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Novel Near-Infrared Fluorescent Probe Sheds Light on Mitochondrial Health, Researchers Say
June 16th 2023Researchers have developed a novel near-infrared fluorescent probe, FNIR-pH, that allows sensitive detection of mitochondrial pH and study of mitophagy, revealing cellular health and disease processes.
Revealing the Size-Dependent Optoelectronics of N-Type Ultra-High Conductive Polymer PBFDO
June 12th 2023A recent study delves into the size-dependent optoelectronics of the N-type ultra-high conductive polymer PBFDO. Researchers explore the absorption spectra, charge transfer modes, and electron transport properties of PBFDO, providing valuable theoretical guidance for its potential applications in nanoscale optoelectronics and device design.
NIR and Raman Spectroscopy Show Promise in Predicting Ice Cream Mix Viscosity
June 12th 2023Researchers have conducted a preliminary study on the potential use of near-infrared (NIR) and Raman spectroscopy for predicting ice cream mix viscosity. The study highlights the promising performance of NIR spectroscopy and serves as a starting point for further investigations into in situ application of these analytical tools in the ice cream manufacturing process.
New Method Enables Accurate Measurement of Iodine-129 in Decommissioning Wastes Using ICP-MS/MS
June 9th 2023Scientists have developed an optimized method for the precise measurement of iodine-129 in decommissioning wastes using tandem ICP-MS/MS. Their study demonstrates the effectiveness of this approach in achieving low-level measurements with improved sensitivity for waste characterization and environmental monitoring.
Machine Learning and Synchrotron Imaging: Advancing Early Cancer Diagnostics
June 2nd 2023Machine 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.
Machine Learning Unveils Efficient Classification of Nanoparticles from Noisy spICP-TOF-MS Data
June 2nd 2023New 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.
New Approach Enhances Accuracy of Laser-Induced Breakdown Spectroscopy for Coal Analysis
June 1st 2023New 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): Unveiling the Potential for High-Precision LIBS Analysis
May 31st 2023Laser-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.