No abstract

The resonance ultrasonic vibrations (RUV) technique is adapted for non-destructive crack detection in full-size silicon wafers for solar cells. The RUV methodology relies on deviation of the frequency response curve of a wafer, ultrasonically stimulated via vacuum coupled piezoelectric transducer, with a periphery crack versus regular non-cracked wafers as detected by a periphery mounted acoustic probe. Crack detection is illustrated on a set of cast wafers. We performed vibration mode identification on square-shaped production-grade Si wafers and confirmed by finite element analyses. The modelling was accomplished for the different modes of the resonance vibrations of a wafer with a periphery crack to assess the sensitivity of the RUV method relative to crack length and crack location.

A three-dimensional holographic image is deteriorated due to quantization of the phase in the hologram. As in two-dimensional Fourier holograms, the deterioration is exhibited as a superposition of false images. However, in the three-dimensional case, the false images fall at depth positions other than the plane of the image to which they correspond. If far out of focus, these false images are harmless.

Recent developments in liquid crystal display (LCD) technology suggest that this technology will replace the cathode ray tube (CRT) as the most popular softcopy display technology in the medical arena. However, LCDs are far from ideal for medical imaging. One of the principal problems they possess is spatial noise contamination, which requires accurate characterization and appropriate compensation before LCD images can be effectively utilized for reliable diagnosis. This paper presents some work we have conducted recently on characterization of spatial noise of high resolution LCDs. The primary purpose of this work is to explore the properties of spatial noise and propose a method to reduce it. A high quality CCD camera was used for physical evaluation. Spatial noise properties were analyzed and estimated from the camera images via signal modeling and processing. A noise compensation algorithm based on error diffusion was developed to process images before they were displayed. Results shown in this paper suggest that LCD spatial noise can be effectively reduced via appropriate processing.