Biomedical subjects

S Mil'shtein

Publications and source records attributed to S Mil'shtein.

3 recordsLinked to original sources

PubMed2000

Semiconductor devices "from inside"

Operation of any semiconductor device can be presented by unique configuration of the electrical field (potential) and charge (doping) distribution within the device. More specifically, the status of operation is described by the quasi-Fermi energy (QFE) profile across the device. Visualization of the dynamic operation of the device and quantitative measurements of the QFE profile is provided by differential voltage contrast (DVC), which is a modification of the secondary electron imaging in a scanning electron microscope (SEM). The DVC consists of storing two images of a tested semiconductor device. Exposed to the electron beam is a cross section, for example, of a field effect transistor (FET). The first image, covering the entire inside of the FET from source to drain, is taken when the device is not biased. The second image of the same area is taken when the transistor is biased. The secondary electron signal is enhanced or retarded by actual distribution of a potential across the tested device. Subtraction pixel by pixel of the two carefully aligned images removes morphologic contrast from the screen, takes away surface features and contamination of the sample, and reveals the contribution of the electrical field to the changes of contrast. The calibration procedure allows measurement of the potential distribution with a precision of 0.05 V. The first derivative of a potential profile provides for distribution of the electrical field and the second derivative gives the doping profile across the tested device. A variety of semiconductor devices such as p-n junctions, Zener diodes, MOSFET's, MESFET's, solar cells and optical detectors, quantum well lasers, etc., were tested. Videotaping of the tested devices allows us to observe the changes in the electrical field and charge distribution as the device operates in a wide range of electrical or optical signals.

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PubMedDate not supplied

Microanalysis using secondary electrons in scanning electron microscopy.

A recent study of secondary electron (SE) spectra in an Auger spectrometer demonstrated unique features indicative of the chemical nature of the tested material. The scanning electron microscope (SEM) naturally generates SEs; therefore, in this paper, we combine the concept of using differential voltage contrast (DVC) with SE spectroscopy to identify the chemical nature of a material. It is demonstrated that this method reveals the uniqueness of electron energy distribution in the conduction band of a solid or, what is the same, the uniqueness of a build-up of the outer electron shell system, and avoids errors due to the changes in the angular distribution or yield of the SE in the SEM. A theory of this new microanalytical method is developed. The experimental limitations of the SEM for this type of study are examined as well.

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PubMedDate not supplied

Direct assessment of recombination noise in semiconductors using electron beam-induced conductivity.

The level of internal noise of the transistors, diodes, and other semiconductor components limits the successful design of any low noise electronic system. All types of noise, namely, Johnson, 1/f, and so forth, are generated due to activity of crystalline defects such as vacancies, dislocations, and others. The intensity of the electron scattering and recombination processes, inflicted by defects (traps), controls the level of noise. Dependent on the dynamic operation condition of semiconductor devices, such as external biases and level of current injection, the traps will generate certain type and level of noise. Material growth or device processing technologies could introduce all kind of defects. Therefore, characterization of the semiconductor wafer in the early stages of processing (at least before packaging) could help to predict the level of noise due to the type and density of defects present on the wafer. Sorting out bad semiconductor chips could save money and effort in the radio frequency design of low-noise circuits. This current study focuses on 1/f noise modeling, which involves most powerful generators of noise and linear defects, named dislocations. The study also examines the possibility of assessing this noise by quantitative electron beam-induced conductivity (EBIC) measurements. These defects could be found in the bulk as well as at the epitaxial interfaces of a semiconductor device. The nanoscale size of these defects makes the scanning electron beam an instrument of choice for the proposed study. Conventional EBIC produces images of the defects, where contrast is proportional to the recombination rate at the site of a defect. Since contrast is measured as a fraction of one percent, the relative nature of contract value precludes quantitative measurements of the recombination rate, thus making quantitative assessment of 1/f noise impossible. In our model, using the Boltzman continuity equation, the recombination-generation processes per unit of length of a dislocation was defined for two operational conditions of EBIC, namely, for low and high intensity of an electron beam. The experimental technique of the quantitative measurement of carrier recombination (Mil'shtein 2001) consists of taking two EBIC scans along the selected defect at two different beam intensities, digitally subtracting the first scan from the second one and normalizing the result to the size of the electron range. The value of the recombination rate, extracted from the model, could then be used to predict the level of 1/f noise in the tested semiconductor sample.

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