Laser-induced breakdown spectroscopy (LIBS) is being proposed more and more as a high-throughput technology to assess the elemental composition of materials. When a specific element is of interest, semiquantification is possible by building a calibration model using the emission line intensity of this element for known samples. However, a unique element has usually more than one emission line, and there are many examples where several emission lines used in combination give dramatically better results than any of the individual variables used alone. With a multivariate approach, models can be constructed that take into account all the emission lines related to a specific element; therefore more robust models can be developed. In this work, chemometric methods such as principal component analysis and partial least squares are proposed to resolve and extract useful information from the LIBS spectral data collected on biological materials.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1364/ao.47.00g158 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Detection of Adulteration of Extra Virgin Olive Oil via Laser-Induced Breakdown Spectroscopy and Ultraviolet-Visible-Near-Infrared Absorption Spectroscopy: A Comparative Study.
Foods
January 2025
Department of Physics, University of Patras, 26504 Patras, Greece.
The fast detection of Extra Virgin Olive Oil (EVOO) adulteration with poorer quality and lower price vegetable oils is important for the protection of consumers and the market of olive oil from fraudulent activities, the latter exhibiting an increasing trend worldwide during the last few years. In this work, two optical spectroscopic techniques, namely, Laser-Induced Breakdown Spectroscopy (LIBS) and UV-Vis-NIR absorption spectroscopy, are employed and are assessed for EVOO adulteration detection, using the same set of olive oil samples. In total, 184 samples were studied, including 40 EVOOs and 144 binary mixtures with pomace, soybean, corn, and sunflower oils, at various concentrations (ranging from 10 to 90% /).
View Article and Find Full Text PDFDetection of heavy metals in soil using Au@SiO nanoparticles and surface microstructure combined with laser-induced breakdown spectroscopy.
J Hazard Mater
January 2025
College of Engineering and Technology, Southwest University, Chongqing 400716, PR China. Electronic address:
The detection of heavy metals in soil is of great scientific significance for food security and human health. However, traditional detection methods are complicated, time-consuming, and labor-intensive. Herein, we developed a novel method using Au@SiO nanoparticles (NPs) and surface microstructure combined with laser-induced breakdown spectroscopy (Au@SiO NPs-SMS-LIBS) for the rapid detection of lead (Pb), chromium (Cr), and copper (Cu) in soil samples.
View Article and Find Full Text PDFTousled-like kinase loss confers PARP inhibitor resistance in BRCA1-mutated cancers by impeding non-homologous end joining repair.
Mol Med
January 2025
Research Institute, National Cancer Center, Goyang-Si, Gyeonggi-Do, 10408, Republic of Korea.
Background: Double-strand breaks (DSBs) are primarily repaired through non-homologous end joining (NHEJ) and homologous recombination (HR). Given that DSBs are highly cytotoxic, PARP inhibitors (PARPi), a prominent class of anticancer drugs, are designed to target tumors with HR deficiency (HRD), such as those harboring BRCA mutations. However, many tumor cells acquire resistance to PARPi, often by restoring HR in HRD cells through the inactivation of NHEJ.
View Article and Find Full Text PDFA review of uranium (U) elemental detection methods.
Anal Methods
January 2025
National Key Laboratory of Uranium Resources Exploration-Mining and Nuclear Remote Sensing, Beijing, 100029, China.
With the increasing demand for energy, nuclear energy has been developing rapidly. The quantitative detection and qualitative identification of uranium (U) are of great significance for the comprehensive and efficient use of U resources and the control of nuclear and radioactive substances. In this study, the detection of U is divided into liquid sample detection, solid sample detection, gas sample detection, and industrial detection from the perspectives of the sample state and detection environment.
View Article and Find Full Text PDFQuantitative analysis and identification of magnesium alloys using fs-LA-SIBS combined with machine learning methods.
RSC Adv
January 2025
School of Electrical Engineering and Intelligentization, Dongguan University of Technology Dongguan 523808 China
This work employs the femtosecond laser-ablation spark-induced breakdown spectroscopy (fs-LA-SIBS) technique for the quantitative analysis of magnesium alloy samples. It integrates four machine learning models: Random Forest (RF), Support Vector Machine (SVM), Partial Least Squares (PLS), and -Nearest Neighbors (KNN) to evaluate their classification performance in identifying magnesium alloys. In regression tasks, the models aim to predict the content of four elements: manganese (Mn), aluminum (Al), zinc (Zn), and nickel (Ni) in the samples.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!