The ability to fabricate defect-free mask blanks is a well-recognized challenge in enabling extreme ultraviolet lithography (EUVL) for semiconductor manufacturing. Both the specification and reduction of defects necessitate the understanding of their printability and how they are generated and grow during Mo-Si multilayer (ML) deposition. A ML phase defect can be depicted by its topographical profile on the surface as either a bump or pit, which is then characterized by height or depth and width. The complexity of such seemingly simple phase defects lies in the many ways they can be generated and the difficulties of measuring their physical shape/size and optical effects on printability. An effective way to study phase defects is to use a programmed defect mask (PDM) as 'model' test sample where the defects are produced with controlled growth on a ML blank and accurate placement in varying proximity to absorber patterns on the mask. This paper describes our recent study of ML phase defect printability with resist data from exposures of a ML PDM on the EUV micro-exposure tool (MET, 5X reduction with 0.3NA).

We present a collection of algorithms which utilizedimensional reduction to perform mesh refinement and study possiblysingular solutions of time-dependent partial differential equations. Thealgorithms are inspired by constructions used in statistical mechanics toevaluate the properties of a system near a critical point. The firstalgorithm allows the accurate determination of the time of occurrence ofa possible singularity. The second algorithm is an adaptive meshrefinement scheme which can be used to approach efficiently the possiblesingularity. Finally, the third algorithm uses the second algorithm untilthe available resolution is exhausted (as we approach the possiblesingularity) and then switches to a dimensionally reduced model which,when accurate, can follow faithfully the solution beyond the time ofoccurrence of the purported singularity. An accurate dimensionallyreduced model should dissipate energy at the right rate. We construct twovariants of each algorithm. The first variant assumes that we have actualknowledge of the reduced model. The second variant assumes that we knowthe form of the reduced model, i.e., the terms appearing in the reducedmodel, but not necessarily their coefficients. In this case, we alsoprovide a way of determining the coefficients. We present numericalresults for the Burgers equation with zero and nonzero viscosity toillustrate the use of the algorithms.

This study was conducted to evaluate the technical feasibility of using pressurized oxyfuel, the ThermoEnergy Integrated Power System (TIPS), to recover energy from biomass. The study was focused on two fronts—computer simulation of the TIPS plant and corrosion testing to determine the best materials of construction for the critical heat exchanger components of the process. The goals were to demonstrate that a successful strategy of applying the TIPS process to wood waste could be achieved. To fully investigate the technical and economic benefits of using TIPS, it was necessary to model a conventional air-fired biomass power plant for comparison purposes. The TIPS process recovers and utilizes the latent heat of vaporization of water entrained in the fuel or produced during combustion. This latent heat energy is unavailable in the ambient processes. An average composition of wood waste based on data from the Pacific Northwest, Pacific Southwest, and the South was used for the study. The high moisture content of wood waste is a major advantage of the TIPS process. The process can utilize the higher heating value of the fuel by condensing most of the water vapor in the flue gas and making the flue gas a useful source of …