The electron backscattering factor was measured from 24 different elements at low primary beam energy (250-5,000 eV). The results were compared with Monte Carlo simulations from a variety of freely available programs and an in-house developed program. The results suggest that a thin film of oxide can modify the backscattering factor at low primary energy. In addition, a number of problems have been identified with the freely available programs.

INTRODUCTIONIt is now established that the spatial resolution of the scanning Auger electron microscope (SAM)$ is governed by the diameter of the incident probe for a flat solid sample containing a sharp chemical edge in its surface. El Gomati and Prutton'.2 studied the effects of energetically back-scattered electrons on the spatial resolution of SAM. They defined the distance d , , between two points on the Auger line scan corresponding to 25% and 75% of the maximum Auger signal as an acceptable resolution criteria for SAM. Their finding was that, for normal incidence onto a flat surface, d50 will be given by d,, = 1.25ro for a substrate with Auger back-scattering factor r and a beam with full width at half maximum of o. Away from normal incidence additional factors modifying d 5 0 are the angle of incidence itself, the direction of scanning with respect to the orientation of the chemical boundary and the beam energy.Another theoretical development was given by Cazaux3 who estimated the SAM resolution for a sharp chemical edge within a flat, thin film on a substrate. He found that by incorporating functions describing the 9: Invited paper presented at the Quantitative Surface Analysis Experimentally, Janssen and Venables4 reported Auger line scans of Ag thin films in situ evaporated on a W substrate. Their results confirmed many of the theoretical predictions and the experimental geometry was later simulated using Monte Carlo techniques by El Gomati et aL5 and good agreement was found with the experimental data.Although there are many practical examples of flat chemically heterogeneous surfaces that a SAM can be used to study, it is true to say that situations where the chemical variations are accompanied with changes in surface topography are very common. For example, raised metallization tracks on Si are frequently investigated in the semiconductor industry. In metallurgical applications one is often forced to examine in situ fractured surfaces or superalloys which have been preferentially etched to enhance the surface contrast in the SEM.6 With such practical surfaces it is important to explore ways of separating the effects of varying surface chemical composition from those of artefacts due to the topography.Shimizu et aL7 have reported Monte Carlo simulations showing the enhancement of the Auger signal from a topographical edge. Their results showed an increase of about 50% in the height of the A1 LVV Auger peak over its size from a bulk Al specimen when an incident beam struck an A1 overlayer near to its edge. This situation was for a 10 keV primary electron beam at normal incidence. They also reported an experiment on A1 overlayers on Si with primary energies of about 1.5 keV where an edge enhancement of about 20% was observed. They gave no details about the A1 overlayer thickness in either simulation or As well as modelling the overlayer signal Tuppen and Davies' included in their Monte Carlo simulations the effects of the edge on the Auger signal from the substrate. They reported the case of an edge to...

The power law form of the secondary electron cascade from electron bombarded solids first suggested by Sickafus is explored both theoretically and experimentally. Backgrounds of the form AE-" are shown to result from a range of different theoretical models of the electron-solid interaction in which generation of fast secondaries by electron Compton scattering and transport to the surface are treated separately. The precise value of the exponent m is seen to depend upon the balance between elastic scattering strength and the energy dependence of the inelastic mean free path.The experimental results for eight different samples with atomic numbers between 6 and 78 are reported. The constant A appears to be related to the number density of valence band electrons. The values of m fall within the range predicted by the theoretical arguments. The generality of the form AE-" to many materials is useful for the estimation of both the Auger back-scattering co-eficient and the energy dependence of the inelastic mean free path from measurement of the parameters A and m.

Summary:The main features of a three-dimensional (3-D) Monte Carlo software system (Mc3D), designed for the simulation of electron scattering and image contrast in a scanning electron microscope, are reported. Before simulating electron trajectories in the sample, impingement of the incident electron beam is described by introducing the idea of a virtual scan path in 3-D space. A general and concise algorithm is given for simulating the intersection of electron trajectories leaving the sample onto multidetector entrance apertures distributed in 3-D space. By optimising the object-oriented design in conjunction with the use of a process-oriented and data-oriented code structure, Mc3D is capable of simulating microscopic analysis of a sample with a 3-D geometry or structure that can be expressed with formulae. Three examples of the use of Mc3D are given. The first is for linescans across a block of SiO 2 on top of a Si substrate; the second is for a stripe of SiO 2 embedded in a Si substrate. Finally, the simulation of Auger linescans across an Au overlay on Si is compared with experimental results. The relationships between experimental linescans and the true beam impact positions on the sample are revealed through the virtual scan path. An edge effect, parallel-edge enhancement, is predicted when the incident electron beam size, the distance of impact position to the terrace edge, and the inelastic mean free path of the Auger electron from a given element are comparable, and the linescan is parallel to the terrace edge. All three examples demonstrate the sensitivity of image contrast to the disposition of the sample with respect to the electron column and the detector position.

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