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Ordered carbon nanotube arrays fabricated on alumina templates were studied using inelastic laser light scattering spectroscopy. Multiple peaks were observed in spectra from an array where the nanotubes extend ∼150nm beyond the template surface. These protruding segments are modeled as hollow cylinders clamped at one end. Good agreement is obtained between the predicted vibrational frequencies and the experimental peak frequency shifts. The peaks are thus attributed to the transverse, longitudinal, and torsional vibrations of the protruding nanotube segments. This assignment yields values of 26 and 20GPa for the Young’s and shear moduli of the nanotubes, respectively.

In the early development stage of 32nm processes, identifying and isolating systematic defects is critical to understanding the issues related to design and process interactions. Conventional inspection methodologies using random review sampling on large defect populations do not provide the information required to take accurate and quick corrective action. This paper demonstrates the successful identification and isolation of systematic defects using a novel methodology that combines Design Based Binning (DBB) and inline Defect Organizer (iDO). This new method of integrating design and defect data produced actionable inspection data, resulting in fewer mask revisions and reduced device development time. INTRODUCTIONEngineers must balance design margins and process windows, while achieving fast development times. In the early development stage, identifying systematic defects accurately and quickly is critical in order to minimize cost and shorten the development cycle. Bright field inspectors are often used to help identify integration defects, but high sensitivity inspections can produce very large defect populations that contain both random and systematic defect types. Limited review sampling on these high defect counts prevents the effective separation of design or processrelated defects from non-relevant defect types. Thus, these conventional inspection methods produce an incomplete picture of issues related to process and design interactions, making it difficult, if not impossible, for engineers to take effective corrective action. DBB is a new technology that classifies defects into groups based on design background [1,2]. In addition, defect critical index (DCI) can be extracted to describe what the impact of defect is [3], while iDO uses design and defect attributes to identify and separate different classes of defects. Using these technologies, systematic defects can be identified and separated from the overall defect population, resulting in improved yield relevance and faster solution of production integration issues. For example, the defect population can be

Increasing inspection sensitivity may be necessary for capturing the smaller defects of interest (DOI) dictated by reduced minimum design features. Unfortunately, higher inspection sensitivity can result in a greater percentage of non-DOI or nuisance defect types during inline monitoring in a mass production environment. Due to the time and effort required, review sampling is usually limited to 50 to 100 defects per wafer. Determining how to select and identify critical defect types under very low sampling rate conditions, so that more yield-relevant defect Paretos can be created after SEM review, has become very important. By associating GDS clip (design layout) information with every defect, and including defect attributes such as size and brightness, a new methodology called Defect Criticality Index (DCI) has demonstrated improved DOI sampling rates.

Brillouin light scattering spectroscopy was used to probe porous silicon carbide films formed from p-type 6H crystalline silicon carbide. The porosities of the films ranged from 30% to 58%. Surface and bulk acoustic wave velocities were measured and compared with those calculated from the Mori-Tanaka acoustic effective medium model. Qualitative agreement is obtained between the experimentally determined velocities and those predicted by Mori-Tanaka acoustic effective medium models with spherical pores and, in the case of surface acoustic waves, also with prolate spheroidal pores with shape factor equal to 0.2. The model demonstrates the importance of morphology in determining the behavior of acoustic waves in a porous material.