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In atomic force microscopy (AFM), high\u2010throughput imaging requires higher scan speeds, however, image quality is fundamentally limited by multiple distortions. These artifacts are further amplified for sharp nano\/microstructures, making accurate image restoration inherently challenging. Most deep learning\u2010based approaches rely on a single primary channel and improve performance by increasing model complexity or training data. Here, we introduce a physics\u2010guided multi\u2010channel input approach for AFM that utilizes co\u2010acquired auxiliary signals to improve image restoration efficiency and accuracy. We construct a four co\u2010acquired channel input, each containing complementary physical information. By integrating these channels into a lightweight convolutional neural network, the proposed approach significantly improves restoration quality with minimal additional parameters. At a scan rate of 7.0 Hz, the four\u2010channel DnCNN achieved higher reconstruction accuracy than a single\u2010channel Restormer with approximately 47 times as many parameters, while providing approximately 24 times faster inference. Across the evaluated EFM and PFM conditions, four\u2010channel inputs reduced the training\u2010patch requirement by approximately two to three times at matched PSNR.<\/jats:p>","DOI":"10.1002\/advs.78289","type":"journal-article","created":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T16:10:57Z","timestamp":1792339857000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Physics\u2010Guided Multi\u2010Channel Restoration for Efficient and Accurate Atomic Force Microscopy Imaging"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7848-2945","authenticated-orcid":false,"given":"Jaeuk","family":"Sung","sequence":"first","affiliation":[{"name":"School of Advanced Materials Science and Engineering Sungkyunkwan University  Suwon Republic of Korea"},{"name":"Department of Applied Data Science Sungkyunkwan University (SKKU)  Suwon Republic of 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