The collection and analysis of x-rays emitted by samples in electron microscopes is in many ways a dynamic process. Conventional methods of off-line teaching are restricted in their ability to convey this dynamic and interactive nature. The recent developments in multimedia software and the increase in power of desktop systems can be taken advantage of in teaching in this area. Specifically the original AMAS (Australian Microbeam Analysis Society) EDS course notes have been integrated with a range of interactive tutorials and multi-choice assessment using the Macromedia Director 6.0 multimedia authoring software. The ‘Virtual EDS’ software is compatible with the Macintosh, Windows'95, Windows NT and Windows 3.11 platforms, on CD-ROM.

The project is on-going but currently the software contains the full AMAS EDS notes updated as thirteen reference topics and the following four interactive tutorials:

1998 Microbeam Analysis Society (MAS) award winners.

A partnership has developed between the Microscope and Graphic Imaging Center (MAGIC) at California State University, Hayward and Ohlone Community College. The purpose of the collaboration is to develop a program to allow community college students to gain experience in preparing and viewing samples using scanning electron microscopy technology. The learning module involves students from the Ohlone College Biology Majors Program and student mentors from CSUH. An additional component is the introduction of under-represented students into a Biology Fellowship Program in which they also participate in the SEM learning module. Participants for these programs are selected on the basis of their interest and how this experience will benefit them as expressed in a one-page written essay. Ten students are selected to participate in the programs.

The objectives of the learning module are to: 1) learn specimen preparation techniques and develop skills in SEM technology; 2) gain hands-on experience and develop some laboratory skills necessary for effective use of a SEM in studying biological specimens; 3) share the experience gained with peers at their home institution.

1998 Microscopy Society of America (MSA) award winners.

Well it's time again for another edition of Net Notes. This edition is for you biological science technicians out there. Maybe this discussion can speed up cell and bacterial processing for SEM so you can take longer lunches. This discussion is archived in full at the Tips & Tricks site located at www.biotech.ufl.edu/~emcl. Good luck.

In 1996 the DOE formed the Materials Microcharacterization Collaboratory (MMC) to bring together the four DOE-sponsored electron microscope user facilities in one collaboratory. The MMC will bring the microanalysis and microcharacterization tools that are available in national centers to geographically dispersed researchers working in industries, universities, and Government laboratories. It will enable these remote users to share on-line the instrumentation, knowledge and expertise available at the individual facilities making up the collaboratory.

LBNL first demonstrated on-line remote control of a high-voltage TEM from Kansas City in 1995 in a joint project by LBNL computer scientists and NCEM microscopists. The microscope chosen was a 1.5MeV Kratos EM-1500 that is used for in-situ electron microscopy. In the demonstration, a specimen of an Al/Pb alloy was heated and observed, with remote-operator control of heating rate, microscope focus, and stage movement (translation and tilt).

To introduce engineering undergraduates to microstructural characterization in the scanning electron microscope, The Department of Materials Science and Engineering (MS&E) at The University of Michigan has developed the Teaching SEM. This instrument, based on a Philips XL30 SEM and located in the teaching laboratories, may be controlled from a lecture theater or classroom virtually anywhere on the University campus via a combination of the campus computing network and the campus cable television network. The use of the campus cable TV network is a limitation. Many areas of the University have Internet connections, but no cable connections. A number of local schools have expressed an interest in incorporating use of this system into their classes. The current work seeks to eliminate the cable TV network and send both the control and video signals over the Internet.

This list contains brief descriptions of each of the positions known to be open in the Microscopy Society of America (MSA) Placement Office files. Potential employers are urged to use the Placement Office as widely as possible to advertise their needs to MSA members. Likewise, MSA members who are seeking employment in microscopy are urged to register with the Office to receive data on open positions periodically.

The integration of nano-science and technology concepts into upper-division high school and lower-division college curricula will require innovative educational approaches that will help students understand the structures and properties of matter on a scale below 100 nanometers, i.e., the nanoscale. This Interactive Nano-Visualization in Science and Engineering Education (IN-VSEE) project will create a consortium of university and industry researchers, community college and high school science faculty, computer scientists and museum educators with a common vision of creating an interactive World Wide Web (WWW) site to develop a new educational thrust based on remote operation of advanced microscopes and nanofabrication tools coupled to powerful surface characterization methods. The centerpiece of this project is the web-based operation of the revolutionary scanning probe microscope (SPM), which has evolved rapidly into a relatively simple, yet powerful, technique capable of imaging and manipulating materials at resolutions down to the atomic scale.

Following is a list of microscopy-related meetings and courses. The editors would greatly appreciate input to this list via the electronic submission form found in the MSA World-Wide Web page at http://www.msa.microscopy.com/. We will gladly add hypertext links to the notice on the Web and insert a listing of the meeting in the next issue of the Journal. Send comments and questions to Barbara Reine, [email protected] or Nestor Zaluzec, [email protected].

The continuing remarkable progress of computer technology is dramatically changing how electron optical instrumentation is being used. Instead of concentrating on taking just one spectrum or one image at a time, it now has become possible to design complete experiments aimed at solving the problems at hand more rapidly and more directly.

We have designed a PC-based acquisition system that aims to innovate and simplify both TEM and STEM operation. The first advance this system represents is integrated data acquisition from all detectors commonly found on electron microscopes: TV and slow-scan CCD cameras, different flavors of STEM detectors, and EDX, CL, Auger and EELS spectrometers. The new system allows experiments combining microscope control with the acquisition capabilities of all these detectors. The second advance is the implementation of “live” processing. Most common processing tasks can be executed on-the-fly, even at video-rate acquisition speeds.

One of the most difficult problems on the way to sub-Ångstrom resolution at a medium accelerating voltage of about 200 kV, the correction of the spherical aberration, has been solved. Already more than fifty years ago, Scherzer showed that the two major axial aberrations, the chromatic and the spherical aberration, can be corrected by a suitable combination of electrostatic and/or magnetic multipole elements. Due to the availability of high-coherent electron sources with a small relative energy width DE/E the necessity of correcting the chromatic aberration can be avoided.

Our solution for spherical aberration correction follows a suggestion by Rose. It is based on two electromagnetic hexapoles and four additional lenses. The principle by which correction is achieved is based on the fact that the primary aberrations of second order of the first hexapole are compensated by the second hexapole element.

There are three main algorithms for autotuning a transmission electron microscope (TEM), (1) image variance method, (2) tilt-induced image shift (TIS) method, and (3) automated diffractogram analysis method (ADA). In practice, each method has its own advantages and limitations. Therefore it is necessary to obtain a comprehensive understanding of each in order to be able to select the most appropriate one(s).

There are four key elements in any TEM autotuning setup, (1) microscope control by an external computer, for example via the standard RS232 serial port; (2) proper image acquisition device, for example a TV or a slow-scan CCD camera; (3) appropriate software for image analysis, processing, and optimization; (4) a fast computer that is the central control unit in the setup and dictates all the activities and operations.

Acquisition of large dynamic range information is important for optimizing the performance of SEM’s, TEM’s, and other microscopies. The majority of digital imaging performed in desktop publishing and other consumer markets today is limited to 8-bit resolution, and these technologies are often modified for use in electron microscopy (EM). The limitations of these techniques are clearly evident in many EM situations despite the fact that human visual system is not equipped to differentiate more than 2^5 gray levels. The most common case is when a user seeks to view information hidden in both the image's dark levels and in the brightest levels. If multiple images at different detection levels are required despite digital processing then the image information is being limited by the digitization resolution.

Digitization is the process of converting a signal from the analog form that originates from our microscope detectors to a digital form that is suitable for processing within computers.

Color and Color Perception

Accurate color reproduction is an essential component in the effective use of digital imaging techniques in light microscopy. The color reproduction process begins with an understanding that color is the result of three key elements; light, the illuminated object, and the observation method. When light strikes an object, wavelengths may be reflected, absorbed or transmitted. Additionally, the observed colors are strongly influenced by the intensity of the illumination and its spectral content. Colors we think of as “white” can vary significantly in their spectral distribution, e.g., skylight is actually a bluish white while tungsten bulbs produce a yellowish white.

Light waves that reach the eye stimulate a complex process that is not yet fully understood. Within the retina, three different types of cones respond to color hues and brightness while rods sense only brightness.

Image analysis is the process of quantifying some aspect of an image—its particle size distribution, for example. Manual methods were in use long before computers made image analysis much faster and more reproducible. Linear measurements of diameter, point counting to measure volume fraction, and intercept counting to determine grain size have been used for over 100 years. Automatic image analysis (AIA), however, can make more measurements, and even calculate derived measurements, such as aspect ratio or circularity. AIA of a specimen or micrograph, of course, is only as good as the contrast mechanism used, so the imaging signal must be chosen carefully to reveal to the computer what is to be measured. Obtaining sufficient contrast is often the limiting task.

Once an imaging signal is chosen and the digital resolution set, the computer can analyze the image. The feature descriptors can be generic:

Accurate characterization of electron diffraction patterns can be tedious, which encourages development of computer assisted tools and methods. We developed a spot measurement tool to characterize rapidly arrays of diffraction spots that are characteristic of a single crystal, and to measure precisely the d-spacing values for individual spots. The spot tool determines these vectors for averaged measurements from many spots in a digital image of the diffraction pattern. Previously we developed automated methods for spot pattern analysis. Why make an operator-assisted tool? This tool is faster than either our automated or entirely manual methods, and it allows assessment of the quality of the data at the beginning of the analysis.

It is easy to see regular patterns of spots in a zone axis diffraction pattern (Fig. 1.1). An operator guides the initial calculations by adjusting an array of circles to approximately cover the spots in the pattern to be analyzed.

Mathematical representation of particle orientation and shape can show quantitative differences in particle morphology and microstructures of ceramic green bodies with apparently equiaxed powders. In this work, fourier descriptors and moment invariants were used to quantify the shape of ceramic particles and identify their orientation. Edges constitute a significant portion of the information contained in these images, and hence edge detection forms an important issue in these image processing algorithms.

A Field Emission Scanning Electron Microscope (FESEM, Leo 982) was used to collect images of various ceramic green bodies in order to assess the ceramic particle shape and orientation. The images were collected and displayed as rectangular pixels on the microscope monitor which were then stored as square pixels (square-pixel-interpolation). Application of various edge detection algorithms on the stored images show strong bias to edges in the direction perpendicular to the scanning direction.

In designing automated systems for interpretation of micrographs, it is often the goal to separate and discern various objects within the image data. After segmentation, measurements of the objects, called features, can then be calculated and used for process or statistical analysis. Simple segmentation schemes based on single threshold operations, often lack the sophistication to deal with intricate or subtle details of the image data, or require user intervention in the threshold selection process. This talk will present and discuss advanced techniques which adapt to the data, and which can operate autonomously without human supervision.

Segmentation is a process which transforms pixel based image data into symbolic descriptors representing groups of pixel elements. These descriptors are called objects and take the form of lines, regions, polygons, points, windows of interests, or other unique representations. Most laboratory image analysis software packages utilize segmentation schemes based on the principle of intensity analysis.

Micro-graphs acquired using optical or electron microscopes reveal information on a local scale. When a sample is not homogeneous at the scale of the image, it may be necessary to view the sample at a magnification lower than that available by the instrument. Montages of micro-graphs can be constructed through the following steps: acquisition of individual images, stitching individual images into a single image (a montage), and producing the final exhibit(s). Performing these steps has traditionally required careful stage and illumination control during acquisition, dodging during printing, and hours with scissors and glue-pot during paste-up. Because this procedure is labor intensive, the creation of montages was limited to only the most important or critical situations. Digital microscopy, image processing software, and Web-enabled multi-media applications have reduced the barriers for creation of montages and provided for new display modes, thereby stimulating a revival of the use of montages as an enhanced presentation mode for technical data.