All News

Revolutionary research demonstrates the power of machine learning in predicting the ground-state electronic structure of organic molecules from core-loss spectra, offering new insights into nanomaterial design.

A new study leverages Fourier transform infrared spectroscopy (FT-IR) to determine the geographical origin and assess the quality of Rosa roxburghii Tratt (RRT), providing valuable insights for functional food production.

New research uncovers novel findings regarding rare earth element (REE) isotopes through the utilization of high-resolution laser-induced breakdown spectroscopy (LIBS) and laser-induced breakdown spectroscopy-molecular laser-induced fluorescence (LIBS-MLIF) techniques.

Machine learning and synchrotron radiation-based micro X-ray fluorescence imaging show promise for early cancer diagnostics by identifying trace biometals as potential cancer biomarkers. The research demonstrates the feasibility of using machine learning algorithms to analyze the spatial distribution of biometals and classify cancer pathogenesis stages, offering potential advancements in non-invasive cancer detection.

New research has demonstrated a two-stage machine learning strategy to overcome bias in spICP-TOF-MS data and improve the classification of nanoparticles. The approach achieves high accuracy in identifying engineered, incidental, and natural nanoparticle types, providing a robust and efficient method for nanoparticle classification in complex samples.

Advanced spectroscopic techniques reveal strong spin-phonon coupling in hexagonal lutetium manganese(III) oxide, providing valuable insights into its magnetoelectric properties. The study's findings pave the way for further exploration and utilization of multiferroic materials in electronic and magnetic device applications.

A theoretical study explores the excited state behavior of triazole pyrimidine group fluorophores, revealing insights into their fluorescence mechanisms and the absence of excited state intramolecular proton transfer (ESIPT). The findings contribute to the understanding and potential applications of these fluorophores in various scientific disciplines.

New approach using polarization spectrum fusion enhances the accuracy of laser-induced breakdown spectroscopy for coal analysis, providing improved predictions of ash content, volatile content, and calorific values.

Laser-induced XUV spectroscopy (LIXS) emerges as a promising technique for high-precision analysis in laser-induced breakdown spectroscopy (LIBS), offering improved limits of detection, precision, and the ability to detect trace heterogeneities in materials. By capturing stable plasma emission in the extreme ultraviolet range, LIXS demonstrates its potential for detecting light elements and halogens with a high signal-to-noise ratio, providing researchers with a valuable tool for advanced material analysis.

The research highlights the significance of tissue preparation methods and demonstrates the feasibility of accurate classification, providing valuable insights into the biomolecular composition of ovarian cancer tissues.

This study addresses crucial factors often overlooked in the literature and provides guidelines for improving the accuracy and interpretation of temperature measurements in plasma diagnostics.

A new publication explores the concept of secondary model-based examination of model-free analysis results in chemical data, revealing hidden insights. His research highlights the significance of integrating quantitative model-based evaluations to enhance data interpretation and extract valuable information.

Researchers from Jan Dlugosz University in Poland employ spectroscopic techniques to characterize calcium phosphate precipitation under conditions mimicking the human eye. Their findings shed light on the mechanisms and structural features of these precipitates, contributing to a better understanding of calcification in intraocular lenses.

Researchers have created a flexible SERS substrate based on Au nanostars and PDMS, enabling highly sensitive detection of thiram residue in apple juice. The innovative substrate offers a reliable method for ensuring food safety by accurately identifying pesticide contaminants.

Two researchers have investigated the fluorescent deactivation behaviors and sensing mechanism of a novel double target fluorescent probe, shedding light on its characteristics and recognition capabilities for aluminum and magnesium ions.

A double spike analytical method has been developed for precise determination of mass-dependent tellurium (Te) isotope compositions in meteorites and terrestrial materials, enabling insights into sample geochemical characteristics and origins.

A research team has developed new photoswitchable cationic spiropyrans that exhibit near-infrared (NIR) fluorescence, opening up exciting possibilities for enhanced biomedical imaging applications. This breakthrough study highlights the potential of these compounds as valuable tools for advancing imaging technologies in the field of biomedicine.

A research team has developed a novel approach using Bessel beam-laser induced breakdown spectroscopy (LIBS) for the classification of uneven steel samples, providing rapid and accurate results. The study highlights the potential of Bessel beam-LIBS as a valuable tool for efficient steel analysis, offering significant applications in the steel industry.

A recent study presents a detailed investigation on the pressure-dependent behavior of a Bi2(MoO4)3 crystal using Raman spectroscopy and lattice dynamic calculations. The study sheds light on the structural transformations and vibrational properties of the crystal under varying pressure conditions, offering valuable insights for material science research.

A newly developed 3D ZnII-based coordination polymer demonstrates exceptional sensitivity in fluorescently detecting nitroaromatic compounds. This research offers potential applications in the field of chemical sensing and provides insights into the interactions between coordination polymers and target molecules.

A team of French researchers has developed a high-precision method for measuring the isotopic composition of europium (Eu) using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), shedding details on the isotopic systematics of this element in geological samples.

Scientists have developed amphiphilic perylene diimide-based fluorescent hemispherical aggregates that serve as effective probes for metal ions, selectively binding to Fe3+ and Ba2+ ions.

Scientists have conducted a spectroscopic analysis of 2-amino-1-naphthalenesulfonic acid, exploring its electronic properties and its potential as an antiviral agent.

A researcher team questions the effectiveness of core consistency as a diagnostic tool in fluorescence analysis of complex samples. This new study suggests the need for alternative methods to accurately determine model complexity in such analyses.

A study utilizing hyperspectral data has revealed valuable insights into the spectral characteristics of typical ground objects. The research findings offer potential for enhanced wetland classification and demonstrate the efficacy of hyperspectral imaging in wetland research.

Scientists have investigated elemental fractionation in aerosol laser-induced breakdown spectroscopy (LIBS) using nanosecond and femtosecond laser ablation. Their study focused on analyzing cesium atomic emissions from airborne nanoparticles in a binary particle matrix. The findings shed light on the influence of the particle matrix on elemental fractionation effects and provide insights for improving LIBS analysis in atmospheric radiation plume tracking.

A geoscience research team has developed a high-resolution method using femtosecond laser ablation multi-collector inductively coupled plasma mass spectrometry (fs-LA-MC-ICP-MS) to determine titanium isotopes in rutiles, offering valuable insights into geological processes.

A research team has developed a rapid and cost-effective method for detecting multiple allergens in gluten-free flour using near-infrared spectroscopy and multivariate chemometric analysis.

Researchers have developed a rapid and accurate method for identifying inflammation in blood using laser-induced breakdown spectroscopy and advanced chemometric methods.

A new study utilized genetic algorithms to optimize pre-processing strategies and classification models such as SVM, multilayer perceptron, and PLS-DA for improved lung cancer diagnosis using Raman spectra data.