Search Results (27)

A novel method was developed for the rapid determination of five biogenic amines (BAs)—histamine (HIS), tyramine (TYR), cadaverine (CAD), spermidine (SPD), and spermine (SPM) in cold-chain fish by portable ion trap mass spectrometry with nano-electrospray(nESI) ionization. Samples were homogenized and extracted with aqueous solution containing 1% (v/v) formic acid and 80% (v/v) acetonitrile. With HIS-d4 as an internal standard, the sample solutions were directly injected with the nESI injection device and detected by a portable ion trap mass spectrometer at MS/MS detection mode. The results showed good linearity in the invested range of 0.2 (or 0.5)–10 μg mL⁻¹ with R² > 0.992, The limit of detection (LODs) and limits of quantification (LOQs) for HIS were less than 1.5 mg/kg and 4.0 mg/kg, respectively; the LOD and LOQ for other four BAs were less than 4.0 mg/kg and 12.5 mg/kg, respectively. Recoveries at three fortified levels ranged from 84.26% to 106.6% with relative standard deviations between 4.56% and 13.84%. With the safety limits of HIS as the concentrations of concern, this method demonstrated excellent performance when applied to the eligibility fast screening of HIS in cold-chain fish. The study provided a valuable methodological reference for the rapid detection of BAs in food. Full article

Fentanyl and its analogues represent a severe threat due to their extreme potency and increasing prevalence in illicit drug supplies. Even trace amounts (on the order of a couple of milligrams) can be lethal, contributing to a surge in opioid overdose deaths worldwide. Beyond the public health crisis, fentanyl has emerged as a security concern, with the potential for deliberate use as a chemical agent in CBRN scenarios. This underscores the critical need for rapid and accurate detection methods that can be deployed by security forces and first responders. Modern technology offers a range of solutions—from portable mass spectrometers and spectroscopic devices to electrochemical sensors and immunoassay kits—that enable on-site identification of fentanyl and its analogues. This review provides a comprehensive overview of detection techniques, examining their capabilities and applications in law enforcement, border control, and CBRN incident response. We highlight how integration of advanced sensors with machine learning is enhancing detection accuracy in complex field environments. Challenges such as operational constraints and the ever-evolving variety of fentanyl analogues are discussed, and future directions are recommended to improve field-deployable detection tools for safety and security applications. Full article

Volatile organic compounds (VOCs) in urine headspace are potential biomarkers for different medical conditions, as canines can detect human diseases simply by smelling VOCs. Because dogs can detect disease-specific VOCs, gas chromatography–mass spectrometry (GC–MS) systems may be able to differentiate medical conditions with enhanced accuracy and precision, given they have unprecedented efficiency in separating, quantifying, and identifying VOCs in urine. Advancements in instrumentation have permitted the development of portable GC–MS systems that analyze VOCs at the point of care, but these are designed for environmental monitoring, emergency response, and manufacturing/processing. The purpose of this study is to repurpose the HAPSITE^® ER portable GC–MS for identifying urinary VOC biomarkers. Method development focused on optimizing sample preparation, off-column conditions, and instrumental parameters that may affect performance. Once standardized, the method was used to analyze a urine standard (n = 10) to characterize intra-day reproducibility. To characterize inter-day performance, n = 3 samples each from three volunteers (and the standard) were analyzed each day for a total of four days (n = 48 samples). Results showed the method could detect VOC signals with adequate reproducibility and distinguish VOC profiles from different volunteers with 100% accuracy. Full article

A portable mass spectrometer (PMS) was combined with a mesoporous silica material (SBA-15) coated solid-phase microextraction (SPME) Arrow to develop a rapid, easy-to-operate and sensitive method for detecting five veterinary drugs—amantadine, thiabendazole, sulfamethazine, clenbuterol, and ractopamine—in milk and chicken samples. Equipped with a pulsed direct current electrospray ionization source and a hyperboloid linear ion trap, the PMS can simultaneously detect all five analytes in approximately 30 s using a one-microliter sample. Unlike traditional large-scale instruments, this method shows great potential for on-site detection with no need for chromatographic pre-separation and minimal sample preparation. The SBA-15-SPME Arrow, fabricated via electrospinning, demonstrated superior extraction efficiency compared to commercially available SPME Arrows. Optimization of the coating preparation conditions and SPME procedures was conducted to enhance the extraction efficiency of the SBA-15-SPME Arrow. The extraction and desorption processes were optimized to require only 15 and 30 min, respectively. The SBA-15-SPME Arrow–PMS method showed high precision and sensitivity, with detection limits and quantitation limits of 2.8–9.3 µg kg⁻¹ and 10–28 µg kg⁻¹, respectively, in milk. The LOD and LOQ ranged from 3.5 to 11.7 µg kg⁻¹ and 12 to 35 µg kg⁻¹, respectively, in chicken. The method sensitivity meets the requirements of domestic and international regulations. This method was successfully applied to detect the five analytes in milk and chicken samples, with recoveries ranging from 85% to 116%. This approach represents a significant advancement in food safety by facilitating rapid, in-field monitoring of veterinary drug residues. Full article

A molecular pump is the core component of vacuum systems in portable mass spectrometers and other analytical instruments. The forms of the existing molecular pumps mainly are the combinations of vertical bleed and compression channel, which have the shortcomings of heavy mass and large volume, which seriously restricts the application and development of portable mass spectrometers. Aiming at the problems of low strength and insufficient pumping performance under the miniaturization constraints (mass of 1.8 kg; exhaust diameter of 25 mm) of molecular pumps, a compound pump consisting of a horizontal bleed channel and multi-stage spiral compression channel is proposed. The pumping principle of the compound molecular pump is analyzed to obtain its preliminary structural size parameters. The test particle Monte Carlo method is presented for establishing an aerodynamic model for a high-speed small compound molecular pump, which can be used to investigate the pumping performance of bleed blades and compression channels in a thin air environment. On the basis of the aerodynamic model, the NNIA multi-objective optimization algorithm is presented to optimize the structural parameters of the compound molecular pump. After structural parameter optimization, the maximum flow rate and compression ratio of the compound molecular pump are increased by 13.6% and 41.6%, respectively. The experimental results of the pumping performance show that the predicted data of the aerodynamic model are in good agreement with the experimental data, with an error of 12–27%. Namely, the established aerodynamic model has high accuracy and the optimized structural parameters of the compound molecular pump can provide basic conditions for the large-scale application and promotion of portable mass spectrometers. Full article

Respiratory viruses’ detection is vitally important in coping with pandemics such as COVID-19. Conventional methods typically require laboratory-based, high-cost equipment. An emerging alternative method is Near-Infrared (NIR) spectroscopy, especially a portable one of the type that has the benefits of low cost, portability, rapidity, ease of use, and mass deployability in both clinical and field settings. One obstacle to its effective application lies in its common limitations, which include relatively low specificity and general quality. Characteristically, the spectra curves show an interweaving feature for the virus-present and virus-absent samples. This then provokes the idea of using machine learning methods to overcome the difficulty. While a subsequent obstacle coincides with the fact that a direct deployment of the machine learning approaches leads to inadequate accuracy of the modelling results. This paper presents a data-driven study on the detection of two common respiratory viruses, the respiratory syncytial virus (RSV) and the Sendai virus (SEV), using a portable NIR spectrometer supported by a machine learning solution enhanced by an algorithm of variable selection via the Variable Importance in Projection (VIP) scores and its Quantile value, along with variable truncation processing, to overcome the obstacles to a certain extent. We conducted extensive experiments with the aid of the specifically developed algorithm of variable selection, using a total of four datasets, achieving classification accuracy of: (1) 0.88, 0.94, and 0.93 for RSV, SEV, and RSV + SEV, respectively, averaged over multiple runs, for the neural network modelling of taking in turn 3 sessions of data for training and the remaining one session of an ‘unknown’ dataset for testing. (2) the average accuracy of 0.94 (RSV), 0.97 (SEV), and 0.97 (RSV + SEV) for model validation and 0.90 (RSV), 0.93 (SEV), and 0.91 (RSV + SEV) for model testing, using two of the datasets for model training, one for model validation and the other for model testing. These results demonstrate the feasibility of using portable NIR spectroscopy coupled with machine learning to detect respiratory viruses with good accuracy, and the approach could be a viable solution for population screening. Full article

The decolorization process plays a pivotal role in refining Ginkgo ketone ester by primarily eliminating ginkgolic acids, a toxic component. Presently, the conventional testing method involves sending samples for analysis, causing delays that impact formulation production. Hence, the development of a rapid process control method becomes imperative. This study introduces a swift detection approach for three ginkgolic acids during Ginkgo ketone ester’s decolorization. Initially, an ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method assessed ginkgolic acid C13:0, ginkgolic acid C15:1, and ginkgolic acid C17:1 concentrations in 91 decolorized solution samples, establishing reference values. Subsequently, using a portable Raman spectrometer, Raman spectra of the decolorized liquid within the 3200–200 cm⁻¹ wavelength range were collected. Ultimately, employing partial least squares regression (PLSR) and ResNeXt50 deep learning algorithms, two quantitative calibration models correlated the ginkgolic acid content to Raman spectral data. Both models exhibited high predictive accuracy, with the ResNeXt50 model demonstrating superior performance. The prediction set correlation coefficients ($R_p^2$) for ginkgolic acid C13:0, ginkgolic acid C15:1, and ginkgolic acid C17:1 were 0.9962, 0.9971, and 0.9974, respectively, with root mean square error of prediction (RMSEP) values of 0.0144, 0.0130, and 0.0122 μg/mL. In contrast, the PLSR model yielded $R_p^2$ values of 0.9862, 0.9839, and 0.9480, with RMSEP values of 0.0273, 0.0305, and 0.0545 μg/mL for the three ginkgolic acids. The ResNeXt50 model not only showcased higher precision but also enhanced interpretability, as analyzed through gradient-weighted class activation mapping (Grad-CAM). The integration of Raman spectroscopy and the ResNeXt50 quantitative calibration model furnishes a real-time and precise approach to monitor ginkgolic acid content in the decolorized solution during Ginkgo ketone ester preparation. This significant advancement establishes a robust framework for implementing quality control measures in the decolorization process. Full article

Synthetic cathinones (SCs) are a group of new psychoactive substances often referred to as “legal highs” or “bath salts”, being characterized by a dynamic change, new compounds continuously emerging on the market. This creates a lack of fast screening tests, making SCs a constant concern for law enforcement agencies. Herein, we present a fast and simple method for the detection of four SCs (alpha-pyrrolidinovalerophenone, N-ethylhexedrone, 4-chloroethcathinone, and 3-chloromethcathinone) based on their electrochemical profiles in a decentralized manner. In this regard, the voltametric characterization of the SCs was performed by cyclic and square wave voltammetry. The elucidation of the SCs redox pathways was successfully achieved using liquid chromatography coupled to (tandem) mass spectrometry. For the rational identification of the ideal experimental conditions, chemometric data processing was employed, considering two critical qualitative and quantitative variables: the type of the electrochemical platform and the pH of the electrolyte. The analytical figures of merit were determined on standard working solutions using the optimized method, which exhibited wide linear ranges and LODs suitable for confiscated sample screening. Finally, the performance of the method was evaluated on real confiscated samples, the resulting validation parameters being similar to those obtained with another portable device (i.e., Raman spectrometer). Full article

Eucommia ulmoides gum (EUG) is a natural polymer predominantly consisting of trans-1,4-polyisoprene. Due to its excellent crystallization efficiency and rubber-plastic duality, EUG finds applications in various fields, including medical equipment, national defense, and civil industry. Here, we devised a portable pyrolysis-membrane inlet mass spectrometry (PY-MIMS) approach to rapidly, accurately, and quantitatively identify rubber content in Eucommia ulmoides (EU). EUG is first introduced into the pyrolyzer and pyrolyzed into tiny molecules, which are then dissolved and diffusively transported via the polydimethylsiloxane (PDMS) membrane before entering the quadrupole mass spectrometer for quantitative analysis. The results indicate that the limit of detection (LOD) for EUG is 1.36 μg/mg, and the recovery rate ranges from 95.04% to 104.96%. Compared to the result of pyrolysis-gas chromatography (PY-GC), the average relative error is 1.153%, and the detection time was reduced to less than 5 min, demonstrating that the procedure was reliable, accurate, and efficient. The method has the potential to be employed to precisely identify the rubber content of natural rubber-producing plants such as Eucommia ulmoides, Taraxacum kok-saghyz (TKS), Guayule, and Thorn lettuce. Full article

T-2 toxin is a mycotoxin routinely found as a contaminant of cereal grains worldwide. A portable mass spectrometer was adapted to enable the detection of T-2 toxin in wheat and maize by APCI-MS. In order to facilitate rapid testing, a rapid cleanup was used. The method was able to detect T-2 toxin in soft white wheat, hard red wheat, and yellow dent maize and could be used to screen for T-2 at levels above 0.2 mg/kg. The HT-2 toxin was only detectable at very high levels (>0.9 mg/kg). Based on these results, the sensitivity was not sufficient to allow the application of the screening method to these commodities at levels recommended by the European Commission. With a cut-off level of 0.107 mg/kg, the method correctly classified nine of ten reference samples of wheat and maize. The results suggest that portable MS detection of T-2 toxin is feasible. However, additional research will be needed to develop an application sensitive enough to meet regulatory requirements. Full article

Cannabis is commercially cultivated for both therapeutic and recreational purposes in a growing number of jurisdictions. The main cannabinoids of interest are cannabidiol (CBD) and delta-9 tetrahydrocannabidiol (THC), which have applications in different therapeutic treatments. The rapid, nondestructive determination of cannabinoid levels has been achieved using near-infrared (NIR) spectroscopy coupled to high-quality compound reference data provided by liquid chromatography. However, most of the literature describes prediction models for the decarboxylated cannabinoids, e.g., THC and CBD, rather than naturally occurring analogues, tetrahydrocannabidiolic acid (THCA) and cannabidiolic acid (CBDA). The accurate prediction of these acidic cannabinoids has important implications for quality control for cultivators, manufacturers and regulatory bodies. Using high-quality liquid chromatography–mass spectroscopy (LCMS) data and NIR spectra data, we developed statistical models including principal component analysis (PCA) for data quality control, partial least squares regression (PLS-R) models to predict cannabinoid concentrations for 14 different cannabinoids and partial least squares discriminant analysis (PLS-DA) models to characterise cannabis samples into high-CBDA, high-THCA and even-ratio classes. This analysis employed two spectrometers, a scientific grade benchtop instrument (Bruker MPA II–Multi-Purpose FT-NIR Analyzer) and a handheld instrument (VIAVI MicroNIR Onsite-W). While the models from the benchtop instrument were generally more robust (99.4–100% accuracy prediction), the handheld device also performed well (83.1–100% accuracy prediction) with the added benefits of portability and speed. In addition, two cannabis inflorescence preparation methods were evaluated: finely ground and coarsely ground. The models generated from coarsely ground cannabis provided comparable predictions to that of the finely ground but represent significant timesaving in terms of sample preparation. This study demonstrates that a portable NIR handheld device paired with LCMS quantitative data can provide accurate cannabinoid predictions and potentially be of use for the rapid, high-throughput, nondestructive screening of cannabis material. Full article

A novel, inexpensive and simple experimental setup for collecting μ-Raman spectra of volatile liquids in very small quantities was developed. It takes advantage of capillary forces to detain minute volatile liquid volumes. Spectra of volatile and even scattering or absorbing media can be measured more effectively. The method is used to facilitate the collection of intensity-consistent Raman spectra from a series of reference compounds present in Origanum essential oils, in order to quantify their constituents by multiple linear regression. Wild grown Origanum plants, collected from five different regions in Greece and taxonomically identified as O. onites, O. vulgare subsp. hirtum and O. vulgare subsp. vulgare, were appropriately distilled to acquire their essential oils. Comparison of the Raman results with those from headspace gas chromatography–mass spectrometry (HS GC-MS) confirmed the successful relative quantification of the most abundant essential oil constituents, highlighting the similarities and differences of the three Origanum taxa examined. Finally, it is demonstrated that directly measuring the leaf peltate glandular hairs yields exploitable results to identify the main components of the essential oil they contain, underlining the potential of in situ (field or industry) measurements utilizing microscope-equipped portable Raman spectrometers. Full article

This paper presents an investigation of wooden artworks from the collection of the National Gallery Prague created by Monogrammist IP–one of the top carvers of the Salzburg-Passau region at the beginning of the 16th century. His wood reliefs were examined to gain a better understanding of the historical techniques used in medieval art workshops. The internal structure of the small relief Visitation was analysed using computed tomography. Tomographic reconstruction made it possible to distinguish wood species, observe the internal structure of the artwork in detail, study the technological procedures and identify earlier repairs, additions and damages. Tomographic investigation proved the use of four types of wood on the relief Visitation, most likely pear, lime, unspecified softwood and other different species used for joining dowels. A combination of non-invasive and micro-destructive analytical techniques was employed for the chemical characterisation of the materials in the surface layers of the artworks. Photomicrographs of the surface were taken to provide material for the initial investigation. Non-invasive material research was conducted using a portable X-ray fluorescence analyser and, in selected cases, an external reflection infrared spectrometer. The detailed analyses on the micro-samples was carried out by optical microscopy, micro-Raman spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy coupled with energy dispersive X-ray spectrometry and gas chromatography with mass spectrometry. A glaze layer based on protein with earth pigment was identified on the relief Christ the Saviour from Death. Full article

Radiological aspects such as natural radioactivity of ²³⁸U, ²³²Th, ²²⁶Ra, ⁴⁰K combined with potentially toxic metal(loid) (PTM) distribution features were seldom simultaneously investigated in rare earth element (REE) processing activities. This work was designed to investigate the distribution levels of natural radioactivity, air-absorbed dose rate of γ radiation as well as PTMs at a typical REE plant in Guangdong, China. Ambient soils around REE processing facilities were sampled, measured and assessed. The natural radioactivity of radionuclides of the samples was determined using a high-purity germanium γ-energy spectrometer while the air-absorbed dose rate of γ radiation was measured at a height of 1 m above the ground using a portable radiometric detector. The PTM content was measured by inductively coupled plasma mass spectrometry (ICP-MS). The results showed that the specific activities of the radionuclides ranged from 80.8 to 1990.2, 68.2 to 6935.0, 78.4 to 14,372.4, and 625.4 to 2698.4 Bq·kg⁻¹ for ²³⁸U, ²²⁶Ra, ²³²Th, and ⁴⁰K, respectively, representing overwhelmingly higher activity concentrations than worldwide soil average natural radioactivity. The radium equivalent activity and external hazard index of most samples exceeded the limits of 370 Bq·kg⁻¹ and 1, respectively. The measured air-absorbed dose rate of γ radiation was in a range of 113~4004 nGy·h⁻¹, with most sites displaying comparatively higher values than that from some other REE-associated industrial sites referenced. The content levels of PTMs of Cu, Ni, Zn, Mn, Pb, Cd, Cr, and As were 0.7~37.2, 1.8~16.9, 20.4~2070.5, 39.4~431.3, 2.3~1411.5, 0.1~0.7, 6.7~526.1, and 59.5~263.8 mg·kg⁻¹, respectively. It is important to note that the PTM contents in the studied soil samples were 2.1~5.4 times higher for Zn-As and 1.4 times higher for Pb than the third level of the China soil standard while 2.5~13 times higher for Zn-As and 1.2 times higher for Pb than Canadian industry standard. The findings call for subsequent site remediation to secure the ecological environment and human health after the REE processing plant was decommissioned. Full article

The computational spectrometer has significant potential for portable in situ applications. Encoding and reconstruction are the most critical technical procedures. In encoding, the random mass production and selection method lacks quantitative designs which leads to low encoding efficiency. In reconstruction, traditional spectrum reconstruction algorithms such as matching tracking and gradient descent demonstrate disadvantages like limited accuracy and efficiency. In this paper, we propose a new lightweight convolutional neural network called the wide-spectrum encoding and reconstruction neural network (WER-Net), which includes optical filters, quantitative spectral transmittance encoding, and fast spectral reconstruction of the encoded spectral information. The spectral transmittance curve obtained by WER-net can be fabricated through the inverse design network. The spectrometer developed based on WER-net experimentally demonstrates that it can achieve a 2-nm high resolution. In addition, the spectral transmittance encoding curve trained by WER-Net has also achieved good performance in other spectral reconstruction algorithms. Full article