Under the joint guidance of Researcher Li Liangbin and Specially Appointed Professor Chen Wei, Ph.D. candidate Chen Xiaojie and colleagues have published a comprehensive review on the applications of low-field nuclear magnetic resonance (LF-NMR) in polymer science in the journal Giant. Centered on the unique characteristics of LF-NMR, the review highlights advances in hardware design, pulse sequence development, and applications in polymer research. Drawing on the structural features of polymers, it further discusses challenges and future prospects in areas such as gelation and polymer networks, the micromechanics of soft matter, and the industrial processing of polymer materials.
The article first summarizes the progress in LF-NMR spectrometer hardware, including magnets, radiofrequency coils, spectrometers, and coupled devices, providing researchers in instrument design and development with a clear overview of the field’s evolution. It then reviews commonly used LF-NMR pulse sequences—covering relaxation, multiple quantum, spin diffusion, small-molecule diffusion, and imaging—explaining their basic principles and emphasizing the distinctive features and parameter requirements of each. This section serves as a valuable reference for experts in pulse design and modulation. Finally, the review presents the applications of LF-NMR in polymer science, including studies of multicomponent polymers, polymer networks, morphology, polymer chain dynamics, and imaging. Classic examples such as semicrystalline polymers, polymer-based nanocomposites, and the heterogeneity of polymer networks are discussed, offering new insights and perspectives for polymer researchers.
This work was supported by the National Natural Science Foundation of China (Grants 52422302 & U20A20256) and the Natural Science Foundation of Anhui Province (Grants 2308085UM02 & 2408055UM001).
Xiaojie Chen, Chengyan Li, Lei Wu, Shaojie Yan, Lingxun Qi, Junfei Chen, Wei Chen, Low-Field NMR for Polymer Science, Giant (2025)
Paper Link：https://doi.org/10.1016/j.giant.2025.100364
