Nanocrystalline semiconductors: synthesis, properties, and perspectives

The preparation of hollow particles of ZnO by calcination of hydrozincite coated poly(styrene) beads is reported. Synthetic studies have been performed on such polymer/inorganic composite precursors in order to establish the optimum conditions for the preparation of the ZnO particles. The morphological properties of the powders were characterised by optical microscopy and scanning electron microscopy. The micrometric ZnO particles show morphological characteristics related to the template used in their preparation

Aerosol-assisted metallo-organic chemical vapour deposition of Bi2Se3 films using single-molecule precursors: the crystal structure of bismuth(m) dibutyldiselenocarbamate

The complexes [Bi{Se2CN(C2H5)2}3], [Bi{Se2CN(C4H9)2}3], [Bi{Se2CN(CH3)(C4H9)}3] and [Bi{Se2CN(CH3)(C6H13)}3] have been synthesized and characterized structurally using IR, 1H and 13C NMR. In addition, the crystal structure of [Bi{Se2CN(C4H9)2}3] was determined by single-crystal X-ray diffraction, showing the bismuth centre coordinated to three dialkyldiselenocarbamate ligands through the selenium donor atoms. The Bi(III) compounds were used as precursors for the deposition of Bi2Se3 films on glass substrates through aerosol-assisted metallo-organic chemical vapour deposition (AA-MOCVD)

Biased cosmological parameter estimation with galaxy cluster counts in the presence of primordial non-Gaussianities

The redshift dependence of the abundance of galaxy clusters is very sensitive to the statistical properties of primordial density perturbations. It can thus be used to probe small deviations from Gaussian initial conditions. Such deviations constitute a very important signature of many inflationary scenarios, and are thus expected to provide crucial information on physical processes which took place in the very early Universe. We have determined the biases which may be introduced in the estimation of cosmological parameters by wrongly assuming the absence of primordial non-Gaussianities. Although we find that the estimation of the present-day dark energy density using cluster counts is not very sensitive to the non-Gaussian properties of the density field, we show that the biases can be considerably larger in the estimation of the dark energy equation of state parameter $w$ and of the amplitude of the primordial density perturbations. Our results suggest that a significant level of non-Gaussianity at cluster scales may be able to reconcile the constraint on the amplitude of the primordial perturbations obtained using galaxy cluster number counts from the Planck Sunyaev-Zeldovich Catalog with that obtained from the primary Cosmic Microwave Background anisotropies measured by the Planck satellite.Comment: 4 pages, 1 figur

Recovery and Purification of (Bio)Pharmaceuticals Using (Nano)Materials

Biopharmaceuticals main classes comprise recombinant proteins, antibodies, and nucleic-acid-derived products, while synthetic pharmaceuticals include a wide variety of organic compounds. The purification of (bio)pharmaceuticals, as part of downstream processing, is mainly carried out by chromatographic processes, which are responsible for the therapeutics high cost. Therefore, there is a crucial need on the development of novel and more efficient separation/purification processes or on the improvement of the current chromatographic-based ones, aiming at producing pharmaceuticals of high quality and at a lower cost. Amongst alternative techniques, it has been demonstrated that inorganic or organic (nano)particles, used in solid-phase extraction approaches, may be promising for the purification of (bio)pharmaceuticals. This chapter provides an overview on solid-liquid separation/purification processes used to obtain high purity and high quality pharmaceuticals. The main purification processes are described and summarized. The areas where there has been a sustainable progress, combined with improved therapeutic characteristics, are highlighted. Materials based on silica (nano)particles, carbon-based (nano)particles (carbon nanotubes, graphene and activated carbon) and magnetic (nano)particles are overviewed. Based on the reported results, nanotechnology may play a key role in future pharmaceutical developments and manufacturing, where the design of suitable functionalized (nano)particles is a crucial factor to enhance the selectivity and to obtain high purification and recovery yields of (bio)pharmaceuticals.publishe

EUS assessment for intermediate risk of choledocholithiasis after a negative magnetic resonance cholangiopancreatography

© 2020 SPRING MEDIA PUBLISHING CO. LTD | PUBLISHED BY WOLTERS KLUWER - MEDKNOW 291. Background and Aims: Guidelines recommend either EUS or magnetic resonance cholangiopancreatography (MRCP) for intermediate risk of choledocholithiasis. There is a lack of evidence that supports proceeding with EUS if the MRCP is negative and if clinical suspicion still exists. Methods: This is a retrospective study of all patients who underwent EUS to assess for choledocholithiasis at a tertiary care referral center from July 2013 to October 2019. Results: A total of 593 patients underwent EUS for evaluation for choledocholithiasis. Of the 593 patients, 35.2% (209/593) had an MRCP. 73.2% (153/209) had a negative MRCP while 26.8% (56/209) had a positive MRCP. Of the group of patients who underwent EUS with a negative MRCP, 15% (23/153) were positive for choledocholithiasis on EUS. Of these, 91% (21/23) were also positive for sludge or stones on endoscopic retrograde cholangiopancreatography and thus 14% (21/153) of the EUS were \u27true positives.\u27 There were no clinical or laboratory factors predictive of choledocholithiasis on univariate analysis in the EUS plus negative MRCP group. When further analyzing the MRCP negative group into MRCP-/EUS+ and MRCP-/EUS-subgroups, a total bilirubin \u3e3 mg/dL predicted a bile duct stone (55% vs. 32%, P = 0.05). Conclusion: The diagnostic yield of EUS for suspected choledocholithiasis in the setting of a negative MRCP is 14% in our cohort. EUS should be considered in patients with intermediate risk of choledocholithiasis with a negative MRCP if the clinical suspicion is still present, and especially if the total bilirubin is above 3 mg/dL

Cosmic Ray Cherenkov and Fluorescence Imaging: Photosensors and data acquisition systems for a new generation of focal planes

In this paper the design of a new generation of focal planes for Imaging Atmospheric Cherenkov and Fluorescence Telescopes is discussed, based on a Digital Photon Counting architecture instrumented with (SiPM) Silicon Photomultipliers. 3 × 3mm2 SiPMs were chosen to minimize the photoelectron pile-up within intervals shorter than the clock sampling time. The large number of channels requires a compact, modular design with minimal cabling and distance between the photosensors and the frontend electronics. Other design requirements are a high reliability, easy field maintenance and minimization of the total power budget. Data acquisition electronics are partitioned in on-board frontend and off-detector high-level trigger electronics. Extensive use of mixed-signal ASICs and low-power FPGAs for early data reduction were adopted. Temperature is controlled by a liquid cooling sub-system. An asynchronous data readout and filtering, where each of the trigger levels works at its own clock frequency is adopted. The off-detector data acquisition and trigger architecture is based on an asynchronous multi-gigabit switching approach implemented over standard MicroTCA boards, equipped with optical interfaces and high-capability FPGAs. The boards are connected by multi-Gbps optical links to the frontend electronics. Trigger primitives are sent asynchronously to the MicroTCA trigger boards via data links running at their own clocks, for maximum bandwidth. Data and slow-control data streams are sent over the same data lines, reducing in this way the number of cables required. Each crate can process up to 4 × 104 channels and the modularity offered allows further expansion by inter-connecting additional crates with optical fiber links

Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach

The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).Comment: 16 pages, 12 figures, accepted for publication in MNRA