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Rationale: Capillary sampling of liquids for direct mass spectrometry (MS) analysis is introduced. The low transfer rate of the solution in the capillary will affect the analytical sensitivity and the response time; hence a pulsed capillary introduction (PCI) method was proposed and characterized. Methods: The experiments were carried out using a miniature quadrupole mass spectrometer, and liquid can be spontaneously drawn into the vacuum chamber for subsequent ionization and detection. A simple up‐and‐down motor platform was used to control the brief contact of the capillary inlet with the liquid sample and implement pulsed injection. The pulsed sampling parameters were optimized based on the characterization and dynamic study of liquid transfer in capillaries. Results: Compared with continuous capillary introduction (CCI), PCI can reduce the response time of MS analysis from more than half a minute to a few seconds. In addition, it provides better detection sensitivity as the ion signals of all solution components are enhanced and the acquired limit of detection (LOD) of toluene is about eight times lower than CCI analysis. For each analysis, the consumed sample volume is only a few nanoliters and the absolute consumption of the analyte can reach the femtogram level. Conclusions: The proposed PCI method is proved to be successful in improving the sampling efficiency when performing direct liquid analysis without increasing the vacuum load. A miniature MS instrument with a proper capillary inlet can possess flexible operation modes to meet different application demands. [ABSTRACT FROM AUTHOR]

Membrane inlet mass spectrometry (MIMS) is commonly used for detecting the components in liquid samples. When a liquid sample flows through a membrane, certain analytes will permeate into the vacuum chamber of a mass spectrometer from the solution. The properties of the membrane directly determine the substances that can be detected by MIMS. A capillary introduction (CI) method we previously proposed can also be used to analyze gas and volatile organic compounds (VOCs) dissolved in liquids. When CI analysis is carried out, the sample is drawn into the mass spectrometer with no species discrimination. The performance of these two injection methods was compared in this study, and similar response time and limit of detection (LOD) can be acquired. Specifically, MIMS can provide better detection sensitivity for most inorganic gases and volatile organic compounds. In contrast, capillary introduction shows wider compatibility on analyte types and quantitative range, and it requires less sample consumption. As the two injection methods have comparable characteristics and can be coupled with a miniature mass spectrometer, factors such as cost, pollution, device size, and sample consumption should be comprehensively considered when choosing a satisfactory injection method in practical applications. [ABSTRACT FROM AUTHOR]

The back cover image is based on the Research Article Pulse capillary introduction applied to a miniature mass spectrometer for efficient liquid analysis by Wenyan Shi et al., https://doi.org/10.1002/rcm.8293. [ABSTRACT FROM AUTHOR]

Baseline correction is an indispensable step in the signal processing of chemical analysis instruments. With the increasing demand for on-site applications, a variety of analytical instruments require a more friendly, rapid and adaptive baseline correction method. In this paper, a data-driven and coarse-to-fine (DD-CF) baseline correction scheme mainly based on the empirical mode decomposition (EMD) algorithm is proposed. For eliminating the mode-mixing effect of the original EMD, the proposed method firstly obtains a coarse baseline estimation using automatic peak detection, elimination and interpolation; and the EMD is applied on the coarse baseline to get a fine baseline finally. We have compared this method with the adaptive iteratively reweighted Penalized Least Squares algorithm (airPLS) and the sparse representation baseline correction methods using simulated signals and experimental signals from different analytical instruments. Results indicate that the proposed DD-CF scheme can effectively estimate the baseline more accurate than the comparing methods for varies of analytical signals such as mass spectrometer, ion mobility spectrometer, gas chromatograph, etc. Furthermore, with signals of different length, different peak distributions and even from totally different instruments, the proposed method requires minimal user intervention, in which the parameters of the comparing methods should be adjusted for a wide range. [Display omitted] • A data-driven method for baseline correction based on the empirical mode decomposition algorithm. • The mode-mixing effect is avoided by a coarse-to-fine scheme. • The proposed scheme can be adaptive to different analytical instruments with better performance under minimal user intervention. [ABSTRACT FROM AUTHOR]