Characterizing ion adsorption and diffusion in porous carbons is essential to understand the performance of such materials in a range of key technologies such as energy storage and capacitive deionisation. Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful technique to get insights in these systems thanks to its ability to distinguish between bulk and adsorbed species and to its sensitivity to dynamic phenomena. Nevertheless, a clear interpretation of the experimental results is sometimes rendered difficult by the various factors affecting NMR spectra. A mesoscopic model to predict NMR spectra of ions diffusing in carbon particles is adapted to include dynamic exchange between the intra-particle space and the bulk electrolyte surrounding the particle. A systematic study of the particle size effect on the NMR spectra for different distributions of magnetic environments in the porous carbons is conducted. The model demonstrates the importance of considering a range of magnetic environments, instead of a single chemical shift value corresponding to adsorbed species, and of including a range of exchange rates (between in and out of the particle), instead of a single timescale, to predict realistic NMR spectra. Depending on the pore size distribution of the carbon particle and the ratio between bulk and adsorbed species, both the NMR linewidth and peak positions can be largely influenced by the particle size.

表征多孔碳中的离子吸附和扩散对于了解此类材料在储能和电容去离子等一系列关键技术中的性能至关重要。核磁共振 (NMR) 光谱是一种强大的技术，可以深入了解这些系统，因为它能够区分大量物质和吸附物质，并且对动态现象非常敏感。然而，由于影响核磁共振谱的各种因素，有时很难清楚地解释实验结果。预测碳颗粒中离子扩散的核磁共振谱的介观模型适用于包括颗粒内空间和颗粒周围的本体电解质之间的动态交换。对多孔碳中不同磁环境分布的核磁共振谱的粒径影响进行了系统研究。该模型证明了考虑一系列磁性环境（而不是与吸附物质相对应的单个化学位移值）以及包括一系列交换率（粒子内部和外部之间）而不是单个时间尺度的重要性，预测真实的核磁共振谱。根据碳颗粒的孔径分布以及本体和吸附物质之间的比例，NMR 线宽和峰位置在很大程度上受颗粒尺寸的影响。