Fluorescent X-ray Scan Image Quality Prediction

• Published in: Journal of hardware and systems security Vol. 4; no. 1; pp. 13 - 23
• Main Authors: Weichman, Peter B., Lavely, Eugene M.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.03.2020; Springer Nature B.V
• Subjects: Algorithms; Circuits and Systems; Computer Hardware; Design of experiments; Electron beams; Electrons; Energy; Engineering; Fluorescence; Fourier transforms; Geometry; High resolution; Image quality; Image resolution; Information Systems Applications (incl.Internet); Integrated circuits; Noise sensitivity; Physics; Point spread functions; Sensor arrays; Sensors; Systems and Data Security; Systems design; Tomography; X-rays; Image quality; X-ray tomography; Transition edge sensor (TES); Scanning electron microscope (SEM); Integrated circuit (IC)
• ISSN: 2509-3428; 2509-3436
• DOI: 10.1007/s41635-019-00084-8

This paper summarizes approaches to image quality prediction in support of an effort under the IARPA RAVEN program to demonstrate a non-destructive, tabletop X-ray microscope for high-resolution 3D imaging of integrated circuits (ICs). The fluorescent X-rays are generated by scanning an electron beam along an appropriately patterned target layer placed in front of the sample and are then detected after passing through the sample by a high-resolution (in both solid angle and energy) backside sensor array. The images are created by way of a model-based tomographic inversion algorithm, with image resolution depending critically on the electron beam scan density and diversity of sample orientations. We derive image quality metrics that quantify the image point spread function and noise sensitivity for any proposed experiment design. Application of these metrics will guide final system design when physical data are not yet available.