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Single column multiple electron beam imaging
Podstránský, Jáchym ; Jánský, Pavel (oponent) ; Zlámal, Jakub (vedoucí práce)
This work is aimed at measuring the electron emission from multiple cathodes formed by n-doped silicon and imaging the electron beams focused by an einzel lens on a CMOS camera. The experimental results are compared with computer simulation to understand the electron emission from the semiconductor cathode and the observed imaging imperfections. Finally, modifications to the experimental setup are suggested that should lead to improvement in the extraction current and spot size of focused electron beams and also better understanding of the processes taking place in the experiment.
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Defectoscopy of thin polymer layers using computer vision
Podstránský, Jáchym ; Sobola, Dinara (oponent) ; Knápek, Alexandr (vedoucí práce)
In the electron beam lithography process, one of the first steps is to coat the substrate, the wafer, with a thin layer of polymer resist. During the coating process, defects occur that can affect the exposure and therefore the functionality of the final nanostructure. By checking the quality of the deposited resin prior to exposure, these defect sites can be avoided. This process can be done manually using a light microscope, but it is a time consuming process. In the framework of this bachelor thesis, a device has been developed that can detect these defects automatically. It is a rasterising device that, by combining two stepper motors and an optical camera, takes images of the desired area of the wafer and then analyses these with the help of artificial intelligence. The user is then provided with a document in which the size, position and type of each defect found is recorded.
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Defectoscopy of thin polymer layers using computer vision
Podstránský, Jáchym ; Sobola, Dinara (oponent) ; Knápek, Alexandr (vedoucí práce)
In the electron beam lithography process, one of the first steps is to coat the substrate, the wafer, with a thin layer of polymer resist. During the coating process, defects occur that can affect the exposure and therefore the functionality of the final nanostructure. By checking the quality of the deposited resin prior to exposure, these defect sites can be avoided. This process can be done manually using a light microscope, but it is a time consuming process. In the framework of this bachelor thesis, a device has been developed that can detect these defects automatically. It is a rasterising device that, by combining two stepper motors and an optical camera, takes images of the desired area of the wafer and then analyses these with the help of artificial intelligence. The user is then provided with a document in which the size, position and type of each defect found is recorded.
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