An Efficient Deep Learning Framework for Revealing the Evolution of Characterization Methods in Nanoscience Article Swipe

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Huicong Duan , Long-Xing Lin , Jichun Wang , Tong-Ruo Diao , Shengjie Qiu , Bi-Jun Geng , Jia Shi , Hu Shu , Zhilin Yang ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1007/s40820-025-01807-z

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Nanotechnology

Deep Learning

Computer Science

Artificial Intelligence

Materials Science

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Characterization (materials science) Nanotechnology Deep learning Computer science Artificial intelligence Materials science

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Type: article
Language: en
Landing Page: https://doi.org/10.1007/s40820-025-01807-z
PDF: https://link.springer.com/content/pdf/10.1007/s40820-025-01807-z.pdf
OA Status: diamond
Cited By: 2
References: 47
Related Works: 10
OpenAlex ID: https://openalex.org/W4411286249

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DOI: https://doi.org/10.1007/s40820-025-01807-z

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Title: An Efficient Deep Learning Framework for Revealing the Evolution of Characterization Methods in Nanoscience

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-06-13

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Authors: Huicong Duan, Long-Xing Lin, Jichun Wang, Tong-Ruo Diao, Shengjie Qiu, Bi-Jun Geng, Jia Shi, Hu Shu, Zhilin Yang

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Landing page: https://doi.org/10.1007/s40820-025-01807-z

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Concepts: Characterization (materials science), Nanotechnology, Deep learning, Computer science, Artificial intelligence, Materials science

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Cited by: 2

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