Goren Elad, Subramani Balamurugan, Avram Liat, Falkovich Alla H, Perlman Or, Bar-Shir Amnon
Department of Molecular Chemistry and Materials Science, Weizmann Institute of Science, Rehovot 7610001, Israel.
Department of Chemical Research Support, Weizmann Institute of Science, Rehovot 7610001, Israel.
J Am Chem Soc. 2025 Jun 4;147(22):18972-18981. doi: 10.1021/jacs.5c03583. Epub 2025 May 19.
The reliance of modern technology growth on lanthanides presents dual challenges: securing sustainable sources from natural or recycled materials and reducing environmental harm from waste discharge. However, the similar ionic radii, oxidation states, and binding affinities of Ln ions hinder their nondestructive detection in mixtures. Furthermore, the overlap of spectroscopic signals and the inapplicability for opaque solutions limit the harness of luminescent sensors for differentiating one Ln from another. Here, we introduce F-paramagnetic guest exchange saturation transfer magnetic resonance fingerprinting (F-paraGEST MRF), a rapid signal acquisition, encoding, and analysis approach for detecting specific Ln in mixtures. Based on a small-sized experimental F-paraGEST data set, we generated a de novo dictionary of ∼2500 combinations of Ln mixtures, resulting in ∼7,000,000 simulated F-paraGEST MRF patterns of different Ln concentrations. This dictionary was later used for computational pattern recognition of experimental NMR signal evolutions ("fingerprints"), utilizing a rapid computational approach executable on a standard laptop within seconds. Hence, fast and reliable multiplexed lanthanide detection in complex mixtures was enabled. Demonstrated through the analysis of lanthanides' content of permanent magnets from a hard disk drive, this MR-based method paves the way for broader applications of lanthanide detection in murky, nontransparent mixtures and further exploration of supramolecular sensors in diverse scenarios.
确保从天然或回收材料中获取可持续资源，并减少废物排放对环境的危害。然而，镧系离子相似的离子半径、氧化态和结合亲和力阻碍了它们在混合物中的无损检测。此外，光谱信号的重叠以及对不透明溶液的不适用性限制了利用发光传感器区分不同镧系元素的能力。在此，我们引入了F-顺磁客体交换饱和转移磁共振指纹图谱（F-paraGEST MRF），这是一种用于检测混合物中特定镧系元素的快速信号采集、编码和分析方法。基于一个小型的实验F-paraGEST数据集，我们生成了一个约2500种镧系混合物组合的从头字典，得到了约700万个不同镧系元素浓度的模拟F-paraGEST MRF模式。该字典随后用于对实验性核磁共振信号演变（“指纹图谱”）进行计算模式识别，利用一种可在标准笔记本电脑上在数秒内执行的快速计算方法。因此，实现了在复杂混合物中快速可靠地进行多重镧系元素检测。通过对硬盘驱动器中永磁体镧系元素含量的分析得到了验证，这种基于磁共振的方法为在浑浊、不透明混合物中更广泛地应用镧系元素检测以及在不同场景中进一步探索超分子传感器铺平了道路。
