Innovative New Method Speeds Up Correction of ATR Infrared Spectra
May 20th 2024Researchers at the Leibniz Institute of Photonic Technology have developed a rapid method to correct infrared attenuated total reflection (ATR) infrared spectra, essential for accurate analysis in various scientific fields. By bypassing iterative processes, this approach enhances efficiency and precision.
Deep Learning Advances Gas Quantification Analysis in Near-Infrared Dual-Comb Spectroscopy
May 15th 2024Researchers from Tsinghua University and Beihang University in Beijing have developed a deep-learning-based data processing framework that significantly improves the accuracy of dual-comb absorption spectroscopy (DCAS) in gas quantification analysis. By using a U-net model for etalon removal and a modified U-net combined with traditional methods for baseline extraction, their framework achieves high-fidelity absorbance spectra, even in challenging conditions with complex baselines and etalon effects.