We describe the development of quantitative electron spectroscopic tomography (QuEST), which provides three-dimensional distributions of elements on a nanometer scale. Specifically, it is shown that QuEST can be applied to map the distribution of phosphorus in unstained sections of embedded cells. A series of 2D elemental maps is derived from images recorded in the energy filtering transmission electron microscope for a range of specimen tilt angles. A quantitative 3-D elemental distribution is then reconstructed from the elemental tilt series. To obtain accurate quantitative elemental distributions it is necessary to correct for plural inelastic scattering at the phosphorus L 2,3 edge, which is achieved by acquiring unfiltered and zero-loss images at each tilt angle. The data are acquired automatically using a cross correlation technique to correct for specimen drift and focus change between successive tilt angles. An algorithm based on the simultaneous iterative reconstruction technique (SIRT) is implemented to obtain quantitative information about the number of phosphorus atoms associated with each voxel in the reconstructed volume. We assess the accuracy of QuEST by determining the phosphorus content of ribosomes in a eukaryotic cell, and then apply it to estimate the density of nucleic acid in chromatin of the cell's nucleus. From our experimental data, we estimate that the sensitivity for detecting phosphorus is 20 atoms in a 2.7 nm-sized voxel.

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New advances in cathodoluminescence (CL) instrumentation allow more advanced characterisation of compound semiconductor materials and devices. CL offers the advantage of combined high spatial and spectral information in one experiment. However, until now, CL results have typically been two dimensional, in the form of images at discrete wavelengths, or spectra chosen from specific points on the specimen. Spectrum Imaging allows large data sets to be collected with relative ease so that the full spectroscopic information can be recorded at every pixel position in an image. Gaussian fitting and advanced subtraction techniques are shown to be valuable in mapping spectral shifts, peak widths, and in the extraction of hidden luminescence features. This helps characterise important luminescence features such as impurities, doping, stress, extended defects, and alloy and quantum confinement inhomogeneities.Introduction Cathodoluminescence (CL) is the emission of photons from a specimen stimulated using an electron beam. The CL emitted is governed by competition between non-radiative and radiative electron-hole pair recombination events. In the field of compound semiconductors, where the ability to emit and detect photons efficiently and of a specific wavelength is of paramount importance in their application, CL is increasingly used as a research and evaluation tool. The growth in the application ranges from materials and growth characterisation through to device design and failure analysis.The technique has the advantage of giving relatively high spatial resolution results using a flexible injection source. In a scanning electron microscope (SEM or STEM) the electron probe is easy to control in terms of position, focusing, energy and flux. In addition it has a high depth of field so can cope with complex structures, and takes place in a vacuum which is ideal for cryogenic temperatures. The spatial resolution which is achievable is dependent on the specimen, microscope and CL equipment. Recent results have demonstrated resolution in the range of 20 nm [1]. CL performed in a transmission electron microscope also offers the promise of high spatial resolution due to the reduced dimensions of the generation volume for a thin TEM sample.Growth in CL as a technique has matched advances in the importance of compound semiconductors and has been associated with advances in electron microscope and cathodoluminescence technology. Early CL studies were primarily limited to panchromatic imaging. This simple method of collecting and detecting luminescence without recourse to dispersion or filtering remains valuable, especially in terms of mapping non radiative recombination sites.Spectral CL has gained in popularity over the last decade. The most favoured and successful approach involves direct optical coupling between a specimen, a monochromator, and finally a photo-multiplier

Electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) is a powerful technique that analyzes the inelastic scattering distribution of the fast TEM electrons after they have lost energy within the sample. The resultant energy-losses are characteristic of elemental, chemical, and dielectric properties and are typically measured in one of two ways. Parallel-detection EELS spectrometers (PEELS) acquire spectral data over a large range of energy-loss simultaneously for rapid acquisition of spectral data at a single point. In contrast, the energy filtering TEM (EFTEM) acquires only a single energy band at once, but does so for thousands or even millions of image pixels simultaneously.Spectrum-imaging concerns the acquisition of spectroscopic data of sufficient detail for rigorous analysis at each pixel in a digital image. (Fig. 1) A STEM EELS spectrum image “data cube” can be acquired by stepping a focused electron probe to each pixel and filling the spectrum image one spectrum at a time.

Electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) analyzes the energy distribution of the probe electrons after they have lost energy within the sample. The resultant energy-losses are characteristic of elemental, chemical, and dielectric properties and are typically measured in one of two ways. Parallel-detection EELS spectrometers (PEELS) acquire large energy ranges of the energy-loss spectrum simultaneously for rapid acquisition of spectral data at a single area. In contrast, the energy filtering TEM (EFTEM) acquires only a single energy band at once, but does so for thousands or even millions of image pixels simultaneously.Spectrum imaging (SI) involves acquisition of detailed spectroscopic data sufficient for rigorous analysis at each pixel in a digital image. (Fig. la) A STEM EELS spectrum image “data cube” can be acquired by stepping a focused electron probe to each pixel and filling the spectrum image one spectrum at a time.