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全二维气相色谱中具有两个调制子峰的一维峰建模

Modeling of the first dimensional peak with two modulated sub-peaks in comprehensive two-dimensional gas chromatography.

作者信息

Mao Hui, Jiang Ming

机构信息

School of Information Engineering, Wuhan Business University, #816 Dongfeng Avenue, Wuhan, Hubei, 430010, People's Republic of China.

School of Pharmacy, Tongji Medical College, Huazhong University of Science & Technology, #13 Hangkong Road, Wuhan, Hubei, 430030, People's Republic of China.

出版信息

Anal Bioanal Chem. 2023 May;415(13):2425-2434. doi: 10.1007/s00216-022-04245-7. Epub 2022 Aug 1.

Abstract

According to previous published works, precise modeling of the first dimensional (D) peak in comprehensive two-dimensional gas chromatography (GC × GC) requires at least 3 modulated sub-peaks (MSP). This requirement is sometimes difficult to meet, e.g., in case of undersampling modulation. In the present work, the feasibility of modeling of the D peak with only 2 MSP was demonstrated. The effects of modulation phase (ϕ), modulation period (P), the peak width (σ), and the peak shape of the original D peak on the accuracy of the proposed method were explored. When employing P ranging from 6 s ~ 3 s to modulate original peaks with σ = 1.2 s ~ 0.6 s, the maximal error of the modeled t is 1.08 s, which is far less than the error generated by employing the largest MSP to estimate the t. The deviation of modeled t increases with the increase of peak shape distortion, and this deviation is ≤ 0.67 s when tailing factor (T) in the range of 0.8 to 1.5. The application of the proposed method was demonstrated by assisting identification of a monoterpene in Myrrh sample. The proposed approach could improve the accuracy in calculation of t or I and enhance the reliability of compound identification in GC × GC analysis with undersampling modulation.

摘要

根据先前发表的研究成果,在全二维气相色谱(GC×GC)中对第一维度(D)峰进行精确建模至少需要3个调制子峰(MSP)。这一要求有时难以满足,例如在欠采样调制的情况下。在本研究中,证明了仅用2个MSP对D峰进行建模的可行性。探讨了调制相位(ϕ)、调制周期(P)、峰宽(σ)以及原始D峰的峰形对所提方法准确性的影响。当使用6 s至3 s的P来调制σ为1.2 s至0.6 s的原始峰时,建模得到的t的最大误差为1.08 s,远小于使用最大的MSP来估计t所产生的误差。建模得到的t的偏差随着峰形畸变的增加而增大,当拖尾因子(T)在0.8至1.5范围内时,该偏差≤0.67 s。通过辅助鉴定没药样品中的一种单萜类化合物,证明了所提方法的应用。所提方法可以提高t或I计算的准确性,并增强欠采样调制的GC×GC分析中化合物鉴定的可靠性。

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