Machine learning assisted interpretation of 2D solid-state nuclear magnetic resonance spectra

Wei, Tao; Yu, Wancheng; Zou, Xiangyu; Chen, Wei

doi:10.1016/j.jmr.2023.107492

Cited by 4 publications

(2 citation statements)

References 37 publications

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“…For strengthening the performance of operando ssNMR experiments, methods, such as hyperpolarization, 312 can be considered to enhance the NMR signal-to-noise ratio as well as new data processing methods, such as machine learning assisted NMR data analysis. 313 For unveiling the molecular origin of complicated macroscopic performance of polymer products, such as nonlinear rheology, operando ssNMR with high time and spatial resolution is required. The development of the operando ssNMR requires the improvement of both hardware (e.g., in situ device and new magnet design) and software (e.g., control system and data analysis).…”

Section: Outlook and Perspectivementioning

confidence: 99%

“…Specifically, for polymer processing, it is desirable to develop new operando ssNMR techniques to capture the transient structure and dynamics information, which is crucial for optimizing processing parameters and eventually increasing final polymer products’ performance. For strengthening the performance of operando ssNMR experiments, methods, such as hyperpolarization, can be considered to enhance the NMR signal-to-noise ratio as well as new data processing methods, such as machine learning assisted NMR data analysis . For unveiling the molecular origin of complicated macroscopic performance of polymer products, such as nonlinear rheology, operando ssNMR with high time and spatial resolution is required.…”

Section: Outlook and Perspectivementioning

confidence: 99%

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Elucidations of Structure and Molecular Dynamics of Complex Polymers by State-of-the-Art Solid-State NMR Spectroscopy

Zhang,

Chen,

Miyoshi

2024

Macromolecules

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Solid-state nuclear magnetic resonance (ssNMR) has been playing an indispensable role in revealing the interplay of structure and molecular dynamics in polymers at different states. In this Perspective, we first provide an overview about the fundamental spin interactions in ssNMR and then highlight some recent progress on sensitivity-enhanced ssNMR spectroscopy and in situ NMR. Moreover, we highlight ssNMR applications in the field of polymer crystallization, molecular dynamics, chemical reactions, supramolecular polymers, energy materials, and so on. Finally, our personal perspective is given on the future development at the crossroad of ssNMR and polymer science.

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Section: Outlook and Perspectivementioning

confidence: 99%

Section: Outlook and Perspectivementioning

confidence: 99%

Elucidations of Structure and Molecular Dynamics of Complex Polymers by State-of-the-Art Solid-State NMR Spectroscopy

Zhang,

Chen,

Miyoshi

2024

Macromolecules

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Solid-state NMR spectroscopy

Aliev

2024

Nuclear Magnetic Resonance

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This solid-state NMR report summarises the subject and results of selected articles and original papers published in 2023. In addition to the published reviews, the two major sections in this report consider various methodological developments and a broad range of applications. The presented classification of papers into different sections and subsections is intended to ease the overview of the results, as well as to evaluate the directions in which solid-state NMR techniques and applications are likely to develop in the near future. The overall survey of published papers indicates that the number of electrolyte and battery materials studies by solid-state NMR has increased considerably in 2023 compared to previous years.

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NMR of soft matter systems

Wallace

2024

Nuclear Magnetic Resonance

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This chapter summarises recent advances and applications of solid-state, solution-state and gel-state NMR techniques to study soft matter systems. Original research articles published between March 2023 and March 2024 are discussed that cover surfactants, liquid crystals, polymer solutions, gels and other soft matter systems. Each section of the review focuses on a different NMR technique, including 1D and 2D solution-state experiments, 2H NMR, nuclear Overhauser effect (NOE) and saturation transfer difference (STD) experiments, pulsed-field gradient (diffusion) NMR, relaxation measurements, experiments on quadrupolar counterions and solid-state NMR.

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Machine learning assisted interpretation of 2D solid-state nuclear magnetic resonance spectra

Cited by 4 publications

References 37 publications

Elucidations of Structure and Molecular Dynamics of Complex Polymers by State-of-the-Art Solid-State NMR Spectroscopy

Elucidations of Structure and Molecular Dynamics of Complex Polymers by State-of-the-Art Solid-State NMR Spectroscopy

Solid-state NMR spectroscopy

NMR of soft matter systems

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