Rapid elemental analysis and provenance study of Blumea balsamifera DC using laser-induced breakdown spectroscopy

Corrosion resistance of aluminum against acid activation in 1.0 M HCl by symmetrical ball - type zinc phthalocyanine

The inhibition effect of symmetrical Ball - type Zinc Phthalocyanine on Aluminum in 1mol/L hydrochloric acid was analyzed by electrochemical techniques. A novel ball-type zinc phthalocyanine (Zn-Pc) inhibitor has been synthesized and verified utilizing FTIR, nuclear magnetic resonance (1H NMR and 13C NMR), MALDI-TOF MS, and absorption spectroscopy (UV-Vis). In addition, laser-induced breakdown and photoluminescence spectroscopy were employed for additional study. Weight loss technique was employed to investigate the corrosion inhibition effectiveness of the synthesized Zn-Pc on Aluminum in 1mol/L hydrochloric acid at the range of variation temperatures (293-333 K). The inhibition efficiency of Zn-Pc increased with higher concentrations of Zn-Pc and decreased as the temperature increased. Furthermore, Zn-Pc demonstrated outstanding outcomes, achieving 72.9% at a very low inhibitor concentration (0.4 mmol/L) at 298 K. The experimental data for Zn-Pc Aluminum in 1mol/L hydrochloric acid obeys the Langmuir adsorption isotherm. Moreover, the corrosion system's thermodynamic parameters and activation energy were determined. Quantum chemical calculations applying the (DFT) Density Functional Theory method was conducted and applied in this study. These calculations played a pivotal role in elucidating molecular structures and reactivity patterns. Through DFT, numerous reactivity indicators were computed, providing valuable insights into the chemical behavior of the studied compounds. These indicators, such as frontier molecular orbitals, electron density, and molecular electrostatic potential, were subsequently correlated with experimental data.

Simultaneous Sensing of Cd(II), Pb(II), and Cu(II) Using Gold Nanoparticle-Modified APTES-Functionalized Indium Tin Oxide Electrode: Effect of APTES Concentration

In this work, indium tin oxide (ITO) electrodes were functionalized with varying 3-aminopropyltriethoxysilane (APTES) concentration percentages (0.5, 0.75, 1.0, and 2.0 wt %) to obtain the optimum conditions for the assembly of the as-synthesized gold nanoparticles (AuNPs). The AuNP coverage, wettability, and electrochemical performance of the modified electrodes were evaluated. The AuNP/0.75% APTES-ITO-modified electrode exhibited uniform coverage of AuNPs and high electrochemical performance for the simultaneous detection of Cd(II), Pb(II), and Cu(II) ions. Under the optimum conditions, the AuNP/0.75% APTES-ITO-modified electrode showed a linear detection range of 5-120 ppb and limit of detection of 0.73, 0.90, and 0.49 ppb for the simultaneous detection of Cd(II), Pb(II), and Cu(II) ions, respectively, via square wave anodic stripping voltammetry. The modified electrode demonstrated good anti-interference toward other heavy metal ions, good reproducibility, and suitability for application in environmental sample analysis.

A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis

A synergetic strategy was proposed to address the critical issue in the brand characterization of Colla corii asini (Ejiao, CCA), a precious traditional Chinese medicine (TCM). In all brands of CCA, Dong'e Ejiao (DEEJ) is an intangible cultural heritage resource. Seventy-eight CCA samples (including forty DEEJ samples and thirty-eight samples from other different manufacturers) were detected by laser-induced breakdown spectroscopy (LIBS) and near-infrared spectroscopy (NIR). Partial least squares discriminant analysis (PLS-DA) models were built first considering individual techniques separately, and then fusing LIBS and NIR data at low-level. The statistical parameters including classification accuracy, sensitivity, and specificity were calculated to evaluate the PLS-DA model performance. The results demonstrated that two individual techniques show good classification performance, especially the NIR. The PLS-DA model with single NIR spectra pretreated by the multiplicative scatter correction (MSC) method was preferred as excellent discrimination. Though individual spectroscopic data obtained good classification performance. A data fusion strategy was also attempted to merge atomic and molecular information of CCA. Compared to a single data block, data fusion models with SNV and MSC pretreatment exhibited good predictive power with no misclassification. This study may provide a novel perspective to employ a comprehensive analytical approach to brand discrimination of CCA. The synergetic strategy based on LIBS together with NIR offers atomic and molecular information of CCA, which could be exemplary for future research on the rapid discrimination of TCM.

Rapid diagnosis of malaria by chemometric peak-free LIBS of trace biometals in blood

Laser Induced Breakdown Spectroscopy (LIBS) trace atomic species of diseased biofluids are subtle (peak-free) in complex spectra. Trace analysis requires a considerable push in analytical strategy. Enabling LIBS with chemometrics can help identify, extract, analyze and interpret the trace species' spectral signatures to give an insight on the biophysiological status of the bodies from which the biofluids originate. We report on the trace quantitative performance of peak-free LIBS enabled by chemometrics modelling using principal components analysis (PCA) for direct artificial neural network (ANN)-based analysis of Cu, Zn, Fe and Mg in Plasmodium falciparum-infected blood in the context of rapid spectral diagnosis of malaria utilizing the biometals as the disease biomarkers. Only one standard is required in this method-to delineate the analyte spectral regions (feature selection) and to test for accuracy. Based on the alteration of the biometal levels and their multivariate and correlational patterns in cultured blood, peripheral finger blood drops dried directly on Nucleopore membrane filters was accurately discriminated as either malaria-infected or healthy. Further the morphological evolution of Plasmodium was accurately predicted using spectral features of the biometals wherein high negative correlations between Fe (- 0.775) and Zn (- 0.881) and high positive correlations between Cu (0.892) and Mg (0.805) with parasitemia were observed. During the first 96 h of malaria infection Cu increases profoundly (from 328 to 1999 ppb) while Fe, Zn and Mg decrease (from 1206 to 674 ppb), (from 1523 to 499 ppb) and (from 23,880 to 19,573 ppb) respectively. Compared with healthy, Plasmodium falciparum-infected blood has high Cu but low levels of Fe, Zn and Mg. Cu and Zn are highly (≥ 0.9) positively correlated while Fe and Cu as well as Zn and Cu are highly (≥ 0.9) negatively correlated. Chemometric peak-free LIBS showed the potential for direct rapid malaria diagnostics in blood based on the levels, alterations and multivariate associations of the trace biometals which are used as biomarkers of the disease.

Application of Laser-Induced Breakdown Spectroscopy and Chemometrics for the Quality Evaluation of Foods with Medicinal Properties: A Review

Laser-induced Breakdown Spectroscopy (LIBS) is becoming an increasingly popular analytical technique for characterizing and identifying various products; its multi-element analysis, fast response, remote sensing, and sample preparation is minimal or nonexistent, and low running costs can significantly accelerate the analysis of foods with medicinal properties (FMPs). A comprehensive overview of recent advances in LIBS is presented, along with its future trends, viewpoints, and challenges. Besides reviewing its applications in both FMPs, it is intended to provide a concise description of the use of LIBS and chemometrics for the detection of FMPs, rather than a detailed description of the fundamentals of the technique, which others have already discussed. Finally, LIBS, like conventional approaches, has some limitations. However, it is a promising technique that may be employed as a routine analysis technique for FMPs when utilized effectively.

Trends and Application of Chemometric Pattern Recognition Techniques in Medicinal Plants Analysis

Medicinal plants have been used and studied for ages, from very old registers to modern ethnopharmacology, which encompasses analytical chemistry, foods, and pharmacy. Based on international norms and governmental organizations of health, phytomedicine-for example, herbal drugs-needs to guarantee the quality control of products and identify contaminants, biomarkers, and chemical profiles, among other issues. In this sense, is necessary to develop advanced analytical methods that show interesting possibilities and obtain a great amount of data. In order to treat the data, a set of mathematical and statistical procedures named chemometrics is necessary. In terms of herbal drugs, chemometric tools may be used to identify the following in plants: parts, development stages, processing, geographic origin, authentication, and chemical markers. This review describes applications of chemometric pattern recognition tools to analyze herbal drugs in different conditions associated with analytical methods in the last six years (2015-2020).

Recent advances of novel technologies for quality consistency assessment of natural herbal medicines and preparations

Quality consistency is one of the basic attributes of medicines, but it is also a difficult problem that natural medicines and their preparations must face. The complex chemical composition and comprehensive pharmacological action of natural medicines make it difficult to simply apply the commonly used evaluation methods in chemical drugs. It is thus urgent to explore the novel evaluation methods suitable for the characteristics of natural medicines. With the rapid development of analytical techniques and the deepening understanding of the quality of natural herbs, increasing numbers of researchers have proposed many new ideas and technologies. This review mainly focuses on the basic principles, technical characteristics and application examples of the chemical evaluation, biological evaluation methods and their combination in quality consistency evaluation of natural herbs. On the bases of chemical evaluation and clinical efficacy, new methods reflecting their pharmacodynamic mechanism and safety characteristics will be developed, and gradually towards accurate quality control, to achieve the goal of quality consistency. We hope that this manuscript can provide new ideas and technical references for the quality consistency of natural drugs and their preparations, thus better guarantee their clinical efficacy and safety, and better promote industrial development.

Elemental analysis of sage (herb) using calibration-free laser-induced breakdown spectroscopy

In this work, laser-induced breakdown spectroscopy (LIBS) has been used for the quantitative and qualitative analysis of the sage sample using the calibration-free LIBS (CF-LIBS) technique. The sage plasma is generated by focusing the second harmonics (532 nm) of a Q-switched Nd:YAG laser with a repetition rate of 10 Hz and pulse duration of 5 ns. The emission spectra are recorded using a LIBS 2000 detection system spectrometer consisting of five high-resolution spectrometers covering a wavelength range from 200 to 720 nm. The optical emission spectra of the sage sample reveal the spectral lines of Fe, Ca, Ti, Co, Mn, Ni, and Cr. The plasma temperature and electron number density of the neutral spectral lines of the pertinent elements have been deduced using the Boltzmann plot and Stark-broadening line profile method, with average values 8855±885K and 3.89×10¹⁶cm^-3, respectively. The average values of the plasma parameters were used for the quantification of the detected elements in the sample. Based on the calibration-free method, the measured results demonstrate that Fe is the major constituent in the sample, having a percentage concentration of 48.1%, while the remaining elements are Ca, Ti, Co, Mn, Ni, and Cr, with percentage concentrations 0.7%, 5.3%, 8%, 11%, 12.3%, and 14.6%, respectively. This study demonstrates the feasibility of LIBS for the compositional analysis of major and trace elements present in the plant samples and its further applications in medicine.

Deep Learning Associated with Laser-Induced Breakdown Spectroscopy (LIBS) for the Prediction of Lead in Soil

In this study, a method based on laser-induced breakdown spectroscopy (LIBS) was developed to detect soil contaminated with Pb. Different levels of Pb were added to soil samples in which tobacco was planted over a period of two to four weeks. Principal component analysis and deep learning with a deep belief network (DBN) were implemented to classify the LIBS data. The robustness of the method was verified through a comparison with the results of a support vector machine and partial least squares discriminant analysis. A confusion matrix of the different algorithms shows that the DBN achieved satisfactory classification performance on all samples of contaminated soil. In terms of classification, the proposed method performed better on samples contaminated for four weeks than on those contaminated for two weeks. The results show that LIBS can be used with deep learning for the detection of heavy metals in soil.

Novelty application of multi-omics correlation in the discrimination of sulfur-fumigation and non-sulfur-fumigation Ophiopogonis Radix

A rapid and sensitive approach to differentiate sulfur-fumigated (SF) Ophiopogonis Radix based on Multi-Omics Correlation Analysis (MOCA) strategy was first established. It was characterized by multiple data-acquisition methods (NIR, HPLC, and UHPLC-HRMS) based metabonomics and multivariate statistical analysis methods. As a result, SF and non-sulfur fumigated (NSF) Ophiopogonis Radix samples were efficaciously discriminated. Moreover, based on the acquired HRMS data, 38 sulfur-containing discriminatory markers were eventually characterized, whose NIR absorption could be in close correlation with the discriminatory NIR wavebands (5000–5200 cm⁻¹) screened by NIR metabonomics coupled with SiPLS and 2D-COS methods. This results were also validated from multiple perspectives, including metabonomics analysis based on the discriminatory markers and the simulation of SF ophiopogonin D and Ophiopogonis Radix sample. In conclusion, our results first revealed the intrinsic mechanism of discriminatory NIR wavebands by means of UHPLC-HRMS analysis. Meanwhile, the established MOCA strategy also provided a promising NIR based differential method for SF Ophiopogonis Radix, which could be exemplary for future researches on rapid discrimination of other SF Chinese herbal medicines.

Application of picosecond laser-induced breakdown spectroscopy to quantitative analysis of boron in meatballs and other biological samples

This report presents the results of laser-induced breakdown spectroscopy (LIBS) study on biological and food samples of high water content using a picosecond (ps) laser at low output energy of 10 mJ and low-pressure helium ambient gas at 2 kPa. Evidence of excellent emission spectra of various analyte elements with very low background is demonstrated for a variety of samples without the need of sample pretreatment. Specifically, limits of detection in the range of sub-ppm are obtained for hazardous Pb and B impurities in carrots and meatballs. This study also shows the inferior performance of LIBS using a nanosecond laser and atmospheric ambient air for a soft sample of high water content and thereby explains its less successful applications in previous attempts. The present result has instead demonstrated the feasibility and favorable results of employing LIBS with a ps laser and low-pressure helium ambient gas as a less costly and more practical alternative to inductively coupled plasma for regular high sensitive inspection of harmful food preservatives and environmental pollutants.