Higher Yield and Quality through Particle Identification

The sources of particulate contamination are often not easy to identify. To control manufacturing processes, the measurement of particle concentration and size is necessary and has been routinely performed for many years. Technology has been developed to increase the information available for the immediate evaluation of particles. The method analyzes airborne particles or particles isolated from liquids automatically according to their number, size, and chemical composition.1,2 The analysis of thousands of particles enables users to locate the major sources of contamination in various manufacturing processes. The analytical tool provides rapid determination of particulate contamination, thus allowing for a quick, efficient response. Over time, the ability to compare analytical result data sets assists in detecting trends and implementing the appropriate quality management. Routine use of the technology contributes to ongoing supervision and optimization of production processes. This study reports on the use of the technology to analyze foreign particles associated with oral, inhalable, and nasal drug products (OINDP), parenterals, and coronary stents. Applications for troubleshooting and identifying latent contamination sources are discussed through several examples.

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Weak Beam Imaging and Diffraction Studies of Stacking Faults in Silicon

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100092918 ◽

1976 ◽

Vol 34 ◽

pp. 590-591

Author(s):

T. Y. Tan ◽

W. K. Tice

Keyword(s):

Fast Neutron ◽

Rapid Determination ◽

Stacking Faults ◽

Imaging Method ◽

Large Reduction ◽

Dislocation Loops ◽

Fringe Spacing ◽

Weak Beam ◽

Kinematical Theory

In studying ion implanted semiconductors and fast neutron irradiated metals, the need for characterizing small dislocation loops having diameters of a few hundred angstrom units usually arises. The weak beam imaging method is a powerful technique for analyzing these loops. Because of the large reduction in stacking fault (SF) fringe spacing at large sg, this method allows for a rapid determination of whether the loop is faulted, and, hence, whether it is a perfect or a Frank partial loop. This method was first used by Bicknell to image small faulted loops in boron implanted silicon. He explained the fringe spacing by kinematical theory, i.e., ≃l/(Sg) in the fault fringe in depth oscillation. The fault image contrast formation mechanism is, however, really more complicated.

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Direct phase determination in electron crystallography: small organic molecules

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100130468 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1166-1167

Author(s):

Douglas L. Dorset

Keyword(s):

Organic Molecules ◽

Data Sets ◽

Temperature Structure ◽

3D Analysis ◽

Intensity Data ◽

Electron Crystallography ◽

Phase Determination ◽

Measured Intensity ◽

3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

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