We present the first report on experimental observation of nonlinear spectral broadening in an all-solid photonic band gap Bragg fiber of relatively large mode area approximately 62 microm(2). The theoretically designed Bragg fiber for this specific application was fabricated by the well known MCVD technique. Nonlinear spectral broadening was observed by launching high power femtosecond pulses of 1067 nm pump wavelength. These first results indicate that fabrication of such Bragg fibers, once perfected, should potentially serve as an alternative route for realization of supercontinuum light.
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http://dx.doi.org/10.1364/OE.17.017130 | DOI Listing |
Sci Rep
January 2025
Department of Physics, TU Dortmund University, Otto-Hahn-Straße 4, 44227, Dortmund, Germany.
Time-resolved momentum microscopy is an emerging technique based on photoelectron spectroscopy for characterizing ultrafast electron dynamics and the out-of-equilibrium electronic structure of materials in the entire Brillouin zone with high efficiency. In this article, we introduce a setup for time-resolved momentum microscopy based on an energy-filtered momentum microscope coupled to a custom-made high-harmonic generation photon source driven by a multi-100 kHz commercial Yb-ultrafast laser that delivers fs pulses in the extreme ultraviolet range. The laser setup includes a nonlinear pulse compression stage employing spectral broadening in a Herriott-type bulk-based multi-pass cell.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
University of Toronto, Chemistry, 1265 Military Trail, M1C1A4, Toronto, CANADA.
The 2024 Zurich perfluorinated compounds (PFCs) summit reiterated the urgent need for non-selective analytical approaches for PFC detection. 19F NMR holds great potential, however, sensitivity limitations lead to long analysis times and/or the possibility of not detecting low concentration species. Steady State Free Precession (SSFP) NMR collects the signal in a steady state regime, allowing 100's of acquisitions in the timespan of a single traditional NMR scan.
View Article and Find Full Text PDFJ Pharm Sci
January 2025
Department of Chemical and Biomedical Engineering, FAMU-FSU College of Engineering, Tallahassee, FL, USA, 32310; Center for Interdisciplinary Magnetic Resonance, National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA, 32310. Electronic address:
Monoclonal antibodies (mAb) represent an important class of biologic therapeutics that can treat a variety of diseases including cancer, autoimmune disorders or respiratory conditions (e.g. COVID-19).
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Key Laboratory of the Ministry of Education for Advanced Catalysis Materials, Department of Chemistry, Zhejiang Normal University, Yingbin Road No.688, Jinhua, 321004, P. R. China.
Polycyclic multiple resonance (MR) molecules reveal narrowband emission, making them very promising emitters for high color purity display. Nevertheless, they still have challenges such as aggregation-induced emission quenching and spectral broadening. Overcoming these obstacles requires an in-depth understanding of the correlations among the alterations in their geometries, packing structures, and molecular vibrations and their corresponding changes in their photoluminescence (PL) properties.
View Article and Find Full Text PDFBioinformatics
January 2025
Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, W12 0NN, United Kingdom.
Unlabelled: Metabolomics extensively utilizes Nuclear Magnetic Resonance (NMR) spectroscopy due to its excellent reproducibility and high throughput. Both one-dimensional (1D) and two-dimensional (2D) NMR spectra provide crucial information for metabolite annotation and quantification, yet present complex overlapping patterns which may require sophisticated machine learning algorithms to decipher. Unfortunately, the limited availability of labeled spectra can hamper application of machine learning, especially deep learning algorithms which require large amounts of labelled data.
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