The paper presents a super‑resolution generative adversarial network (SRGAN) that boosts electron backscatter diffraction (EBSD) throughput for lithium‑ion battery electrode materials. Trained on LiNixMnyCozO2 cathode data, the SRGAN outperforms classical interpolation across 2×–12× upscaling, especially preserving small grains and realistic boundaries. A 5× upscaling yields a 25× speed‑up or larger field of view with acceptable errors in grain size and shape metrics.
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