Influence of α′‐/α‐crystal polymorphism on properties of poly(l‐lactic acid)

Poly(l ‐lactic acid) (PLLA) is a biodegradable and biocompatible thermoplastic polyester produced from renewable sources, widely used for biomedical devices, in food packaging and in agriculture. It is a semicrystalline polymer, and as such its properties are strongly affected by the developed semicrystalline morphology. As a function of the crystallization temperature, PLLA can form different crystal modifications, namely α′‐crystals below about 120 °C and α‐crystals at higher temperatures. The α′ modification is therefore of special importance as it may be the preferred polymorph developing at processing‐relevant conditions. It is a metastable modification which typically transforms into the more stable α‐crystals on annealing at elevated temperature. The structure, kinetics of formation and thermodynamics of α′‐ and α‐crystals of PLLA are reviewed in this contribution, together with the effect of α′‐/α‐crystal polymorphism on the properties of PLLA. © 2018 Society of Chemical Industry     

In Vivo Albumin-Binding of a C-Functionalized Cyclam Platform for 64Cu-PET/CT Imaging in Breast Cancer Model

An improved glucose-chelator-albumin bioconjugate (GluCAB) derivative, GluCAB-2^Mal, has been synthesized and studied for in vivo ⁶⁴Cu-PET/CT imaging in breast cancer mice models together with its first-generation analogue GluCAB-1^Mal. The radioligand works on the principle of tumor targeting through the enhanced permeability and retention (EPR) effect with a supportive role played by glucose metabolism. [⁶⁴Cu]Cu-GluCAB-2^Mal (99 % RCP) exhibited high serum stability with immediate binding to serum proteins. In vivo experiments for comparison between tumor targeting of [⁶⁴Cu]Cu-GluCAB-2^Mal and previous-generation [⁶⁴Cu]Cu-GluCAB-1^Mal encompassed microPET/CT imaging and biodistribution analysis in an allograft E0771 breast cancer mouse model. Tumor uptake of [⁶⁴Cu]Cu-GluCAB-2^Mal was clearly evident with twice as much accumulation as compared to its predecessor and a tumor/muscle ratio of up to 5 after 24 h. Further comparison indicated a decrease in liver accumulation for [⁶⁴Cu]Cu-Glu-CAB-2^Mal.     

Analysis of Temperature Effect in Quadruple Gate Nano-scale FinFET

Silicon - Quadruple gate FinFET is a promising candidate among other multi-gate MOS devices due to it’s better scalability and higher short channel effect suppression capability in advanced...     

κ-Opioid Signaling in the Lateral Hypothalamic Area Modulates Nicotine-Induced Negative Energy Balance

Several studies have reported that nicotine, the main bioactive component of tobacco, exerts a marked negative energy balance. Apart from its anorectic action, nicotine also modulates energy expenditure, by regulating brown adipose tissue (BAT) thermogenesis and white adipose tissue (WAT) browning. These effects are mainly controlled at the central level by modulation of hypothalamic neuropeptide systems and energy sensors, such as AMP-activated protein kinase (AMPK). In this study, we aimed to investigate the kappa opioid receptor (κOR)/dynorphin signaling in the modulation of nicotine’s effects on energy balance. We found that body weight loss after nicotine treatment is associated with a down-regulation of the κOR endogenous ligand dynorphin precursor and with a marked reduction in κOR signaling and the p70 S6 kinase/ribosomal protein S6 (S6K/rpS6) pathway in the lateral hypothalamic area (LHA). The inhibition of these pathways by nicotine was completely blunted in κOR deficient mice, after central pharmacological blockade of κOR, and in rodents where κOR was genetically knocked down specifically in the LHA. Moreover, κOR-mediated nicotine effects on body weight do not depend on orexin. These data unravel a new central regulatory pathway modulating nicotine’s effects on energy balance.     

Authenticity green coffee bean species and geographical origin using near-infrared spectroscopy combined with chemometrics

To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Structural Aspects of P2-Type Na0.67Mn0.6Ni0.2Li0.2O2 (MNL) Stabilization by Lithium Defects as a Cathode Material for Sodium-Ion Batteries

A known strategy for improving the properties of layered oxide electrodes in sodium-ion batteries is the partial substitution of transition metals by Li. Herein, the role of Li as a defect and its impact on sodium storage in P2-Na_0.67Mn_0.6Ni_0.2Li_0.2O₂ is discussed. In tandem with electrochemical studies, the electronic and atomic structure are studied using solid-state NMR, operando XRD, and density functional theory (DFT). For the as-synthesized material, Li is located in comparable amounts within the sodium and the transition metal oxide (TMO) layers. Desodiation leads to a redistribution of Li ions within the crystal lattice. During charging, Li ions from the Na layer first migrate to the TMO layer before reversing their course at low Na contents. There is little change in the lattice parameters during charging/discharging, indicating stabilization of the P2 structure. This leads to a solid-solution type storage mechanism (sloping voltage profile) and hence excellent cycle life with a capacity of 110 mAh g^-1 after 100 cycles. In contrast, the Li-free compositions Na_0.67Mn_0.6Ni_0.4O₂ and Na_0.67Mn_0.8Ni_0.2O₂ show phase transitions and a stair-case voltage profile. The capacity is found to originate from mainly Ni³⁺/Ni⁴⁺ and O^2-/O^2-δ redox processes by DFT, although a small contribution from Mn⁴⁺/Mn⁵⁺ to the capacity cannot be excluded.     

Influence of SiC microstructure on its corrosion behavior in molten FLiNaK salt

The influence of the microstructure on the corrosion rate of three monolithic SiC samples in FLiNaK salt at 900 °C for 250 h was studied. The SiC samples, labeled as SiC-1, SiC-2, and SiC-3, had corrosion rates of 0.137, 0.020, and 0.043 mg/cm²h, respectively. Compared with grain size and the presence of special grain boundaries (i.e., Σ3), the content of high-angle grain boundaries (HAGBs) appeared to have the strongest influence on the corrosion rate of SiC in FLiNaK salt, since the corrosion rate increased six times as the concentration of high-angle grain boundaries increased from 19 to 32% for SiC-2 and SiC-1, respectively. These results stress the importance of controlling the content of HAGBs during the production process of SiC.     

Dual effect synergistically triggered Ce:(Y,Tb)3(Al,Mn)5O12 transparent ceramics enabling a high color-rendering index and excellent thermal stability for white LEDs

Ce:Y₃Al₅O₁₂ transparent ceramics (TCs) with appropriate emission light proportion and high thermal stability are significant to construct white light emitting diode devices with excellent chromaticity parameters. In this work, strategies of controlling crystal-field splitting around Ce³⁺ ion and doping orange-red emitting ion, were adopted to fabricate Ce:(Y,Tb)₃(Al,Mn)₅O₁₂ TCs via vacuum sintering technique. Notably, 85.4 % of the room-temperature luminescence intensity of the TC was retained at 150 °C, and the color rendering index was as high as 79.8. Furthermore, a 12 nm red shift and a 16.2 % increase of full width at half maximum were achieved owing to the synergistic effects of Tb³⁺ and Mn²⁺ ions. By combining TCs with a 460 nm blue chip, a warm white light with a low correlated color temperature of 4155 K was acquired. Meanwhile, the action mechanism of Tb³⁺ ion and the energy transfer between Ce³⁺ and Mn²⁺ ions were verified in prepared TCs.     

Corrosion behavior of T24, T92, VM12, and AISI 304 steels exposed to KCl–NaCl–K2SO4–Na2SO4 salt mixtures

The corrosion mechanisms of T24, T92, VM12, and AISI 304 steels are studied under the influence of NaCl–KCl, NaCl–Na₂SO₄, and KCl–K₂SO₄ salt mixtures in a dry air atmosphere at 650°C for 15 days. NaCl–KCl was the most aggressive deposit and AISI 304 stainless steel exhibited the highest corrosion resistance. There was no relation between the Cr content of the ferritic steels and their corrosion resistance in NaCl–KCl. In contrast, the resistance of high-Cr steels was better when exposed to NaCl–Na₂SO₄ and KCl–K₂SO₄. The high-Cr and the low-Cr steels were more susceptible to NaCl–Na₂SO₄ and to KCl–K₂SO₄, respectively.