AI + MEMS to enable new electron imaging modes and improve resolution/dose efficiency
AI-assisted strategies support fast and reliable tuning of the MEMS phase modulation and help stabilize operation by accounting for system variability and aberrations. Data-driven optimisation is applied to select effective operating conditions and illumination patterns. This contributes to more automated and reproducible microscope workflows.
Silicon-based MEMS chips are used as in-microscope elements to manipulate the phase of the electron beam. The device functions as a programmable phase modulator, enabling structured electron-wavefront patterns suitable for computational imaging approaches. This provides a compact, tunable platform for controlled beam shaping in TEM.
A computational ghost imaging (CGI) framework is adopted for TEM, where images are reconstructed from structured measurements rather than conventional direct imaging alone. The approach targets enhanced lateral resolution through phase-modulated pattern formation and improved information-per-dose, which is especially relevant for beam-sensitive specimens and low-dose experiments.
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