Development of the optical non-destructive method and related experimental setup allowing interstitial oxygen-in-silicon "mapping" when doing in-process wafer control are described. Scanning translucent IR microscope principle has been used, in which a specific radiation source has been implemented-a solid-state tunable laser diode (TLD) on PbS-heterojunctions. This light source possesses a number of very useful features (small radiation-body size, very high spectral selectivity, high accuracy of single-mode positioning and fast mode-to-mode switching), which, in combination, allow building-up an efficient measurement procedure. Particularly, TLD allows implementation a new method enabling strong suppression of undesired interference effect of multiple beams reflected from front and back wafer's surfaces. It is shown that, when implementing double-wavelength scan procedure, not only oxygen concentration map may be derived from the data, but the info about the wafer thickness variations in the scanned area may be obtained simultaneously. The theoretical estimations are presented of the attainable limits of spatial resolution, concentration sensitivity and scan rates. The experimental setup is described realizing the method; experimental data are presented obtained by the new method demonstrating good agreement with the integrated values obtained by the standard method while possessing much better spatial resolution (~90..100μm for the present). Further improvements in the method’s parameters are discussed, as well as the perspectives for the method to be used in electronic industry.
Currently, the commonly used method for determination of interstitial O-in-Si concentration, Nox, which is responsible for defect formation in very different types of semiconductor devices, is measuring optical transmission spectra of silicon wafers in the 8 to 11 μm band. The Nox value is extracted from the experimental data by use of standardized algorithms assuming quasi-continuous sequence of spectral transmission samples are available. According to USA standard (ASTM F951-96) such a procedure is assumed to be applied to the separate wafer’s area regions with the diameter of about 7 mm. However, the very much better spatial resolution (up to 30-50 μm is desired under the condition of progressive decreasing of basic element’s characteristic size. To do this, one cannot use the standard algorithms assuming quasi-continuous sequence of spectral samples being available in relatively wide (~3 μm spectral band, because of unrealistic times the measurements requires for. For to choose more economical algorithm of extracting the No value we have compared several proposed calculation methods, which are based upon moderate numbers of spectral samples. As the input test data set for the calculations, the series of experimental samples were taken with the step in wavelength of 0.05 μm obtained on the silicon wafers of different thickness (0.4-2 mm) and of various Nox. The results show that the algorithms using small number of samples (one or two), being optimized properly, do not yields to the standard time-consuming procedure.
Under the today’s tendency of progressive growth of integration level and diminishing of the basic element size of microelectronic devices, the significance of control of spatial distribution of defect-inducing impurities during device processing treatments increases. One of the most important impurities for silicon microelectronics is oxygen, which already presents in the initial Czochralski-grown silicon. Existing standard optical methods of measuring interstitial O-in-Si content based on analysis of silicon wafer’s transmission spectra on the IR optical band of ~ 9 μm doesn’t provide the desired degree of spatial resolution. The purpose of this work is to modify measuring method in such a way to make it possible for one to obtain, in relatively fast manner, oxygen distribution “map” over the wafer’s area, with spatial resolution up to 30..50 μm. The work describes the approach to measuring setup construction, which provides oxygen distribution control in silicon wafers containing O in concentration lying between 1017...3*1018 cm3 with the accuracy of 5% and with the above localization degree. Different realizations of the optical source, projection optics, detector and signal processing system are discussed, and the best choice is grounded. Presented are the technical estimations showing the evidence for the measuring setup to provide the desired features when tunable laser diode is used as a light source along with the special parabolic collimator, cylindrical projection optics and commercially available time-delay-and-integration CMT LWIR detectors.
A program model and relative software tool has been developed allowing to simulate transformations of different physical nature the initial image undergo while passing through electro-optical path of IR TDI system. The program consists of appropriate successively processed units, considering influence of atmosphere, optics, scanning, photodetector (PD) and multiplexer, on initial thermal image. The developed software is intended to be an everyday-practice focal plane arrays (FPAs) engineer's tool for optimizing PD and multiplexer structure and tradeoff analysis. In addition, the software was developed as a first part of more general program now under design, which allows one to estimate the effectiveness of different methods and algorithms of image reconstruction from TDI-rows output data. The software is especially useful in the cases of relatively complex arrangement of photodetector apertures, and/or when image motion trajectory in the focal plane is non-ideal (e.g., skewed with respect to its normal direction, or waved-form), which are the cases in practical systems. The main features of the designed model are described and some advantages of the program are discussed. The preliminary results on the image processing in practical middle-wave infrared (MWIR) TDI system are given demonstrating the influence of various system parameters on final image quality and confirming the validity of the model.
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