Rapid Quantitative Analysis Research Articles

Monitoring Fuel Dilution of Diesel Engine Lubricant Oil by Ultraviolet Fluorescence Spectroscopy

Fuel contamination is a common problem in lubricating oil contamination. Generally, methods such as gas chromatography can be used, but the experimental process is more complicated. Fluorescence spectroscopy analysis has the advantages of fast detection speed and high sensitivity. Applying it to fuel dilution analysis can simplify the analysis process and enable rapid and accurate quantitative analysis. A certain type of fluorescence spectrophotometer was used to analyze and monitor lubricating oil containing different proportions of diesel oil. The fluorescence sensitive band was found, and the corresponding relationship between different lubricating oil content and the height and peak area of the fluorescence characteristic peak was analyzed.

Copper(II) ions-immobilized virus-like hollow covalent organic frameworks for highly efficient capture and sensitive analysis of amyloid beta-peptide 1–42 by MALDI-MS

Amyloid beta-peptide 1–42 (Aβ1–42) is one of the biomarkers of Alzheimer's disease, and its selective capture and quantitative detection are important for diagnosis and treatment of Alzheimer's disease. Herein, copper(II) ions-immobilized virus-like hollow covalent organic frameworks (V-HCOFs@Cu2+) were synthesized by a facile approach. The as-prepared V-HCOFs@Cu2+ showed unique morphology, ultra-high specific surface (2552 m2/g), uniform mesoporous structure (3.2 nm), superior chemical stability and abundant binding sites. Based on these excellent properties, the V-HCOFs@Cu2+ could be adopted as an ideal enrichment probe for highly efficient capture of Aβ1–42, exhibiting high adsorption capacity (320 mg/g), and fast adsorption equilibration time (3 min). In addition, an attractive approach of the V-HCOFs@Cu2+-based matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) was developed for the rapid screening and quantitative analysis of Aβ1–42 in human serum by using C-peptide as an internal standard, which exhibited low limit of detection (LOD, 0.2 fmol/µL), and satisfactory recovery. This work provides an alternative solution for enrichment of biomarkers and also offers the potential applications of COFs in clinical analysis

Rapid Quantitative Analysis of IR Absorption Spectra for Trace Gas Detection by Artificial Neural Networks Trained with Synthetic Data.

Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases. The concentration information is often retrieved by fitting absorption profiles to the acquired spectra, utilizing spectroscopic databases. In complex gas matrices an expanded parameter space leads to long computation times of the fitting routines due to the increased number of spectral features that need to be computed for each iteration during the fit. This hinders the capability of real-time analysis of the gas matrix. Here, an artificial neural network (ANN) is employed for rapid prediction of gas concentrations in complex infrared absorption spectra composed of mixtures of CO and N2O. Experimental data is acquired with a mid-infrared dual frequency comb spectrometer. To circumvent the experimental collection of huge amounts of training data, the network is trained on synthetically generated spectra. The spectra are based on simulated absorption profiles making use of the HITRAN database. In addition, the spectrometer’s influence on the measured spectra is characterized and included in the synthetic training data generation. The ANN was tested on measured spectra and compared to a non-linear least squares fitting algorithm. An average evaluation time of 303 µs for a single measured spectrum was achieved. Coefficients of determination were 0.99997 for the predictions of N2O concentrations and 0.99987 for the predictions of CO concentrations, with uncertainties on the predicted concentrations between 0.04 and 0.18 ppm for 0 to 100 ppm N2O and between 0.05 and 0.18 ppm for 0 to 60 ppm CO.

Online coupling of bubbling extraction with gas chromatography-mass spectrometry for rapid quantitative analysis of volatiles in beer

Coexistence of matrices and analytes makes the analysis, determination, and quantification of volatiles in beer a tedious process that is difficult to conduct. Bubbling extraction, a newly established sample pretreatment method, directly releases analytes from liquid phase to gas phase by bubble bursting. In this study, we combined bubbling extraction with gas chromatography-mass spectrometry (GC–MS) for direct molecular characterization as well as effective qualitative and quantitative analysis of three types of fermented beers. This method was found to have a high extraction efficiency (bubbling time of 30–300 s), short analysis time (< 30 min), and rational recovery rates (85.6–97.3%) with relative standard deviations (RSDs) less than 10%. Thirteen volatiles were extracted at a wide concentration range of 0.1–10,000 ng/g with correlation coefficient (R2) > 0.990, while the limits of detection (LODs) and limits of quantification (LOQs) were found in scope of 0.001–50 ng/g. Analytical Eco-Scale, Green Analytical Procedure Index (GAPI), and Analytical Greenness (AGREE) approaches proved that our proposed method has a good greenness. In addition, Ale-type, Lambic, and Lager-type beer were successfully classified by the orthogonal partial least squares-discriminant analysis (OPLS-DA). In conclusion, bubbling extraction coupled with GC–MS has potential as a routine analysis tool for identifying volatiles in alcoholic beverages.

Rapid recognition and quantitative analysis of niobium minerals by scanning electron microscopy/energy dispersive X-ray spectroscopy

Rapid recognition and quantitative analysis of niobium minerals by multi-stage filtration techniques based on SEM-EDS.

Competitive fluorescence immunoassay for the rapid qualitative screening and accurate quantitative analysis of ketamine.

In this paper, a sensitive and specific competitive fluorescence immunoassay (CFIA) method was developed for the qualitative and quantitative analysis of ketamine (KET). A novel competitive model in which ketamine hapten (KET-BSA), coated on microporous plates, competed with ketamine antigen (KET-Ag) in actual samples to bind fluorescein isothiocyanate-labeled antibody (KET-Ab) could be used for rapid and indirect quantitative analysis of KET in human urine, blood, or sewage. In the CFIA method, KET concentration in the sample negatively correlated with the detected fluorescence intensity. The linear correlation coefficient of the competitive quantitative equation was 0.992, the linear range was 0.01-0.5 μg mL-1, and the limit of detection (LOD) was 0.1 pg mL-1. The specificity results showed that the cross-reaction rate of norketamine was less than 10%. Recoveries of spiked samples at low, medium, and high concentrations ranged from 96% to 117%. The CFIA method and classical gas chromatography-tandem mass spectrometry (GC-MS/MS) were used to detect the actual samples simultaneously. The relative deviation of the quantitative results was less than 10%. The LOD value of KET by CFIA was four orders of magnitude lower than that by GC-MS/MS. Additionally, CFIA had great advantages over GC-MS/MS in terms of sample pretreatment and economic investment. In conclusion, this study provided a targeting detection platform for KET, which achieved a rapid, portable, and sensitive analysis of trace KET in various materials.

Rapid quantitative analysis of palladium in ores using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence (LIBS-LIF)

This paper discusses the use of conventional LIBS and LIBS-LIF techniques for measuring trace amounts of palladium in solid ore samples.

Rapid Determination of Antioxidant Irganox 1076 in Polyethylene

A method was established to quickly determine the content of antioxidants in polyethylene by Fourier transform infrared spectroscopy. By analyzing the FTIR spectra of the antioxidant Irganox 1076 and PE, the characteristic peak of the antioxidant Irganox 1076 in PE was determined to be the absorption peak at 1738cm-1. According to the standard curve of the antioxidant, the content of the antioxidant had a good linear relationship with the absorption intensity of its characteristic peak, and the linear regression coefficient of the equation was 0.97363. The relative error was less than 7%. The method is accurate and reliable, allowing for rapid quantitative analysis of trace antioxidant content in polyolefin.

A comprehensive strategy for quality evaluation of Wushe Zhiyang Pills by integrating UPLC-DAD fingerprint and multi-ingredients rapid quantitation with UPLC-MS/MS technology

Wushe Zhiyang Pills (WZP), a classical traditional Chinese medicine (TCM) formula, has been extensively used for the treatment of chronic urticaria and other relevant dermatologic diseases. In this study, a holistic method combining ultra-performance liquid chromatography coupled with diode array detector (UPLC-DAD) fingerprint and multi-components quantitative analysis was developed and validated for quality evaluation of WZP. As a result, a total of 34 characteristic peaks were screened to assess the chemical similarities of 16 batches of WZP samples. By coupling with a hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer, 163 compounds were identified or tentatively identified in WZP. Furthermore, a rapid quantitative analysis method based on ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) technique was optimized and validated for simultaneously determination of 16 chemical markers within 13 min in WZP. The developed UPLC-MS/MS approach was successfully employed for analysis of 16 batches of WZP samples. The proposed comprehensive method combining holistic chemical profile with notable target compounds has proved to be suitable for the systematical quality evaluation of WZP, which provides a feasible and efficient strategy to monitor the overall quality consistency of TCM formulae.

Stable isotope labelling-flow injection analysis-mass spectrometry for rapid and high throughput quantitative analysis of 5-hydroxymethylfurfural in drinks

In this work, we reported a stable isotope labelling-flow injection analysis-mass spectrometry (SIL-FIA-MS) method for high throughput analysis of 5-hydroxymethylfurfural (HMF) content in drinks. 3-Nitrophenylhydrazine (3-NPH) and 13 C 6 -3-Nitrophenylhydrazine hydrochloride ( 13 C 6 -3-NPH) were used as pared labelling reagents to selectively label HMF. With a simple centrifugal operation, a certain volume of sample was directly mixed with 3-NPH solution. After adding a small amount of 13 C 6 -3-NPH labelled HMF as internal standard, the sample can be directly transferred for the subsequent MS analysis owing to the contamination-free feature of excess 3-NPH. By using a multi-well thermostatic oscillator to carry out bath derivatization, the average time cost for each sample pretreatment was less than 1 min. Coupled with a triple-quadrupole mass spectrometer, FIA-MS with multiple reaction monitoring (MRM) was used for the rapid and high throughput detection of the labelled HMF in negative ion mode. The time cost for MS detection including injection process for each sample was about 1.5 min. Namely, the whole procedure including sample pretreatment and MS detection can be completed within 3 min per sample, which was very suitable for routine analysis for its high throughput and simplification. By labelling HMF with 3-NPH, the characteristic fragment ion after labelling and detection in interference-lesser negative ion mode enabled high detection specificity even without chromatographic separation. By using 13 C 6 -3-NPH labelled HMF as internal standard to counteract the matrix effect during MS analysis, the detection accuracy and precision were guaranteed. In order to achieve the best conditions for the derivatization of HMF, several derivatization conditions including the acid concentration, the proportion of acetonitrile (ACN), the derivatization reagent concentration, reaction temperature and reaction time were investigated in detail. Under the optimized derivatization, quantitative analysis method was validated in ranges of 0.050–5.0 μg/mL. The relative standard deviations (RSDs) of inter-day and intra-day precision were less than 5.42% and 4.89%, respectively, showing satisfied reproducibility. The proposed method has been successfully applied to the analysis of HMF in sugar-sweetened drinks for feasibility verification in real samples. • SIL-FIA-MS was realized by using MS response-free and contamination-free 3-NPH and 13 C 6 -3-NPH for labelling. • Rapid and high throughput MS analysis for HMF was realized. • The method also offers competitive advantages in accuracy, specificity, simplification, automatability and LODs. • The method is promising to determine other aldehydes in foods with proper modifications.

Label-free Au NRs-based SERS coupled with chemometrics for rapid quantitative detection of thiabendazole residues in citrus

Citrus is a highly consumed fruit worldwide. However, the excessive use of thiabendazole (TBZ) pesticides during citrus cultivation poses a health risk to people. Hence, a rapid and quantitative method has been established for TBZ determination in citrus by coupling gold nanorods (Au NRs) based surface enhanced Raman scattering (SERS) coupling chemometrics. The results show that support vector machine (SVM) can distinguish TBZ residues of different orders of magnitude with 99.1667% accuracy and that genetic algorithm-partial least squares (GA-PLS) had the best performance in the quantitative prediction of TBZ residues (Rp2 = 0.9737, RMSEP = 0.1179 and RPD = 5.85) in citrus. The limit of detection (LOD) was 0.33 μg mL−1. Furthermore, the proposed method was validated by a standard HPLC method using t-test with no significant difference. Therefore, the proposed Au NRs-based SERS technique can be used for the rapid quantitative analysis of TBZ residues in citrus.

Rapid qualitative profiling and quantitative analysis of Juglandis Mandshuricae Cortex and seven flavonoids by ultra‐high performance liquid chromatography–quadrupole/orbitrap high‐resolution mass spectrometry

Juglandis Mandshuricae Cortex is the bark of Juglans mandshurica Maxim., which has been used as a folk medicine plant in China and India. In this study, an ultra-high performance liquid chromatography-quadrupole/orbitrap high-resolution mass spectrometry method was developed to clarify and quantify the chemical profiling of Juglandis Mandshuricae Cortex rapidly. A total of 113 compounds were characterized. Among them, seven flavonoids were simultaneously quantified in 15 min, including myricetin, myricetrin, taxifolin, kaempferol, quercetin, quercitrin, and naringenin. The method was validated for accuracy, precision, and the limits of detection and quantification. All calibration curves showed a good linear relationship (r>0.9990) within test ranges. The intra- and inter-day relative standard deviations were less than 2.16%. Accuracy validation showed that the recovery was between 95.6 and 101.3% with relative standard deviation values below 2.85%. The validated method was successfully applied to determine the contents of seven flavones in Juglandis Mandshuricae Cortex from seven sources and the contents of these places were calculated respectively. This method provides a theoretical basis for further developing the medicinal value of Juglandis Mandshuricae Cortex.

Rapid quantitative analysis and optical properties of ZCTO thin films based on picosecond laser-induced breakdown spectroscopy

Rapid quantitative analysis and optical properties of ZCTO thin films based on picosecond laser-induced breakdown spectroscopy

Analysis of Five Mushroom Toxins in Blood by UPLC-HRMS.

To develop a method for the simultaneous and rapid detection of five mushroom toxins (α-amanitin, phallacidin, muscimol, muscarine and psilocin) in blood by ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS). The blood samples were precipitated with acetonitrile-water solution(Vacetonitril∶Vwater=3∶1) and PAX powder, then separated on ACQUITY Premier C18 column, eluted gradient. Five kinds of mushroom toxins were monitored by FullMS-ddMS2/positive ion scanning mode, and qualitative and quantitative analysis was conducted according to the accurate mass numbers of primary and secondary fragment ions. All the five mushroom toxins had good linearity in their linear range, with a determination coefficient (R2)≥0.99. The detection limit was 0.2-20 ng/mL. The ration limit was 0.5-50 ng/mL. The recoveries of low, medium and high additive levels were 89.6%-101.4%, the relative standard deviation was 1.7%-6.7%, the accuracy was 90.4%-101.3%, the intra-day precision was 0.6%-9.0%, the daytime precision was 1.7%-6.3%, and the matrix effect was 42.2%-129.8%. The method is simple, rapid, high recovery rate, and could be used for rapid and accurate qualitative screening and quantitative analysis of various mushroom toxins in biological samples at the same time, so as to provide basis for the identification of mushroom poisoning events.

Insect Protein Content Analysis in Handcrafted Fitness Bars by NIR Spectroscopy. Gaussian Process Regression and Data Fusion for Performance Enhancement of Miniaturized Cost-Effective Consumer-Grade Sensors.

Future food supply will become increasingly dependent on edible material extracted from insects. The growing popularity of artisanal food products enhanced by insect proteins creates particular needs for establishing effective methods for quality control. This study focuses on developing rapid and efficient on-site quantitative analysis of protein content in handcrafted insect bars by miniaturized near-infrared (NIR) spectrometers. Benchtop (Büchi NIRFlex N-500) and three miniaturized (MicroNIR 1700 ES, Tellspec Enterprise Sensor and SCiO Sensor) in hyphenation to partial least squares regression (PLSR) and Gaussian process regression (GPR) calibration methods and data fusion concept were evaluated via test-set validation in performance of protein content analysis. These NIR spectrometers markedly differ by technical principles, operational characteristics and cost-effectiveness. In the non-destructive analysis of intact bars, the root mean square error of cross prediction (RMSEP) values were 0.611% (benchtop) and 0.545–0.659% (miniaturized) with PLSR, and 0.506% (benchtop) and 0.482–0.580% (miniaturized) with GPR calibration, while the analyzed total protein content was 19.3–23.0%. For milled samples, with PLSR the RMSEP values improved to 0.210% for benchtop spectrometer but remained in the inferior range of 0.525–0.571% for the miniaturized ones. GPR calibration improved the predictive performance of the miniaturized spectrometers, with RMSEP values of 0.230% (MicroNIR 1700 ES), 0.326% (Tellspec) and 0.338% (SCiO). Furthermore, Tellspec and SCiO sensors are consumer-oriented devices, and their combined use for enhanced performance remains a viable economical choice. With GPR calibration and test-set validation performed for fused (Tellspec + SCiO) data, the RMSEP values were improved to 0.517% (in the analysis of intact samples) and 0.295% (for milled samples).

A silicon-based metasurface for terahertz sensing

With the rapid advances in terahertz technologies, the research on sensing applications implemented by terahertz metasurface has attracted significant attention. In this work, we experimentally demonstrated a silicon-based metasurface, which offers the capability for pesticide residue sensing. The spectral characteristics of the resonance peak at about 0.89 THz exhibit a good linear correlation with both benomyl and tricyclazole solutions concentrations. The correlation coefficient reaches 0.995 and 0.972, and the sensitivity is 0.0017 ppm −1 and 0.0015 ppm −1, respectively. In addition, the effects of analytes on spectra were analyzed by numerical simulation. These results provided a promising sensing platform for biochemical sensing application and feasible strategy to achieving rapid primary screening and quantitative analysis of the analyte.

Rapid Analysis of Trace Phthalates by Spray-Inlet Microwave Plasma Torch Ionization Tandem Mass Spectrometry in Commercial Perfumes.

The less volatile fraction of perfumes is susceptible to contamination by phthalate esters (PAEs), which are endocrine-disrupting chemicals encountered during the production, bottling, and transportation processes. There is a need to establish an innovative and rapid method for the determination of trace PAEs in commercial perfumes. Therefore, self-built spray-inlet microwave plasma torch (MPT) ionization coupled with quadrupole time-of-flight (QTOF) tandem MS (MS/MS) was developed for the direct analysis of PAEs in perfumes without sample pretreatment. Perfumes were sprayed directly onto the flame of the MPT by means of a sampling pump at a rate of 10 µL/min and the ions produced by the MPT were introduced into the QTOF-MS equipment with the MPT operating at 2450 MHz and 40 W at a flow rate of 800 ml/min of argon. For the established method, excellent linearity was obtained with a correlation coefficient of 0.9799 for di-n-pentyl phthalate and of greater than 0.99 for the other substances tested. The LOD and LOQ obtained were in the ranges of 1.452-18.96 and 4.839-63.19 ng/g, respectively. The spiked recoveries of PAEs ranged from 100.1 to 105.2% with satisfactory intraday RSDs and interday RSDs ranging from 1.51 to 4.34% and 3.45 to 5.65%, respectively. PAEs in commercial perfumes were successfully detected by spray-inlet MPT-MS/MS with low concentrations ranging from 0.036 to 1.352 µg/g. The method is a promising tool for the on-site analysis of PAEs in cosmetic solutions requiring rapid qualitative and quantitative analysis. The method was successfully applied to the analysis of the commercial perfume samples within 30 s, and displayed the merits of simplicity, sensitivity, environmental friendliness and ease of operation.

Rapid quantitative analysis of hormones in serum by multilayer paper spray MS: Free MS from HPLC

Developing rapid and reliable method for simultaneous hormones quantitation is of great significant because of important roles of hormones in metabolism. However, current methods are faced with problems of low throughput or complicated operation procedure to remove matrices from serum samples in routine clinical diagnosis. In the present work, a multilayer PS-MS method was developed for rapid and simple detection of hormones. In the strategy, multilayer filter paper acted as the Liquid Chromatography in LC-MS/MS for separation of hormones and biological matrices. Qualitative and quantitative analysis of three hormones, testosterone (T), androsterone (ADT) and androstenedione (4-AD) were realized through MS/MS spectra. The method exhibited linearity in the range of 0.02–2 μg/L and the results of recovery and repeatability were satisfactory for standard samples and spiked serum. The time-cost of a whole detection process was less than 3 min. The established multilayer PS-MS realized rapid, simple and reliable quantitative analysis of various hormones and provided broad prospect for clinical analysis of small molecules in different biological samples. Moreover, it provides a novel MS approach with high through-put and free HPLC, meeting the requirements of point-of-care testing (POCT).

APPLICATION OF MICROCOLUMN HPLC-UV FOR RAPID QUANTITATIVE ANALYSIS OF ARBUTIN, BERGEN-IN AND GALLIC ACID IN BERGENIA CRASSIFOLIA

This work is aimed at the development of a microcolumn HPLC-UV assay for the rapid quantitative analysis of arbutin, bergenin, and gallic acid in Bergenia crassifolia. The results obtained indicate appropriate metrological parameters of the developed assay. It was found that the known methods of quantitative analysis of phenolic glycosides using SPE-spectrophotometry cannot be characterized as selective and accurate, due to the fact that the presences of the impurity compounds that do not belong to the group of phenolic glycosides negatively influenced the results. The developed assay was used for quantitative analysis of wild and commercial samples of B. crassifolia raw material. It was found that the content of arbutin, bergenin, and gallic acid in samples of B. crassifolia rhizomes collected in the Republic of Buryatia was 38.58–45.97, 66.74–139.76 and 1.22–1.65 mg/g, respectively, and for commercial batches of raw materials 20.57–41.37, 35.04–83.94 and 0.22–1.28 mg/g, respectively. It was found that the process of gradual enzymatic changes in the color of B. crassifolia leaves (green, red, black) leads to significant changes in the chemical composition. The most pronounced phenomenon is the degradation of bergenin, the presence of which is noted only in green leaves. The concentration of gallic acid is reduced in black leaves. Arbutin is characterized by an increased content in red leaves (102.02 mg/g). Additionally, a quantitative analysis of the peduncles and flowers of B. crassifolia was realized, and it was shown that they are distinguished by a high content of arbutin 48.40 and 42.15 mg/g, respectively, as well as bergenin in flowers (16.89 mg/g). The study demonstrated that the developed technique can be applied for a quick, selective, and accurate quantitative analysis of three compounds in various organs of B. crassifolia.

SEMANTIC SEGMENTATION METHOD ACCELERATED QUANTITATIVE ANALYSIS OF THE SPATIAL CHARACTERISTICS OF TRADITIONAL VILLAGES

Abstract. Rapid investigation and quantitative analysis are crucial for heritage conservation and renewal design. As an important category of architectural heritage - traditional settlements - with their large number and complex spatial characteristics, their spatial character patterns are an important support to assist settlement conservation and renewal design. However, the current means of analysis often requires manual data collection, secondary mapping of the collected data, extraction of individual elemental patterns and village boundaries. Then settlement boundary form, settlement density will be calculated by mathematical methods. The above methods are inefficient and prone to manual mapping errors, making it difficult to quantify and analyze a large number of traditional villages in a short period of time. Semantic segmentation is a computer vision technique for quickly segmenting different objects. Based on the collected remote sensing data of traditional villages, this paper established a dataset of semantic segmentation of spatial features of traditional settlements, segmenting village buildings, water systems, roads and plants. Using Transfer learning, data augmentation and other methods, a model was trained that can automatically segment elements of the villages. From the national traditional villages that have been announced so far, 60 traditional villages from different regions in the north and south were selected for analysis. The experiments show that the model established in this paper has an accuracy rate of above 86% in segmenting elements of villages, can effectively identify the location of different elements in remote sensing images, effectively improves the quantification rate of spatial features of settlements and saves the cost of mapping and data transcription. The results of the spatial characteristics of the 60 villages studied in this paper can also provide some theoretical basis and inspiration for the study, conservation, design and transformation of traditional villages.