Diffractive triangulation of radiative point sources

Abstract

We describe a general method to determine the location of a point source of waves relative to a two-dimensional single-crystalline active pixel detector. Based on the inherent structural sensitivity of crystalline sensor materials, characteristic detector diffraction patterns can be used to triangulate the location of a wave emitter. The principle described here can be applied to various types of waves provided that the detector elements are suitably structured. As a prototypical practical application of the general detection principle, a digital hybrid pixel detector is used to localize a source of electrons for Kikuchi diffraction pattern measurements in the scanning electron microscope. This approach provides a promising alternative method to calibrate Kikuchi patterns for accurate measurements of microstructural crystal orientations, strains, and phase distributions

Refined Calibration Model for Improving the Orientation Precision of Electron Backscatter Diffraction Maps

“…As has been discussed above, the projection center is essentially related to the purely geometrical relationships in the measurement setup. In order to analyze the absolute precision of the projection center, alternative determinations of the projection geometry could use methods which are independent of the observation of any Kikuchi patterns from the sample, such as shadow casting methods [6,15] or single-crystalline detectors like those discussed in [19].…”

“…EBSD is based on the measurement of Kikuchi diffraction patterns in a gnomonic projection [3] on a planar screen placed near the sample, with the position of the SEM beam on the sample determining the center of the projection relative to the detector plane [4]. Because the knowledge of the gnomonic projection center (PC) is necessary to carry out any angular measurements on the detector screen, a key problem for various diffraction methods in the SEM is the determination of the exact position of the electron beam meeting the sample surface, relative to the detector plane [1,2,[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. In addition to EBSD, the technique of electron channeling orientation determination (eCHORD) also requires an accurate knowledge of the incident beam geometry for precise orientation determination when large sample areas are scanned [22,23].…”

Improved EBSD indexation accuracy by considering energy distribution of diffraction patterns

“…Dynamical EBSP simulation proves to have a higher similarity with experimental pattern than kinematic simulations [12]. To achieve the optimization of the projection parameters, many algorithms have been suggested, such as a Nelder-Mead algorithm [13,14,15], cross-correlation with log-polar transform [16], evolution algorithm [17], SNOBFIT algorithm [15], integrated DIC algorithm [18] or non-disclosed ones used in commercial software [19]. IDIC is able to calibrate overlapped EBSPs at grain boundaries, to obtain multiple sets of Euler angles, one set of PC and the contribution ratio for each crystal orientation [20].…”

Improved high-resolution EBSD analyses by correcting radial distortion of electron diffraction patterns

“…The basic idea of the increasingly popular software-based EBSD is to tune the projection parameters (and in particular the three coordinates of the PC) in order to maximize the similarity between experimental and simulated EBSPs, especially the dynamically simulated ones [16]. To match precisely the experimental and simulated patterns, many algorithms have been suggested, such as Nelder-Mead algorithm [17,18,19], cross-correlation with log-polar transform [20], evolution algorithm [21], SNOBFIT algorithm [19], global integrated-DIC (IDIC) algorithm [22] or non-disclosed ones used in commercial software [23].…”