基于模拟退火优化的定量重聚INEPT方法
收稿日期: 2023-06-20
网络出版日期: 2023-08-04
基金资助
中国科学院仪器设备功能开发技术创新项目(2017g0105)
Quantitative Refocused INEPT Method Based on Simulated Annealing Optimization
Received date: 2023-06-20
Online published: 2023-08-04
以重聚INEPT（不灵敏核的重聚极化转移增强）脉冲序列为基础，采用模拟退火算法，优化得到极化转移和重聚时间参数集，建立定量重聚INEPT方法．序列中引入组合脉冲，克服射频场不均匀性和频率偏置效应的影响，提高检测的可靠性．进一步利用模拟退火优化，实现重聚INEPT的定量谱编辑．采用青蒿素、辛伐他丁等模型化合物对上述方法进行了验证，应用Case I极化时间参数集，定量积分的相对标准偏差分别为1.6%和3.3%，表明方法有效可靠，可满足定量检测的要求．在实际应用方面，采用定量重聚INEPT方法测定大豆油中脂肪酸含量，其结果与常规定量13C NMR测定的含量相符合，但检测时间显著减少．本文提出的定量重聚INEPT方法在石油、高分子等复杂体系的快速定量检测方面具有广泛的应用前景．
陈雷 , 刘红兵 , 刘惠丽 , 王立英 . 基于模拟退火优化的定量重聚INEPT方法[J]. 波谱学杂志, 2024 , 41(1) : 30 -42 . DOI: 10.11938/cjmr20233071
In this paper, we presented a quantitative refocused INEPT (Refocused Insensitive Nuclei Enhanced by Polarization Transfer) method based on simulated annealing optimization, which utilizes the optimized polarization transfer and refocus delay set to yield nearly uniform enhancement for CH, CH2 and CH3 groups. The 180° composite pulses are applied in 13C channel to overcome the inhomogeneity of B1 field and the offset effect to improve the measurement reliability. Simulated annealing optimization is further applied to achieve quantitative spectral editing of refocused INEPT. The above methods were validated using model compounds such as artemisinin and simvastatin, and the relative standard deviations of the quantitative integrals with Case I delay set were 1.6% and 3.3%, respectively. As an application of the proposed method, major fatty acid compositions in soybean oils were determined using quantitative refocused INEPT, and the results were consistent with those determined by conventional quantitative 13C NMR, while the measurement time was significantly reduced. The quantitative refocused INEPT method is particularly attractive for rapid, accurate detection of complex systems such as petroleum and polymers.
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