Electron backscattering coefficient, material contrast and response function of BSE- detectors in scanning electron microscopy.

Images of Ga+ -implanted amorphous silicon layers in a 110 n-type silicon substrate have been collected by a range of detectors in a scanning electron microscope and a helium ion microscope. The effects of the implantation dose and imaging parameters (beam energy, dwell time, etc.) on the image contrast were investigated. We demonstrate a similar relationship for both the helium ion microscope Everhart-Thornley and scanning electron microscope Inlens detectors between the contrast of the images and the Ga+ density and imaging parameters. These results also show that dynamic charging effects have a significant impact on the quantification of the helium ion microscope and scanning electron microscope contrast.

The impurities segregated at the grain boundary of ZnO grains, such as Bi2O3, are important factor to obtain the nonlinear voltage-current (V-I ) characteristics of a Bi-added ZnO varistor. The deterioration of V-I characteristics progresses with voltage application. It has been reported that one of the reasons for this deterioration is the movement of oxide ions and interstitial Zn2+ ions across grain boundaries and around the neighborhood of grain boundaries. Thus, the mobility of ions and the pathway of the current formed by voltage application strongly correlate with the structure of grain boundary, such as the crystal orientation of ZnO grains, the phase of Bi2O3 at the grain boundary, and segregated grains. In the present studies, the structure of grain boundary for the ZnO varistor has been evaluated by composition images obtained from energy dispersive X-ray spectrometry (EDS) with scanning electron microscope (SEM) or with transmission electron microscope (TEM). However, the elemental mapping obtained from EDS with SEM is low resolution and the distribution of elements is obscure. Furthermore, the observation of varistor with TEM is difficult because the sample used for TEM needs precise processing. On the other hand, a composition image with high contrast of tone can be easily obtained using back-scattered electron (BSE) detector with SEM, although BSE detector is lack in the quantitative analysis. In this study, to clarify the microscopic distribution of impurities at the grain boundary with simple method, we observed the fractured surface of ZnO varistor using BSE detector with SEM. For the fractured surface, two types of fracture exist; grain boundary fracture and transcrystalline fracture. The microscopic distribution of impurities can be obtained by observing the surface of grain boundary fracture. The characteristics of ZnO varistor deeply correlate with the state of impurities at the grain boundary such as Bi2O3. To clarify the distribution of these impurities, the fractured surface of Bi-Mn-Co-Sb-added ZnO varistor was observed using SEM, EDS, and BSE detector. It was found that the deposit of Bi2O3 as additive had two types of shape on the surface of grain boundary fracture; spot-like and sheet-like, for Bi-Mn-Co-Sb-added ZnO varistor. With dissolving SiO2 in Bi2O3, the surface tension of Bi2O3 decreased and the sheet-like deposit of Bi2O3 increased, while the spot-like deposit of Bi2O3 decreased. Moreover, when the sample was annealed at 700°C, the surface free energy (surface tension) decreased because Zn2+ and Bi3+ were speculated to become the compound such as Bi7.65 Zn0.35 O11.83 and move to the triple point or line.

Objective. A scanning electron microscope (SEM) is a popular tool for investigating the root canal surface to visualize dentinal tubules, the smear layer and various root canal filling materials in endodontics. Most of the SEM micrographs taken in endodontic research are in secondary electrons (SE) mode, in which the topographic view of a subject can be demonstrated without giving any information about the real structure. Back-scattered electron (BSE) images are also used, which reveal some information about the internal structure while providing no topographic details. The aim of this study was to investigate the possibility of using back-scattered (BSE) and secondary electron (SE) mode of scanning electron microscopy (SEM) together for obtaining detailed information about biomaterials in relation to dental structures. Materials and methods. Mesiobuccal roots of four permanent maxillary molars were cleaned and shaped with rotary instruments. Two samples were obturated with gutta-percha and sealer. After 2 weeks, gutta-perch was removed using rotary instruments and chloroform. In the other phase of the study, white mineral trioxide aggregate was mixed and packed into five glass tubes and exposed to blood, deionized water, synthetic tissue fluid and egg white. All the samples were prepared for visualization under SE and BSE modes of SEM to observe the characteristics of material remnants and surface structures. Results. BSE mode illustrated different grey scale views which made it possible to differentiate dentin chips from filling material remnants on the surface of root canal dentin. In addition, SE mode focused on image topography, while a BSE detector showed new texture formation on the surface of white mineral trioxide aggregate exposed to proteinaceous fluids such as blood or egg white. Conclusions. Mapping BSE and SE micrographs helped us to better understand the structure of materials on the surface of root canal dentin and MTA. Moreover, analysis of structure of materials on the surface of root canal dentine and MTA can be performed better by mapping of BSE and SE micrographs.

The electron channeling contrast imaging (ECCI) is a technique that makes use of the influence of back scattered electrons (BSE) by the relative orientation of crystalline lattice and incident electron beam [1]. The ECCI in scanning electron microscope (SEM) is especially useful to image the crystallographic defects such as dislocations, stacking faults and twin boundaries [2]. In this contribution the amount of channeling contrast in the total BSE signal is quantified and its dependence on different working conditions is explored. An example of the ECCI on an epitaxial GaN thin film is shown in Figure 1. The sample is investigated using ZEISS GeminiSEM 500 FE‐SEM with a PIN‐diode BSE detector under the objective lens. By adjusting the strength of the scanning coil it is possible to move the pivot point of scanning electron down to the surface of the sample, forming the selected area channeling pattern (SACP) [1]. The intensity variation of BSE signal can be extracted by the line profile across the Kikuchi line, shown as the red dotted line in the figure. The relative variation of BSE signal in SACP with respect to average signal can thus be used as a quantification of channeling contrast. The amount of channeling contrast is influenced by the properties of incident electron beam and the detector. In principle, the energy and convergence angle of the incident electron beam determines the channeling pattern itself, while the position and energy response of the detector influence the amount of channeling contrast. In this study a large parameter space is explored to optimize the channeling contrast, including electron beam energy, working distance, convergence angle and position of detectors. As an example, the influence of electron beam energy to channeling contrast is summarized in Figure 2. The SACPs are shown in the right part of the figure. The position of the lines as well as intensity variations within the pattern changes significantly between different energies. However, quantification of the channeling contrast shows a clear trend of increasing channeling contrast at lower electron beam energy.

Standardization and quantification of backscattered electron imaging in scanning electron microscopy

The use of backscattered electron (BSE) imaging in low voltage scanning electron microscopy (SEM) has increased over the past few years. This appears to be due to several factors including improved performance of SEMs at low voltages, reduced beam penetration, more reliable metrology, improved atomic number (Z) contrast information (for low Z) and reduced charging artefacts over secondary electron (SE) imaging. Understanding the factors involved in low voltage BSE detection may assist in improving the information attainable. It has been shown that the signal Sdet from a BSE detector, for EB ≫ Ew is given by where η is the BSE yield, Ω is the solid angle subtended by the detector to the specimen, D is the internal conversion efficiency of the detector, EB is beam accelerating voltage, Ew is the energy barrier of the dead layer on the detector's surface, IB is the beam current, F(Z) and F(Ω) are functions which take into account the variation of BSE energy with atomic number Z and collection angle respectively.

X-ray absorption and backscattered electron (BSE) microscopies are two commonly used techniques for estimating mineral contents in calcified tissues. The resolution in BSE images is usually higher than in x-ray images, but due to the previous lack of good standards to quantify the grey levels in BSE images of bones and teeth, x-ray microtomography (XMT) images of the same specimens have been used for calibration. However, the physics of these two techniques is different: for a specimen with a given composition, the x-ray linear attenuation coefficient is proportional to density, but there is no such relation with the BSE coefficient. To understand the reason that this calibration appears to be valid, the behaviour of simulated bone samples was investigated. In this, the bone samples were modelled as having three phases: hydroxyapatite (Ca10(PO4)6(OH)2), protein, and void (either empty or completely filled with polymethylmethacrylate (PMMA), a resin which is usually used for embedding bones and teeth in microscopic studies). The x-ray linear attenuation coefficients (calculated using published data) and the BSE coefficients (calculated using Monte Carlo simulation) were compared for samples of various phase proportions. It was found that the BSE coefficient correlated only with the x-ray attenuation coefficient for samples with PMMA infiltration. This was attributed to the properties of PMMA (density and mean atomic number) being very similar to those of the protein; therefore, the sample behaves like a two-phase system which allows the establishment of a monotonic relation between density and BSE coefficient. With the newly developed standards (brominated and iodinated dimethacrylate esters) for BSE microscopy of bone, grey levels can be converted to absolute BSE coefficients by linear interpolation, from which equivalent densities can be determined.

Poorly conducting specimens can be examined without coating by using a variable pressure SEM. However, many labs may only have a high vacuum SEM, or for other reasons, choose a high vacuum mode. In order to examine insulating specimens in a high vacuum SEM (using operating conditions conducive to BSE and X-ray analysis) specimens must be coated with a conductive thin film. The perspective of this article is from a materials point of view, but the principles remain the same for biological examinations requiring similar information. Back Scattered Electron (BSE) image contrast is primarily a function of the average atomic number of an imaged area. This is particularly true for polished specimens where there is no topography to contribute to contrast. The BSE coefficient is the ratio of back scattered electrons to incident (beam) electrons.

The contrast of backscattered electron (BSE) images in scanning electron microscopy can be exploited for atomic number or material density determination [1]. However, BSE images suffer from limited spatial resolution for bulk specimens due to the large interaction volume of the primary electrons. This limitation can be overcome by using electron transparent samples as is demonstrated in this work. Comparison of experimental BSE intensities with calculations is required for the quantification of material contrast. We apply here the electron diffusion model of Werner et al. [2] which considers single electron scattering and electron diffusion. To verify and adapt the diffusion model, the calculated results are compared with Monte‐Carlo (MC) simulations [3]. The limited detection angle range of the used annular semiconductor detector from 2.3 rad to 2.77 rad must be taken into account in the calculations. It is also important to take into account the threshold energy of the semiconductor detector, because BSE below 2 keV are not detected by our BSE detector. Hence, the calculation of the energy loss of the BSE is necessary and was accomplished on the basis of an expression for the electron energy dissipation given in [4]. The validity of our procedure for composition analysis is verified by analyzing a sample with known composition and geometry. The investigated sample contains four In x Ga 1‐x As layers of 25 nm thickness with In‐concentrations of x = 0.1, 0.2, 0.3 and 0.4 which are embedded in GaAs‐barrier layers with 35 nm thickness. Details on the growth and verification of the composition of the analyzed sample by alternative techniques are outlined by Volkenandt et al. [5]. Cross‐section samples with wedge‐shaped thickness profiles are prepared perpendicular to the layer system by focused‐ion‐beam (FIB) techniques. A FEI Quanta ESEM equipped with an annular BSE semiconductor detector is used for the measurements. Fig. 1a shows a BSE cross‐section image of a wedge sample with the brighter In x Ga 1‐x As layers separated by GaAs with lower intensity. A Pt‐layer was deposited prior to FIB milling to protect the sample. The thickness of the wedge sample is determined in a region with known composition (here GaAs). For this purpose, an intensity line scan along the wedge with increasing thickness is performed in the GaAs substrate (green arrow in Fig. 1a) at different primary electron energies (Fig. 1b). The thickness‐dependent BSE intensity is normalized with respect to intensity in the thickest part of the wedge, which corresponds in a good approximation to the bulk BSE intensity. By comparison with calculations of the thickness‐dependent backscattering‐coefficient ratio η(t)/η(bulk) (black lines) the offset thickness at the thin edge of the wedge and the local thickness along the line scan can be determined. Subsequently a line scan perpendicular to the layer system (red arrow in Fig. 1a) is performed at a constant thickness of 200 nm. BSE intensity ratios of the In x Ga 1‐x As quantum wells with respect to the GaAs barrier layers are shown in Fig. 2a. Lines with different colors denote calculations for η(t) InGaAs /η(t) GaAs for different E 0 and thicknesses of (200 ± 20) nm. The calculated intensity ratios agree well with the measurements. The accuracy of the technique improves for higher E 0 values because the gradient of the intensity ratios increases. This allows to distinguish In‐concentration differences of 10%. Fig. 2b shows η(t) InGaAs /η(t) GaAs for 20 keV as a function of the sample thickness. Only a weak dependence on the local specimen thickness is observed between 50 and 250 nm giving the optimal range for composition quantifications. At lower thicknesses the BSE intensity is low, while at higher thicknesses the contrast blurs due to the electron beam broadening. It is shown that contrast quantification of BSE images is possible with a high lateral resolution. The sample thickness and the material composition were determined within one single image. Quantifications are successfully performed by comparison of the experimental with calculated data from an analytical model.

The need for increased SEM resolution and the simultaneous demand for enhanced analytical capability have led to the development of increasingly sophisticated instruments. Here we describe the design of a novel SEM column where recently‐developed high‐resolution optics [1] is brought together with traditional analytical capabilities. Combined with FIB it greatly enlarges the capability for 3D tomography inspection of a specimen especially when used in combination with other analytical techniques like EDS or EBSD. The SEM column comprises a triple objective lens design. The first objective lens is optimized to yield an image resolution of less than 1.1 nm at 1 kV. The design retains a single‐pole lens [2] which creates a strong magnetic field around the sample, dramatically decreasing optical aberrations. However, the leaking magnetic field distorts ion trajectories of the FIB and causes beam splitting of ion‐isotopes. To overcome this, FIB processing is performed in a magnetic‐field‐free mode, where the second objective lens of a conventional type with a resolution of 2.5 nm is used. The third objective lens enables a large field of view. A combination of all three objective lenses allows for multiple display modes, e.g. for enlarged field of view, greater depth of field or optimizing resolution at high probe currents. To prevent thermal instability due to changes of lens excitation when switching between the imaging, analytical and other modes, the column works in a regime where constant thermal power dissipation is maintained independent of lens excitation. It significantly reduces image drift and enables stable, long‐term, automatic 3D analysis. 3D BSE tomography of an SERS‐active structure of gold‐coated, partially‐etched polystyrene spheres (Figure 1) was performed maintaining stable operation over a 13 hour period [3]. The sample was sliced using FIB and each cross‐section was automatically imaged at 2 kV using one of the three dedicated back‐scattered electrons (BSE) detectors to obtain the gold distribution on the polystyrene surface. InBeam BSE detector placed in the column acquires high‐angle BSE signal, whereas the two other detectors collect BSE with lower angles. The BSE detector triplet thus enables angle filtration. Furthermore, energy‐filtering of the BSE signal enhances material contrast, (Figure 2), where low‐loss 1.95‐2 keV BSEs reveal details not observable in the integral BSE signal. The redesigned electron gun further enhances the analytical capabilities of the column. It allows probe currents as high as 400 nA for structural analysis and ten times faster beam energy alternation compared to the previous generation. The sharp conus of the objective pole‐piece enables FIB processing of large tilted samples, e.g. 8 inch wafers. The new SEM column will be used in the Mark II generation of the TESCAN MAIA electron microscope and the dual FIB‐SEM instruments GAIA and XEIA [4].

It has been shown that using a Scanning Electron Microscope (SEM), equipped with a Field Emission Gun (FEG) and in-lens specimen position (ultrahigh resolution SEM), operating in the backscattered electron (BSE) mode, it is possible to obtain correct characterization of a superlattice with an image contrast related to the atomic number variation (1).In order to check the performance of a JEOL JSM 890 SEM in the BSE imaging mode, a GaAs/ Ga1-xAlxAs superlattice structure, whose cross section is reported in Fig. 1, has been characterized. On the top there are layers with a fixed value of the mole fraction of Al (x =0.3) and thickness variable between 1 and 20 nm. Below, all the layers are 5 nm thick and the Al mole fraction varies in the range 0.05<x<0.40. Observations at different accelerating voltages show that the image contrast decreases by increasing the electron energy, whereas the resolution is improved. According to our experiments, in these specimen, the best compromise between resolution and contrast is in the energy range 10 - 15 kV. Fig. 2 shows the BSE image, taken at 13 kV, of the top superlattice structure; the GaAs layers appear bright and those of Ga0.7Al0.3As are dark. The resolution obtained on this structure, where the mean atomic number varies by ΔZ=2.7 from layer to layer (corresponding to a contrast C= 4.4% ), is 2 nm. A better evidence of this resolution is given by Fig. 3, which shows a superstructure of 2 nm AlAs / 2nm GaAs, ( ΔZ = 9, C=16%). The image of fig. 4 refers to the superlattice on the bottom of Fig. 1 and allows to specify the minimum detectable ΔZ for a fixed resolution of 5nm. The fringe contrast drops linearly, as well known, with the mean atomic number variation between the layers. As the number of visible fringes is 7, we deduce that the minimum detectable mean atomic number variation is 0.8, (C = 1.3 %).

Paleontologists routinely study fossils using high-magnification and high-resolution backscattered electron (BSE) images acquired via scanning electron microscopy (SEM). In BSE imaging, contrast corresponds to differences in backscattering of primary electrons and BSE detection among points in the electron beam raster scan. In general, BSE images are known for compositional contrast corresponding to backscattering monotonically related to average atomic number. However, two other types of contrast are relevant to BSE-SEM of fossils: (1) topographic contrast corresponding to backscattering and BSE detection varying with specimen shape and (2) mass-thickness contrast corresponding to backscattering varying with the relative masses and thicknesses of materials in the uppermost few microns of a sample. Here, we demonstrate the significance of these contrast mechanisms for resolving three-dimensional and subsurficial features of fossils. First, we show—through study of mass-thickness contrast in BSE images of carbonaceous compressions from the Triassic Solite Quarry Lagerstatte (Virginia)—that some tissues (e.g., leaf and insect wing veins) are preserved as thicker carbonaceous films than others (e.g., leaf laminae and insect wing membranes), possibly reflecting taphonomic differences among anatomical tissues. Second, we show that the problematic phosphatic shelly fossil Sphenothallus (lower Cambrian, China) is covered by low-relief transverse ribs and made up of exteriorly sculptured and interiorly unsculptured carbon- and phosphorus-rich layers with microstructures. Taking advantage of both topographic and mass-thickness contrast mechanisms, these case studies demonstrate that BSE imaging elucidates morphological details that are not obvious in surficial light microscopy or secondary-electron SEM and are otherwise only evident via tomography.

Using the signals of four backscattered electron (BSE) detectors with different detection angles in the scanning electron microscope (SEM) the three‐dimensional surface topography of various samples, i.e. catalysts, fractured surfaces and micro‐devices can be derived and analyzed [1], [2]. An efficient shape from shading reconstruction algorithm is applied to these signals to extract high resolution height and texture information. The surface reconstruction is very fast and needs no sample tilting since the surface topography is calculated from the four simultaneous recorded backscattered electron images. While the 3D reconstruction of the surface topography works very well, the calculation of quantitative height differences depends on different imaging and geometric parameters and requires a calibration of the used BSE detectors. This includes the adjustment of gain and offset of the signals as well as the checking of the geometrical properties of the detector, i.e. detector radius, height, detection area and the horizontal angle to the scan rotation. Especially the height determination, which also depends on the adjustment of the working distance, is hard to determine. Therefore, a spatial calibration is applied with the help of 3D calibration standards [3]. As a result, not only lateral scaling factors, but also z‐scale and shearing effects are estimated. Furthermore, nonlinear deviations are calculated and allow an evaluation of the local and overall accuracy of topographic data, which is achieved applying 3D reconstruction using a calibrated 4Q‐BSE detector. For better accuracy, the reconstruction algorithm was improved by applying refined geometry for the primary and the backscattered electron beam. At low magnifications, the electron beam is not perpendicular to a horizontal specimen surface and the distribution of the backscattered electrons is not isotropic. In addition, the distance between the specimen and the detector is not constant for all image points. Without consideration and correction, this yields to spherical distorted surfaces. The advanced 3D reconstruction algorithm includes geometrical improvements, allowing a distortion‐free mapping of the surface topography over a large magnification range. As an example for application of 3D reconstruction in material sciences, fracture surfaces of a copper base alloy were analyzed. The applied SEM (Hitachi S‐520) is equipped with a complete digital imaging system and in particular with a 4‐quadrant BSE detector (point electronic GmbH) and was geometrically calibrated using a 3D calibration standard. Thus, the spatial scale factors were determined for a magnification of 1000x to cx = 1.013, cy = 1.024, cz = 1.198. While the remaining maximum geometrical deviations after application of these calibration parameters were evaluated with dx = 60 nm, dy = 41 nm and dz = 57 nm the spatial mean deviations for the whole measurement volume is 16 nm. The figures present some results of the investigation. The upper row of pictures shows the dimpled surface microstructure of a forced fracture where the material mostly cracks in a ductile trans‐crystalline manner. The pictures of the bottom row show some crystallographically oriented facets of a fatigue fracture of the same material. On the left for both cases the secondary electron (SE) images are shown, on the right side pictures of the 3D reconstructions of the BSE images are presented. Height differences can be visualised immediately whereas more complex data will be derived from the 3D datasets. The improved 3D reconstruction algorithm is available as standalone software version as well as integrated solution for SEM. Integration into a SEM system allows not only on‐line 3D visualisation, but also easier calibration and especially more reliable application, because full control over all relevant physical and imaging parameters is guaranteed. The integrated topographic 3D reconstruction was developed in cooperation with point electronic GmbH and is now available within their SEM control hard‐ and software DISS. Therefore we like to thank point electronic GmbH for the fruitful cooperation.

The advent of simultaneous energy dispersive X-ray spectroscopy (EDS) data collection has vastly improved the phase separation capabilities for electron backscatter diffraction (EBSD) mapping. A major problem remains, however, in distinguishing between multiple cubic phases in a specimen, especially when the compositions of the phases are similar or their particle sizes are small, because the EDS interaction volume is much larger than that of EBSD and the EDS spectra collected during spatial mapping are generally noisy due to time limitations and the need to minimize sample drift. The backscatter electron (BSE) signal is very sensitive to the local composition due to its atomic number (Z) dependence. BSE imaging is investigated as a complimentary tool to EDS to assist phase segmentation and identification in EBSD through examination of specimens of meteorite, Cu dross, and steel oxidation layers. The results demonstrate that the simultaneous acquisition of EBSD patterns, EDS spectra, and the BSE signal can provide new potential for advancing multiphase material characterization in the scanning electron microscope.

Nanotechnology places increasing demands on techniques for sample characterisation on the sub‐100 nm length scale. The scanning electron microscope (SEM) is one, widely used, technique for imaging and characterising nanomaterials using the intensity of secondary (SE) or backscattered electron (BSE) emission from a probed region of the nanomaterial to generate spatially resolved contrast in an image. The acquisition of the low‐loss electron (LLE) signal [1] in the SEM provides an alternative method which may offer the advantage of improved spatial resolution compositional imaging. Spatial resolution and contrast in compositional imaging of the LLE signal has been investigated by means of experimental measurements in a scanning electron microscope and Monte Carlo simulations for the case of a semiconductor superlattice structure comprising Si 0.85 Ge 0.15 of 11.5 ± 0.4 nm separated by pure Si layers at a periodicity of 69.2 ± 0.2 nm. Both continuous slowing down approximation (CSDA) and discrete‐loss based Monte Carlo models were considered (NISTMonte and PENELOPE) and it was found that the calculated contrast values were particularly sensitive to the choice of model in the low‐loss regime. Experimental data were obtained using a purpose‐built low‐energy electron loss detector [2,3] comprising a retarding field analyser with an electron‐optical input lens. The detector was attached to an FEI Sirion FEGSEM. Experimental data indicated that improved contrast was obtained as the maximum loss energy was lowered (fig 1a), and this trend was reproduced by the simulations (fig 1b). The results indicate that the LLE technique is a useful alternative to operating at low primary beam energies when performing compositional imaging on samples which have nanoscale compositional structure. Statistical noise considerations that affect the LLE signal are discussed. In the case of spatial resolution, resolution metrics for compositional imaging are discussed. It was found that the LLE signal shows improved resolution compared with the backscattered electron signal (figs 2 & 3), however CSDA‐based simulations predict better resolutions than simulations based on a discrete loss model. It is found that the energy‐straggling has the most significant influence on the predicted resolution in the low‐loss regime. The simulations suggest that a SEM with a high‐quality small‐diameter probe is required to fully appreciate the resolution benefits of the LLE signal. Experimental data indicates that certain samples (such as those with sub‐surface compositional inhomogeneity or nanoscale topography) benefit from the LLE technique even when the SEM used has a more modest probe diameter.