developing methods that help reduce the number of masks in advanced nodes by “combining” DSA-compatible groups, thus reducing the total cost of the process.
From the point of view of EDA, new tools are required when a technology is adopted, and most technologies are adopted when they show a clear cost-benefit over alternative techniques. In addition, years of EDA development have led to the creation of very flexible toolkits that permit rapid prototyping and evaluation of new process alternatives. With the development of high-chi materials, and by moving away of the well characterized PS-PMMA systems, as well as novel integrations in the substrates that work in tandem with diblock copolymer systems, it is necessary to assess any new requirements that may or may not need custom tools to support such processes.
Hybrid DSA processes (which contain both chemo and grapho elements), are currently being investigated as possible contenders for sub-5nm process techniques. Because such processes permit the re-distribution of discontinuities in the regular arrays between the substrate and a cut operation, they have the potential to extend the number of applications for DSA.
This paper illustrates the reason as to why some DSA processes can be supported by existing rules and technology, while other processes require the development of highly customized correction tools and models. It also illustrates how developing DSA cannot be done in isolation, and it requires the full collaboration of EDA, Material’s suppliers, Manufacturing equipment, Metrology, and electronic manufacturers.
Mathematical Optimization is an empowering and indispensable tool in productive engineering practices. A variety of lithographical applications rely on optimization methods to deliver efficient engineering solutions: Process engineers routinely tune the number of films and optical properties of resist stacks, while lithographers subject the projection illuminator towards a laborious perfection by using Source-Mask Optimization (SMO). The spectrum of methods, which are used in the aforementioned (and numerous other) everyday practices, is broad. Finding a suitable algorithm for a given problem is not always easy.
This course classifies lithography-related optimization problems, scrutinizes state-of-the-art optimization algorithms, and then makes recommendations on how to properly match these problems with effective and practical optimization methods.
We will start by working with unconstrained and constrained one-dimensional problems, move on to consider linear programming, and then address special types of high-dimensional problems, all illustrated with lithographical examples, including mask-inverse lithography (ILT) and SMO. The course will continue with an outline of modern optimization algorithms and explanation of their properties, strengths, weaknesses, and limitations.
View contact details
No SPIE Account? Create one
