Near-infrared (NIR) phosphor-converted light-emitting diode (pc-LED) has emerged as the most promising NIR light source, highlighting the importance of exploring phosphors with excellent efficiency and sufficient spectral coverage. Herein, a garnet NaCaHfGeO:Cr phosphor with an internal quantum efficiency (IQE) of 79.2% has been developed, which exhibits a relatively long wavelength NIR emission peak at 830 nm and a full width at half maximum (FWHM) of 144 nm. Moreover, the emission peak can be gradually tuned to 903 nm with an emission intensity maintaining over 60% utilizing a chemical unit co-substitution strategy. Thus, the developed material in this work has an excellent efficiency with a relatively long wavelength NIR emission and wide-range spectral tunability, being promising for multifunctional spectroscopy applications.
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http://dx.doi.org/10.1364/OL.539857 | DOI Listing |
Neural Netw
January 2025
Department of Mathematics, Southern Methodist University, Dallas, 75275, TX, USA. Electronic address:
In this paper, we derive diffusion equation models in the spectral domain to study the evolution of the training error of two-layer multiscale deep neural networks (MscaleDNN) (Cai and Xu, 2019; Liu et al., 2020), which is designed to reduce the spectral bias of fully connected deep neural networks in approximating oscillatory functions. The diffusion models are obtained from the spectral form of the error equation of the MscaleDNN, derived with a neural tangent kernel approach and gradient descent training and a sine activation function, assuming a vanishing learning rate and infinite network width and domain size.
View Article and Find Full Text PDFPlant Cell Environ
January 2025
Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India.
The generation of spectral libraries using hyperspectral data allows for the capture of detailed spectral signatures, uncovering subtle variations in plant physiology, biochemistry, and growth stages, marking a significant advancement over traditional land cover classification methods. These spectral libraries enable improved forest classification accuracy and more precise differentiation of plant species and plant functional types (PFTs), thereby establishing hyperspectral sensing as a critical tool for PFT classification. This study aims to advance the classification and monitoring of PFTs in Shoolpaneshwar wildlife sanctuary, Gujarat, India using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and machine learning techniques.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Mathematical, Physical and Computer Sciences, University of Parma, Viale delle Scienze 7/A, 43124 Parma, Italy.
Electrical contacts are of the greatest importance as they decisively contribute to the overall performance of photoresistors. Undoped κ-GaO is an ideal material for photoresistors with high performance in the UV-C spectral region thanks to its intrinsic solar blindness and extremely low dark current. The quality assessment of the contact/κ-GaO interface is therefore of paramount importance.
View Article and Find Full Text PDFJ Phys Chem A
January 2025
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States.
We present direct frequency comb cavity ring-down spectroscopy with Vernier filtering as a straightforward approach to sensitive and multiplexed trace gas detection. The high finesse cavity acts both to extend the interaction length with the sample and as a spectral filter, alleviating the need for dispersive elements or an interferometer. In this demonstration, a free running interband cascade laser was used to generate a comb centered at 3.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island, United States of America.
Negotiating social dynamics among allies and enemies is a complex problem that often requires individuals to tailor their behavioral approach to a specific situation based on environmental and/or social factors. One way to make these contextual adjustments is by arranging behavioral output into intentional patterns. Yet, few studies explore how behavioral patterns vary across a wide range of contexts, or how allies might interlace their behavior to produce a coordinated response.
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