An approach to overcome barriers to practical Compressed Sensing (CS) implementation in serial scanning electron microscopes (SEM) or scanning transmission electron microscopes (STEM) is presented which integrates scan generator hardware specifically developed for CS, a novel and generalized CS sparse sampling strategy, and an ultra-fast reconstruction method, to form a complete CS system for 2D or 3D scanning probe microscopy. The system is capable of producing a wide variety of highly random sparse sampling scan patterns with any fractional degree of sparsity from 0- 99.9% while not requiring fast beam blanking. Reconstructing a 2kx2k or 4kx4k image requires ~150-300ms. The ultra-fast reconstruction means it is possible to view a dynamic reduced raster reconstructed image based upon a fractional real-time dose. This CS platform provides a framework to explore a rich environment of use cases in CS electron microscopy that benefit from the combination of faster acquisition and reduced probe interaction.

This paper discusses the development of an extensible programmatic workflow that leverages evolving technologies in 2D/3D imaging, distributed instrument control, image processing, and automated mechanical/chemical deprocessing technology. Initial studies involve automated backside mechanical ultra-thinning of 65nm node IC processor chips in combination with SEM imaging and X-ray tomography. Areas as large as 800μm x 800μm were deprocessed using gas-assisted plasma FIB delayering. Ongoing work involves enhancing the workflow with “intelligent automation” by bridging FIB-SEM instrument control and near real-time data analysis to establish a computationally guided microscopy suite.