One of the essential goals of molecular spectroscopy is to measure all fundamental molecular vibrations simultaneously. To this end, one needs to measure broadband infrared (IR) absorption and Raman scattering spectra, which provide complementary vibrational information. A recently demonstrated technique called complementary vibrational spectroscopy (CVS) enables simultaneous measurements of IR and Raman spectra with a single device based on a single laser source. However, the spectral coverage was limited to ∼1000, which partially covers the spectral regions of the fundamental vibrations. In this work, we demonstrate a simple method to expand the spectral bandwidth of the CVS with a cascaded intra-pulse difference-frequency generation (IDFG). Using the system, we measure broadband CVS spectra of organic liquids spanning over 2000, more than double the previous study.
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http://dx.doi.org/10.1364/OL.444003 | DOI Listing |
Polymers (Basel)
December 2024
Faculty of Materials Engineering and Physics, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland.
Thermoplastic composites have garnered significant attention in various industries due to their exceptional properties, such as recyclability and ease of molding. In particular, biocomposites, which combine biopolymers with natural fibers, represent a promising alternative to petroleum-based materials, offering biodegradability and reduced environmental impact. However, there is limited knowledge regarding the efficacy of joining PLA/PHBV-based biocomposites modified with nanocrystalline cellulose (NCC) using vibration welding, which restricts their potential applications.
View Article and Find Full Text PDFEntropy (Basel)
November 2024
Faculty of Information Engineering, Quzhou College of Technology, Quzhou 324000, China.
Rolling bearings, as critical components of rotating machinery, significantly influence equipment reliability and operational efficiency. Accurate fault diagnosis is therefore crucial for maintaining industrial production safety and continuity. This paper presents a new fault diagnosis method based on FCEEMD multi-complexity low-dimensional features and directed acyclic graph LSTSVM.
View Article and Find Full Text PDFSci Rep
January 2025
College of Intelligent Equipment, Shandong University of Science and Technology, Taian, 271000, Shandong, China.
Coal-gangue recognition technology plays an important role in the intelligent realization of integrated working faces and coal quality improvement. However, the existing methods are easily affected by high dust, noise, and other disturbances, resulting in unstable recognition results that make it difficult to meet the needs of industrial applications. To realize accurate recognition of coal-gangue in noisy environments, this paper proposes an end-to-end multi-scale feature fusion convolutional neural network (MCNN-BILSTM) based gangue recognition method, which can automatically learn and fuse complementary information from multiple signal components of vibration signals.
View Article and Find Full Text PDFTalanta
December 2024
Department of Chemistry and Research Institute for Convergence of Basic Science, Hanyang University, Seoul, 04763, Republic of Korea. Electronic address:
This study explored convolutional autoencoder (CAE)-based feature extraction from entire two-trace two-dimensional (2T2D) correlation maps as a promising tool to enhance the accuracy of vibrational spectroscopy-based discriminant analysis. Although 2T2D correlation maps constructed using only a pair of spectra were effective to highlight minute spectral differences, there was an excessive number of features (variables). Thus, only slice spectra at a wavenumber chosen from the map were typically used for discriminant analysis.
View Article and Find Full Text PDFChem Soc Rev
December 2024
Hefei National Research Center for Physical Sciences at the Microscale, Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, and National Synchrotron Radiation Laboratory, School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, Anhui 230026, China.
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