By Peter W. Hawkes
Advances in Imaging & Electron Physics merges long-running serials―Advances in Electronics & Electron Physics and Advances in Optical & Electron Microscopy. The sequence positive aspects prolonged articles at the physics of electron units (especially semiconductor devices), particle optics at low and high energies, microlithography, picture technological know-how and electronic photo processing, electromagnetic wave propagation, electron microscopy, and the computing equipment utilized in a lot of these domains.
- Contributions from prime specialists
- Informs and updates on all of the most modern advancements within the field
Read or Download Advances in imaging and electron physics. Volume 183 PDF
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Additional resources for Advances in imaging and electron physics. Volume 183
F. M. (1960). Wide-band detector for micro-microampere low-energy electron currents. Journal of Scientiﬁc Instruments, 37, 246–248. Fernandez-Varea, J. , & Salvat, F. (2005). Cross sections for electron interactions in condensed matter. Surface and Interface Analysis, 37, 824–832. , & Ikeno, S. (2007). Cathode lens mode of the SEM in materials science applications. Materials Transactions, 48, 944–948. 38 Mohamed M. El-Gomati and Christopher G. H. Walker Furman, M. , & Pivi, M. T. F. (2002). Probabilistic model for the simulation of secondary electron emission.
2008b). If such an oxide layer is followed by the growth of an advantageous carbon layer, one could end up having a MOS Toward Quantitative Scanning Electron Microscopy 35 device, which would react differently under the various experimental conditions of most SEMs and, more interestingly, for various beam currents as well. Given that Chee et al. (2011) can simulate their results using Monte Carlo, then it would be interesting to see how their model copes with the case of a thin metallic ﬁlm covering the surface as investigated by El-Gomati and Wells (2001).
This is a powerful tool for analyzing the stationary phenomena and for computing more advanced signal-processing methods. In this context, the fast Fourier transform has been implemented for digital signal processing, solving the discrete Fourier transform in a very small amount of time Lifermann (1979). The natural space of the analyzed signals is a Hilbert space (Mallat (2008). Figure 1 illustrates the role of the Fourier transform by showing the magnitude of the complex valued function ^f ðnÞ as an example.