We report the synthesis of quaternary CuIn
x
Ga1−x
S2 (0 ≤ x ≤1) chalcopyrite nanoparticles from decomposition of two molecular single source precursors (SSPs), (Ph3P)2Cu(μ-SEt)2In(SEt)2 (1) and (Ph3P)2Cu(μ-SEt)2Ga(SEt)2 (2), via microwave irradiation. We were able to precisely control stoichiometry and bandgaps of quaternary CuIn
x
Ga1−x
S2 nanoparticles ranging from 1.40 to 2.30 eV.
Raman spectroscopy is evaluated as a spectroscopic method for identification of common household plastics for recycling purposes. The methods of K-nearest neighbor (KNN), cyclic subspace regression (CSR), and library searching are compared for computerized plastic classification. Plastics studied consist of polyethylene terephthalate, high-density polyethylene, polyvinyl chloride, low-density polyethylene, polypropylene, and polystyrene. With principal component analysis (PCA), visual distinction between the different plastics becomes possible. Correct class membership to all six plastic types is provided by KNN. To date, all development and uses of CSR have been based on building models for each prediction property analogous to the form of partial least-squares known as PLS1. Cyclic subspace regression is modified in this paper to also allow modeling of multiple properties, as does PLS2. The new form of CSR was able to correctly classify all six plastic types when seven-factor models were used. This paper reports that key observations made in comparing PCR to PLS1 are verified for the interrelationships of PCR and PLS2 models. Most notable is that even though PLS2 uses spectral responses and plastic identifications to form factors, PLS2 eigenvector weights are not much different from PCR eigenvector weights where PCR only uses spectral responses to form eigenvector weights. Library searching showed less significant results than KNN and CSR. Regardless of the identification approach, polyethylene samples could be identified as either being high density or low density with the use of Raman spectroscopy.
The properties of 60-μm thick Ultra-Fast Silicon Detectors (UFSD) detectors manufactured by Fondazione Bruno Kessler (FBK), Trento (Italy) were tested before and after irradiation with minimum ionizing particles (MIPs) from a 90 Sr β-source. This FBK production, called UFSD2, has UFSDs with gain layer made of Boron, Boron low-diffusion, Gallium, carbonated Boron and carbonated Gallium. The irradiation with neutrons took place at the TRIGA reactor in Ljubljana, while the proton irradiation took place at CERN SPS. The sensors were exposed to a neutron fluence of 4•10 14 , 8•10 14 , 1.5•10 15 , 3•10 15 , 6•10 15 n eq /cm 2 and to a proton fluence of 9.6•10 14 p/cm 2 , equivalent to a fluence of 6•10 14 n eq /cm 2 . The internal gain and the timing resolution were measured as a function of bias voltage at -20 o C. The timing resolution was extracted from the time difference with a second calibrated UFSD in coincidence, using the constant fraction method for both.
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