Saeed Bagheri

Experimental result and simulation analysis for the use of pixelated illumination from source mask optimization for 22nm logic lithography process

We demonstrate experimentally for the first time the feasibility of applying SMO technology using pixelated illumination. Wafer images of SRAM contact holes were obtained to confirm the feasibility of using SMO for 22nm node lithography. There are still challenges in other areas of SMO integration such as mask build, mask inspection and repair, process modeling, full chip design issues and pixelated illumination, which is the emphasis in this paper. In this first attempt we successfully designed a manufacturable pixelated source and had it fabricated and installed in an exposure tool. The printing result is satisfactory, although there are still some deviations of the wafer image from simulation prediction. Further experiment and modeling of the impact of errors in source design and manufacturing will proceed in more detail. We believe that by tightening all kind of specification and optimizing all procedures will make pixelated illumination a viable technology for 22nm or beyond. Publishers Note: The author listing for this paper has been updated to include Carsten Russ. The PDF has been updated to reflect this change.

Extension of depth of field using amplitude and phase modulation of the pupil function

We analyze the extension of depth of field using both amplitude and phase modulation of the pupil function. In particular, we discuss the advantages and disadvantages of each approach and establish the range of applicability of each method based on the range of spatial frequencies of interest in the imaging system. To the best of our knowledge, this is the first such report on the range of applicability of amplitude and phase modulation to extend the depth of field.

Silicon-on-insulator mode-selective add-drop unit for on-chip mode-division multiplexing

A broadband, low-crosstalk, mode-selective add-drop multiplexer using quasi phase-matching and staged coupling is presented. This ultra-compact device can be used to enable mode-division multiplexing for further increasing the aggregate bandwidth of on-chip optical interconnects.

Benefits and trade-offs of global source optimization in optical lithography

Source optimization in optical lithography has been the subject of increased exploration in recent years [1-4], resulting in the development of multiple techniques including global optimization of process window [4]. The performance advantages of source optimization have been demonstrated through theory, simulation, and experiment. This paper will emphasize global optimization of sources over multiple patterns, e.g. co-optimization of critical SRAM cells and the critical pitches of random logic, and implement global source optimization into current resolution enhancement techniques (RETs). The effect on optimal source due to considering multiple patterns is investigated. We demonstrate that optimal source for limited patterns does work for a large clip of layout. Through theoretical analysis and simulations, we explain that only critical patterns and/or critical combinations of patterns determine the final optimal source; for example those patterns that contain constraints which are active in the solution. Furthermore, we illustrate, through theory and simulation, that pixelated sources have better performance than generic sources and that in general it is impossible for generic sources to construct a truly optimal solution. Sensitivity, tool matching, and lens heating issues for pixelated sources are also discussed in this paper. Finally, we use a RETs example with wafer data to demonstrate the benefits of global source optimization.

Analytical optical solution of the extension of the depth of field using cubic-phase wavefront coding. Part II. Design and optimization of the cubic phase

In this paper we use our derived approximate representation of the modulation transfer function to analytically solve the problem of the extension of the depth of field for two cases of interest: uniform quality imaging and task-based imaging. We derive the optimal result for each case as a function of the problem specifications. We also compare the two different imaging cases and discuss the advantages of using our optimization approach for each case. We also show how the analytical solutions given in this paper can be used as a convenient design tool as opposed to previous lengthy numerical optimizations.

Signal-to-noise-ratio limit to the depth-of-field extension for imaging systems with an arbitrary pupil function

We discuss the limit of the depth-of-field (DOF) extension for an imaging system using aspheric surfaces. In particular we consider an imaging system with an arbitrary pupil function and present the rigorous tradeoff between the DOF of the system and the spectral signal-to-noise ratio (SNR) over an extended DOF, to our knowledge for the first time. In doing so we use the relation between the conservation of ambiguity and modulation-transfer function (MTF) on one hand and the relation between the spectral SNR and MTF on the other. Using this, we rigorously derive the expression for an upper bound for the minimum spectral SNR, i.e., the limit of spectral SNR improvement. This leads to the introduction of our spectral SNR conservation principle. We also draw the relation between our result and the conservation of brightness theorem and establish that our result is the spectral version of the brightness conservation theorem.

Three-dimensional resolvability in an integral imaging system

The concept of three-dimensional (3D) resolvability of an integral imaging system is thoroughly investigated in this research. The general concept of 3D resolution fails to describe the 3D discrimination completely. Then the concepts of the depth-resolution plane and lateral-resolution plane are introduced to show the difference between the conventional 3D spatial resolution and the newly introduced 3D resolvability. Therefore, the different properties of these planes for differentiating lateral spatial variations and axial variations are analyzed in this paper. The theoretical statements are demonstrated experimentally.

Risk adjustment of patient expenditures: A big data analytics approach

For healthcare applications, voluminous patient data contain rich and meaningful insights that can be revealed using advanced machine learning algorithms. However, the volume and velocity of such high dimensional data requires new big data analytics framework where traditional machine learning tools cannot be applied directly. In this paper, we introduce our proof-of-concept big data analytics framework for developing risk adjustment model of patient expenditures, which uses the “divide and conquer” strategy to exploit the big-yet-rich data to improve the model accuracy. We leverage the distributed computing platform, e.g., MapReduce, to implement advanced machine learning algorithms on our data set. In specific, random forest regression algorithm, which is suitable for high dimensional healthcare data, is applied to improve the accuracy of our predictive model. Our proof-of-concept framework demonstrates the effectiveness of predictive analytics using random forest algorithm as well as the efficiency of the distributed computing platform.

Agility of Enterprise Operations across Distributed Organizations: A Model of Cross Enterprise Collaboration

We discuss the need for agility of business operations in a collaborative services ecosystem of partners and providers, and present a new system architecture for cross collaboration among multiple service enterprises. We demonstrate the importance and inevitability of such collaboration along with challenges in its proper realization through several real-life examples taken from different business domains. We then show that these challenges are rooted in two key factors: unpredictability and responsiveness; agility enables optimal response to unpredictable events. The key contribution of this manuscript is the presentation of a new model, centered on the modeling of work-asa-service (WaaS) and an intelligent hub for coordinating cross enterprise collaboration. This hub is constructed in a manner intended to directly identify and solve the two key fundamental challenges of cross enterprise collaboration. As such, we expect it to outperform other means of collaboration across service providers. We demonstrate the potential for such performance using field examples.

Demonstrating the benefits of source-mask optimization and enabling technologies through experiment and simulations

In recent years the potential of Source-Mask Optimization (SMO) as an enabling technology for 22nm-and-beyond lithography has been explored and documented in the literature.1-5 It has been shown that intensive optimization of the fundamental degrees of freedom in the optical system allows for the creation of non-intuitive solutions in both the mask and the source, which leads to improved lithographic performance. These efforts have driven the need for improved controllability in illumination5-7 and have pushed the required optimization performance of mask design.8, 9 This paper will present recent experimental evidence of the performance advantage gained by intensive optimization, and enabling technologies like pixelated illumination. Controllable pixelated illumination opens up new regimes in control of proximity effects,1, 6, 7 and we will show corresponding examples of improved through-pitch performance in 22nm Resolution Enhancement Technique (RET). Simulation results will back-up the experimental results and detail the ability of SMO to drive exposure-count reduction, as well as a reduction in process variation due to critical factors such as Line Edge Roughness (LER), Mask Error Enhancement Factor (MEEF), and the Electromagnetic Field (EMF) effect. The benefits of running intensive optimization with both source and mask variables jointly has been previously discussed.1-3 This paper will build on these results by demonstrating large-scale jointly-optimized source/mask solutions and their impact on design-rule enumerated designs.