The main problem addressed by this dissertation is the accurate and automated determination of electron microscope imaging conditions. This enables the restoration of the object wave, which confers direct structural information about the specimen, from sets of differently aberrated images. An important member in the imaging chain is the image recording device, in many cases now a charge-coupled device (CCD) camera. Previous characterisations of these cameras often relied on the unjustified assumption that the Modulation Transfer Function (MTF) also correctly describes the spatial frequency dependent attenuation of the electron shot noise. A new theory is therefore presented that distinguishes between signal and noise transfer. This facilitates the evaluation of both properties using a detailed Monte-Carlo simulation model for the electron and photon scattering in the scintillator of the camera. Furthermore, methods for the accurate experimental determination of the signal and noise transfer functions are presented. In agreement with the Monte-Carlo simulations, experimental results for commercially available CCD cameras show that the signal transfer is significantly poorer than the noise transfer. The centrepiece of this dissertation is the development of new methods for determining the relative aberrations in a set of images and the absolute symmetric aberrations in the restored wave. Both are based on the analysis of the phase information in the Fourier domain and give each Fourier component a weight independent of its strength. This makes the method suitable even for largely crystalline samples with little amorphous contamination, where conventional methods, such as automated diffractogram fitting, usually fail. The method is then extended to also cover the antisymmetric aberrations, using combined beam tilt and focal series. The applicability of the new method is demonstrated with object wave restorations from tilt and focal series of complex inorganic block oxides and of carbon nanotubes filled with one-dimensional inorganic crystals. The latter specimens allowed for the first time a direct comparison between the phase shift in the restored object wave of a specimen with precisely known thickness and the value predicted by simulations.

The field of infrared (IR) detector technology has shown vast improvements in terms of speed and performance over the years. Specifically the dynamic range (DR) and sensitivity of detectors showed significant improvements. The most commonly used technique of implementing these IR detectors is the use of charge-coupled devices (CCD). Recent developments show that the newly investigated bipolar complementary metal-oxide semiconductor (BiCMOS) devices in the field of detector technology are capable of producing similar quality detectors at a fraction of the cost. Prototyping is usually performed on low-cost silicon wafers. The band gap energy of silicon is 1.17 eV, which is too large for an electron to be released when radiation is received in the IR band. This means that silicon is not a viable material for detection in the IR band. Germanium exhibits a band gap energy of 0.66 eV, which makes it a better material for IR detection. This research is aimed at improving DR and sensitivity in IR detectors. CCD technology has shown that it exhibits good DR and sensitivity in the IR band. CMOS technology exhibits a reduction in prototyping cost which, together with electronic design automation software, makes this an avenue for IR detector prototyping. The focus of this research is firstly on understanding the theory behind the functionality and performance of IR detectors. Secondly, associated with this, is determining whether the performance of IR detectors can be improved by using silicon germanium (SiGe) BiCMOS technology instead of the CCD technology most commonly used. The Simulation Program with Integrated Circuit Emphasis (SPICE) was used to realise the IR detector in software. Four detectors were designed and prototyped using the 0.35 µm SiGe BiCMOS technology from ams AG as part of the experimental verification of the formulated hypothesis. Two different pixel structures were used in the four detectors, which is the silicon-only p-i-n diodes commonly found in literature and diode-connected SiGe heterojunction bipolar transistors (HBTs). These two categories can be subdivided into two more categories, which are the single-pixel-single-amplifier detectors and the multiple-pixel-single-amplifier detector. These were needed to assess the noise performance of different topologies. Noise influences both the DR and sensitivity of the detector. The results show a unique shift of the detecting band typically seen for silicon detectors to the IR band, accomplished by using the doping feature of HBTs using germanium. The shift in detecting band is from a peak of 250 nm to 665 nm. The detector still accumulates radiation in the visible band, but a significant portion of the near-IR band is also detected. This can be attributed to the reduced band gap energy that silicon with doped germanium exhibits. This, however, is not the optimum structure for IR detection. Future work that can be done based on this work is that the pixel structure can be optimised to move the detecting band even more into the IR region, and not just partially. / Dissertation (MEng)--University of Pretoria, 2013. / Electrical, Electronic and Computer Engineering / unrestricted

The main problem addressed by this dissertation is the accurate and automated determination of electron microscope imaging conditions. This enables the restoration of the object wave, which confers direct structural information about the specimen, from sets of differently aberrated images. An important member in the imaging chain is the image recording device, in many cases now a charge-coupled device (CCD) camera. Previous characterisations of these cameras often relied on the unjustified assumption that the Modulation Transfer Function (MTF) also correctly describes the spatial frequency dependent attenuation of the electron shot noise. A new theory is therefore presented that distinguishes between signal and noise transfer. This facilitates the evaluation of both properties using a detailed Monte-Carlo simulation model for the electron and photon scattering in the scintillator of the camera. Furthermore, methods for the accurate experimental determination of the signal and noise transfer functions are presented. In agreement with the Monte-Carlo simulations, experimental results for commercially available CCD cameras show that the signal transfer is significantly poorer than the noise transfer. The centrepiece of this dissertation is the development of new methods for determining the relative aberrations in a set of images and the absolute symmetric aberrations in the restored wave. Both are based on the analysis of the phase information in the Fourier domain and give each Fourier component a weight independent of its strength. This makes the method suitable even for largely crystalline samples with little amorphous contamination, where conventional methods, such as automated diffractogram fitting, usually fail. The method is then extended to also cover the antisymmetric aberrations, using combined beam tilt and focal series. The applicability of the new method is demonstrated with object wave restorations from tilt and focal series of complex inorganic block oxides and of carbon nanotubes filled with one-dimensional inorganic crystals. The latter specimens allowed for the first time a direct comparison between the phase shift in the restored object wave of a specimen with precisely known thickness and the value predicted by simulations.