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Black silicon (BSi) is a branch of silicon material whose surface is specially processed to a micro-/nano-scale structure, which inherits most of the advantages of bulk silicon material and possesses some unique optical, electronic, and electrochemical properties that originate from its distinctive surface geometry. BSi is a highly versatile material with properties that can be tuned by changing the surface morphology during the fabrication process. The diverse range of BSi surface morphology enables it to suit the requirements for many applications in the semiconductor industry, such as high-efficiency solar cells, biosensors, photocathodes, or as an anode for lithium batteries. However, the complex nature of BSi surface morphology poses challenges to the current state-of-art surface-related characterisation methods. This thesis will focus on the accurate characterisation for BSi surface morphology and surface dopant profiles. For a surface with micro-/nano-structure morphology, the most established surface topographical method is atomic force microscopy (AFM). However, AFM is not able to probe highly roughened BSi with near-vertical features or overhanging structures. An improved method to accurately extract the BSi morphology is first demonstrated in this thesis, enabling the BSi three-dimensional (3D) surface data to be extracted with high precision over a surface area of up to 320 µm2. This method is based on an automated Xe+ plasma focused ion beam (PFIB) and scanning electron microscopy (SEM) tomography technique. This thesis provides guidelines from sample preparation to optimized post-data processing procedures. For characterising surface dopant profiles, standard dopant profiling techniques can neither properly probe the highly textured BSi surface nor provide a two-dimensional (2D) dopant map. An optimized method based on scanning electron microscopy (SEM) quantitative 2D dopant contrast imaging (SEMDCI) is thoroughly investigated in this thesis. This method utilises SEM under imaging conditions optimized to primarily show the voltage contrast arising from the surface work function. The optimized SEMDCI procedure enables quantitative resolution of the doping level derived from the signal intensity. It can therefore provide the spatial distribution of dopant profiles for complex nano/microtextured surfaces such as BSi. This work provides comprehensive methodology guidelines for BSi-related characterisation that offer suitable measurement accuracy for simulation input. In this thesis, two highly reliable characterisation methods are developed for BSi, offering an in-depth understanding of BSi material properties, and providing insightful design guidelines for BSi semiconductor devices fabrication. |
