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Structural annotation of small molecules in tandem mass spectrometry has always been a central challenge in mass spectrometry analysis, especially using a miniaturized mass spectrometer for on-site testing. Here, we propose the Transformer enabled Fragment Tree (TeFT) method, which combines various types of fragmentation tree models and a deep learning Transformer module. It is aimed to generate the specific structure of molecules de novo solely from mass spectrometry spectra. The evaluation results on different open-source databases indicated that the proposed model achieved remarkable results in that the majority of molecular structures of compounds in the test can be successfully recognized. Also, the TeFT has been validated on a miniaturized mass spectrometer with low-resolution spectra for 16 flavonoid alcohols, achieving complete structure prediction for 8 substances. Finally, TeFT confirmed the structure of the compound contained in a Chinese medicine substance called the Anweiyang capsule. These results indicate that the TeFT method is suitable for annotating fragmentation peaks with clear fragmentation rules, particularly when applied to on-site mass spectrometry with lower mass resolution. Tandem mass spectrometry spectra contain structural information of analyzed small molecules, however structural annotation and prediction from MS spectra remain challenging. Here, the authors combine the fragmentation tree models with a deep-learning transformer module, to annotate the fragmentation peaks and generate de novo molecular structures from a low-resolution mass spectrometer. [ABSTRACT FROM AUTHOR]

A miniature ion trap mass spectrometer with capillary direct sampling and vacuum ultraviolet photoionization source was developed to conduct trace analysis of organic compounds in liquids. Self-aspiration sampling is available where the samples are drawn into the vacuum chamber through a capillary with an extremely low flow rate (less than 1 μL/min), which minimizes sample consumption in each analysis to tens of micrograms. A pulsed gas-assisted inlet was designed and optimized to promote sample transmission in the tube and facilitate the cooling of ions, thereby improving instrument sensitivity. A limit of detection of 2 ppb could be achieved for 2,4-dimethylaniline in a methanol solution. The sampling system described in the present study is specifically suitable for a miniature photoionization ion trap mass spectrometer that can perform rapid and online analysis for liquid samples. [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]

Graphical abstract Highlights • An optimized T-trap with uniform electric field was obtained based on electric field analysis and SIMION simulation. • A high correlation was found between the in-trap electric field gradient distribution and the ion emission characteristics. • Directional ion excitation ability can be achieved with appropriate structure modification. • The finding can be used to implement structure optimization of asymmetric ion trap analyzers. Abstract The toroidal-cylindrical ion trap (TCIT) is a small multi-function tandem ion trap analyzer with a simple structure and a compact design. The asymmetric structure of the out toroidal ion trap (T-trap) confers the in-trap region with a non-uniform electric field distribution, particularly when a plate ring electrode is used. To optimize the electric field distribution in the trap, the shapes of the toroidal electrodes were modified to compensate for the electric field. For this purpose, we developed a simple simulation-based method for evaluating the optimized asymmetric structure of the ion trap electrode. Specifically, static electric field distribution in the trap was acquired using COMSOL software and then simply analyzed, while the SIMION simulation platform was adopted to characterize both the ion motion and the performance of the T-trap with an modified structure. The results revealed that electrode optimization can not only improve the non-uniformity of the in-trap electric field distribution but also implement unidirectional emission of the ions upon resonance excitation, thereby significantly increasing the utilization efficiency of the ions in TCIT. In addition, a high correlation was found between the electric field gradient distribution in the trap and the ion emission characteristics, which can provide an simple but useful guiding significance for the performance and structural optimization of T-trap. [ABSTRACT FROM AUTHOR]

In this study, we introduce the design, characterization, and application of an integrated thermal desorption corona discharge ionization (TD-CDI) device, which was developed for direct mass spectrometry (MS) analysis of drugs in solid or liquid samples. The structure and operational parameters of the TD module were optimized through simulation and experimental investigations. For the CDI module, a hollow needle was used as the discharge electrode and sample inlet, allowing self-aspiration and efficient ionization of the desorbed samples. The TD-CDI device was tested and characterized using different mass spectrometers, exhibiting satisfactory stability and quantitative performance. Owing to its compact structure, it can be coupled to a miniature MS instrument to implement rapid identification of various drugs in urine solutions. [Display omitted] • A compact thermal desorption module was coupled to a self-aspiration corona discharge ionization source for drug analysis. • Simulation and experimental methods were combined to optimize various operational parameters. • The TD-CDI device was coupled with both large and miniature mass spectrometers to realizedrug analysis in real samples. [ABSTRACT FROM AUTHOR]

• A complete and practical on-site mass spectrometry food rapid detection strategy. • Self-aspiration ESI constitutes a kind of disposable in-situ MS detection solution. • Two-step pretreatment and one-key analysis to achieve synchronous detection of 31 targets. • Intelligent algorithm improves detection accuracy and reduces matrix interference. With the expansion of the functional food market, the qualification assessment of these products has become a major challenge, and efficient analytical tools are urgently needed. Here, a miniature mass spectrometer (MS) with self-aspiration capillary electrospray ionization (SACESI) source and ion trap analyzer was developed for rapid screening of various illegally added drugs in functional foods. No chromatographic separation was required, but a simplified two-step pretreatment method was developed to reduce the operational procedures and time consumption of the entire analysis. SACESI source uses capillary action to drive solution injection, which utilizes a simple structure and convenient operation to constitute a kind of disposable MS detection solution. To achieve accurate and automatic identification, an intelligent recognition algorithm with steps of spectrum preprocessing, characteristic peak matching, and support vector machine learning was constructed. The relative accuracy of rapid screening of 31 suspicious drugs in various samples is up to 99.78%. It achieves 100% correct identification for the 55 batches of actual samples captured by on-site inspection, which demonstrates the feasibility of the proposed analytical system and strategy in food safety applications. [ABSTRACT FROM AUTHOR]

With the development of instrumental miniaturization, the portable mass spectrometer is becoming a new tool for on-site rapid analysis of environmental samples. Membrane inlet (MI) and photoionization (PI) are two commonly used sampling and ionization techniques, respectively, as they both exhibit detection selectivity for volatile organic compounds (VOCs). In this paper, a membrane inlet photoionization ion trap mass spectrometer was developed for the direct analysis of VOCs in gaseous samples. With the new structure and timing design, various operation modes were proposed and tested. In particular, the use of pulse carrier gas can integrate the appropriate pressure conditions required by each module, thus improving the efficiency of analyte transport, ionization, and mass analysis. The detection limit of sub-ppb was obtained, and the response time can be greatly reduced by increasing the sample flow rate. Furthermore, the capability of selective enrichment for organic analytes was also realized by using a special accumulation mode with a modified sequence, which is easy to operate because no additional devices are needed. [Display omitted] • A miniature membrane inlet photoionization ion trap mass spectrometer was developed for VOCs analysis. • The pulse carrier gas was used to facilitate analyte transfer, ionization, and mass analysis. • The detection limit of sub-ppb level can be obtained for some volatile compounds. • Selective enrichment of organic analytes can be realized without additional devices. [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]