Improved near surface heavy impurity detection by a novel charged particle energy filter technique

As the typical feature size of silicon integrated circuits, such as in VLSI technology, has become smaller, the surface cleanliness of silicon wafers has become more important. Hence, detection of trace impurities introduced during the processing steps is essential. A novel technique, consisting of a ``Charged Particle Energy Filter (CPEF)`` used in the path of the scattered helium ions in the conventional Rutherford Backscattering geometry, is proposed and its merits and limitations are discussed. In this technique, an electric field is applied across a pair of plates placed before the detector so that backscattered particles of only a selected energy range go through slits to strike the detector. This can be used to filter out particles from the lighter substrate atoms and thus reduce pulse pileup in the region of the impurity signal. The feasibility of this scheme was studied with silicon wafers implanted with 1{times}10{sup 14} and 1{times}10{sup 13} {sup 54}Fe/cm{sup 2} at an energy of 35 keV, and a 0.5 MeV He{sup +} analysis beam. It was found that the backscattered ion signals from the Si atoms can be reduced by more than three orders of magnitude. This suggests the detection limit for contaminants can be improved by at least two orders of magnitude compared to the conventional Rutherford Backscattering technique. This technique can be incorporated in 200--300 kV ion implanters for monitoring of surface contaminants in samples prior to implantation

Robust image adaptive steganography using integer wavelets

Information-Theoretic Analysis for Parallel Gaussian Models of Images prescribe embedding the secret data in low and mid frequency regions of image which have large energies. In this paper, we propose a novel steganographic scheme called Robust Image Adaptive Steganography using Integer Wavelet Transform(RIASlWT), which is a practical realization of these prescriptions. Using this scheme we can hide large volumes of data without causing any perceptual degradation of the cover image. The scheme embeds the payload in every non-overlapping 4x4 blocks of the low frequency band of cover image, two pixels at a time, one on either sides of the principal diagonal. Tests for the similarity between the Condition Number of the cover image and the stego image are done for further embedding. We also perform cover image adjustment before embedding the payload in order to ensure lossless recovery. Embedding done in the low frequency bands ensures robustness against attacks such as compression and filtering. Experimental results show better trade off between Visual perceptivity and capacity compared to the existing algorithms