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Chalcopyrite copper indium sulfide (CuInS 2 , CIS) has a bandgap that is optimal for a solar energy conversion material. In this paper, we used a polymer-type ion release source to control the precursor concentration of the hydrothermal system to grow CIS nanowires. The analytical results indicate that the reaction process is based on the formation of CuS binary compound, which is then followed by indium intercalation, which induces the formation of the CIS chalcopyrite crystal structure. The products were characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The CIS nanowires were 100–300 nm in diameter and 2–5 µm in length. [ABSTRACT FROM AUTHOR]

It has been demonstrated that by using doping and co-doping strategies the lifetimes as well as luminescence intensities of the doping species in the lanthanide oxysulfide nanoparticles (NPs) Ln 2 O 2 S:Ln’ 3+ (Ln=Gd, Tb, Eu; Ln׳=Tb, Eu, 1% and 5%) could be tuned. The lanthanide oxysulfide NPs, i.e., Gd 2 O 2 S, Tb 2 O 2 S and Gd 2 O 2 S:Tb 3+ (5%) were synthesized as matrices and doped with Eu 3+ (1% or 5%), by the thermal decomposition method and characterized by TEM, XRD, photoluminescence, cellular and in vivo animal imaging studies for potential luminescence bioimaging applications. Of these materials, Gd 2 O 2 S:Eu 3+ (5%) NPs possess the highest photo-stability and strongest luminescent intensity at 625 nm with a lifetime 853 μs in hexane. Surface modification of the Gd 2 O 2 S:Eu 3+ (5%) NPs with mPEG-APTES to increase its aqueous solubility resulted in almost complete luminescence quenching. Calcination of the host Gd 2 O 2 S:Eu 3+ (5%) NPs at 400 °C to increase their crystallinity and maintained some of their luminescence properties in aqueous solution. Further surface modification of the Gd 2 O 2 S:Eu 3+ (5%)-APTES NPs with mPEG and Alexa Fluor 660 allowed their effective cellular and in vivo animal luminescence imaging with low bio-toxicity. These novel imaging materials with tunable lifetimes would be potentially useful for luminescence bioimaging applications, particularly in the time-resolved, up-conversion, and/or multiplex modes. [ABSTRACT FROM AUTHOR]

A method of direction-of-arrival (DoA) estimation for FMCW (Frequency Modulated Continuous Wave) radar is presented. In addition to MUSIC, which is the popular high-resolution DoA estimation algorithm, deep learning has recently emerged as a very promising alternative. It is proposed in this paper to use a 3D convolutional neural network (CNN) for DoA estimation. The 3D-CNN extracts from the radar data cube spectrum features of the region of interest (RoI) centered on the potential positions of the targets, thereby capturing the spectrum phase shift information, which corresponds to DoA, along the antenna axis. Finally, the results of simulations and experiments are provided to demonstrate the superior performance, as well as the limitations, of the proposed 3D-CNN. [ABSTRACT FROM AUTHOR]