Works matching Nuclear magnetic resonance


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    DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data.

    Published in:
    Journal of Cheminformatics, 2023, v. 15, n. 1, p. 1, doi. 10.1186/s13321-023-00738-4
    By:
    • Kim, Hyun Woo;
    • Zhang, Chen;
    • Reher, Raphael;
    • Wang, Mingxun;
    • Alexander, Kelsey L.;
    • Nothias, Louis-Félix;
    • Han, Yoo Kyong;
    • Shin, Hyeji;
    • Lee, Ki Yong;
    • Lee, Kyu Hyeong;
    • Kim, Myeong Ji;
    • Dorrestein, Pieter C.;
    • Gerwick, William H.;
    • Cottrell, Garrison W.
    Publication type:
    Article
    24

    DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data.

    Published in:
    Journal of Cheminformatics, 2023, v. 15, n. 1, p. 1, doi. 10.1186/s13321-023-00738-4
    By:
    • Kim, Hyun Woo;
    • Zhang, Chen;
    • Reher, Raphael;
    • Wang, Mingxun;
    • Alexander, Kelsey L.;
    • Nothias, Louis-Félix;
    • Han, Yoo Kyong;
    • Shin, Hyeji;
    • Lee, Ki Yong;
    • Lee, Kyu Hyeong;
    • Kim, Myeong Ji;
    • Dorrestein, Pieter C.;
    • Gerwick, William H.;
    • Cottrell, Garrison W.
    Publication type:
    Article
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    On Design Challenges of Portable Nuclear Magnetic Resonance System.

    Published in:
    Journal of Nuclear Engineering (JNE), 2023, v. 4, n. 2, p. 323, doi. 10.3390/jne4020025
    By:
    • Hosseinzadehtaher, Mohsen;
    • D'silva, Silvanus;
    • Baker, Matthew;
    • Kumar, Ritesh;
    • Hein, Nathan T.;
    • Shadmand, Mohammad B.;
    • Jagadish, S.V. Krishna;
    • Ghanbarian, Behzad
    Publication type:
    Article
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