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台式核磁共振波谱仪间偏最小二乘回归模型的校正传递。

Calibration Transfer of Partial Least Squares Regression Models between Desktop Nuclear Magnetic Resonance Spectrometers.

机构信息

Departamento de Química, Universidade Estadual de Londrina, 86.057-970 Londrina, Brazil.

Programa de Pós-Graduação em Tecnologia de Alimentos, Universidade Tecnológica Federal do Paraná, Câmpus - Campo Mourão, 87301-899 Campo Mourão, Brazil.

出版信息

Anal Chem. 2020 Oct 6;92(19):12809-12816. doi: 10.1021/acs.analchem.0c00902. Epub 2020 Sep 14.

Abstract

Low-field proton nuclear magnetic resonance (LF-H NMR) devices based on permanent magnets are a promising analytical tool to be extensively applied to the process analytical chemistry scenario. To enhance its analytical applicability in samples where the spectral resolution is compromised, multivariate regression methods are required. However, building a robust calibration model, such as partial least squares (PLS) regression, is a laborious task because (1) the number of measurements required during the calibration process is large and (2) the procedure must be repeated when the instrument is changed or after a certain period due to the long-term stability of the instrument. Thus, the present work describes the application of calibration transfer methodologies (direct standardization (DS), piece-wise direct standardization (PDS), and double-window piece-wise direct standardization (DWPDS)) on LF-H NMR to exempt the necessity of a recalibration procedure when moving from the original spectrometer to a second one with the same, lower, or higher magnetic field. These calibration transfer methodologies were tested with PLS models built on a 60 MHz (for the proton Larmor frequency) spectrometer to predict the specific gravity (SG), distillation temperature (T50%), and final boiling point (FBP) of commercial gasoline. The results showed that the DWPDS method applying only 2 to 7 transference samples enables the transference of all PLS models built on the primary instrument (60 MHz) to other (43, 60, and 80 MHz) different instruments, reaching the same RMSEP values as the primary instrument: 1.2 kg/m for SG, 5.1 °C for FBP, and 1.1 °C for T50%.

摘要

基于永磁体的低磁场质子核磁共振(LF-H NMR)设备是一种很有前途的分析工具,可广泛应用于过程分析化学领域。为了提高其在光谱分辨率受到影响的样品中的分析适用性,需要使用多元回归方法。然而,建立一个稳健的校准模型,如偏最小二乘法(PLS)回归,是一项繁琐的任务,因为(1)在校准过程中需要进行大量的测量,(2)当仪器发生变化或由于仪器的长期稳定性,在经过一段时间后,必须重复该过程。因此,本工作描述了校准转移方法(直接标准化(DS)、分段直接标准化(PDS)和双窗口分段直接标准化(DWPDS))在 LF-H NMR 中的应用,当从原始光谱仪转移到具有相同、较低或较高磁场的第二个光谱仪时,无需进行重新校准过程。这些校准转移方法使用在 60 MHz(质子拉莫尔频率)光谱仪上建立的 PLS 模型进行了测试,以预测商业汽油的比重(SG)、蒸馏温度(T50%)和终沸点(FBP)。结果表明,仅应用 2 到 7 个转移样品的 DWPDS 方法能够将在主要仪器(60 MHz)上建立的所有 PLS 模型转移到其他(43、60 和 80 MHz)不同的仪器上,达到与主要仪器相同的 RMSEP 值:SG 为 1.2 kg/m,FBP 为 5.1°C,T50%为 1.1°C。

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