An improved method for particle measurement based on diffraction and pattern recognition

Author(s):  
Ma Fengying ◽  
Ding Rundong ◽  
Hao Ming
Author(s):  
Ling Ma ◽  
Yumin Liu ◽  
Huiqin Jiang ◽  
Zhongyong Wang ◽  
Haofei Zhou

Author(s):  
G.Y. Fan ◽  
J.M. Cowley

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.


Author(s):  
E.A. Fischione ◽  
P.E. Fischione ◽  
J.J. Haugh ◽  
M.G. Burke

A common requirement for both Atom Probe Field-Ion Microscopy (APFIM) and Scanning Tunnelling Microscopy (STM) is a sharp pointed tip for use as either the specimen (APFIM) or the probe (STM). Traditionally, tips have been prepared by either chemical or electropolishing techniques. Recently, ion-milling has been successfully employed in the production of APFIM tips [1]. Conventional electropolishing techniques are applicable to a wide variety of metals, but generally require careful manual adjustments during the polishing process and may also be time-consuming. In order to reduce the time and effort involved in the preparation process, a compact, self-contained polishing unit has been developed. This system is based upon the conventional two-stage electropolishing technique in which the specimen/tip blank is first locally thinned or “necked”, and subsequently electropolished until separation occurs.[2,3] The result of this process is the production of two APFIM or STM tips. A mechanized polishing unit that provides these functions while automatically maintaining alignment has been designed and developed.


Author(s):  
J. C. Fanning ◽  
J. F. White ◽  
R. Polewski ◽  
E. G. Cleary

Elastic tissue is an important component of the walls of arteries and veins, of skin, of the lungs and in lesser amounts, of many other tissues. It is responsible for the rubber-like properties of the arteries and for the normal texture of young skin. It undergoes changes in a number of important diseases such as atherosclerosis and emphysema and on exposure of skin to sunlight.We have recently described methods for the localizationof elastic tissue components in normal animal and human tissues. In the study of developing and diseased tissues it is often not possible to obtain samples which have been optimally prepared for immuno-electron microscopy. Sometimes there is also a need to examine retrospectively samples collected some years previously. We have therefore developed modifications to our published methods to allow examination of human and animal tissue samples obtained at surgery or during post mortem which have subsequently been: 1. stored frozen at -35° or -70°C for biochemical examination; 2.


Author(s):  
L. Fei ◽  
P. Fraundorf

Interface structure is of major interest in microscopy. With high resolution transmission electron microscopes (TEMs) and scanning probe microscopes, it is possible to reveal structure of interfaces in unit cells, in some cases with atomic resolution. A. Ourmazd et al. proposed quantifying such observations by using vector pattern recognition to map chemical composition changes across the interface in TEM images with unit cell resolution. The sensitivity of the mapping process, however, is limited by the repeatability of unit cell images of perfect crystal, and hence by the amount of delocalized noise, e.g. due to ion milling or beam radiation damage. Bayesian removal of noise, based on statistical inference, can be used to reduce the amount of non-periodic noise in images after acquisition. The basic principle of Bayesian phase-model background subtraction, according to our previous study, is that the optimum (rms error minimizing strategy) Fourier phases of the noise can be obtained provided the amplitudes of the noise is given, while the noise amplitude can often be estimated from the image itself.


1989 ◽  
Vol 34 (11) ◽  
pp. 988-989
Author(s):  
Erwin M. Segal
Keyword(s):  

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