Monte Carlo simulations completed for sem resolution study. (General Developments).In June, a NIST (National Institute of Standards & Technology, Washington, DC, www.nist.gov) The standards-defining agency of the U.S. government, formerly the National Bureau of Standards. It is one of three agencies that fall under the Technology Administration (www.technology. scientist completed Monte Carlo simulations Monte Carlo Simulation A problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables. of scanning electron microscope scan·ning electron microscope n. Abbr. SEM An electron microscope that forms a three-dimensional image on a cathode-ray tube by moving a beam of focused electrons across an object and reading both the electrons scattered by the object and (SEM) imaging of resist lines on silicon. These represent the first part of a study being performed at the behest of International SEMATECH SEMATECH Semiconductor Manufacturing Technology on the limits imposed by noise on the ability of the SEM to resolve differences between widths of lines. In the simulations, the samples are 800 nm of PAR 810 resist on l0 nm of BARC (bottom anti-reflection coating) on thick polycrystalline silicon Polycrystalline silicon or polysilicon or poly-Si or simply poly (in context) is a material consisting of multiple small silicon crystals. Polycrystalline silicon can be one of the purest elements in the world; it may be as much as 99.9999999+% pure. . The resist lines edge angle (relative to the plane of the substrate) was varied from 81[degrees] to 93[degrees], simulating a range of possible manufacturing process variation. The effect of the SEMs finite depth of field was modeled by varying the convergence angle of the incident electron beam. These results will form the inputs for the next stage of the study, in which simulated noise will be added to the images and a number of different algorithms will be employed to determine edge positions from these simulated noisy images. By comparing the edge positions so determined with the known true edge positions, the accuracy and repeatability of the various edge detection algorithms can be determined as a function of edge shape and instrument depth of field. CONTACT: John Villarrubia, (301) 975-3958; john.villarrubia@nist.gov. |
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