Structure and crystallization behavior of complex mold flux glasses in the system CaO-Na2O-Li2O-CaF2-B2O3-SiO2: A multi-nuclear NMR spectroscopic study

The structure of mold flux glasses in the system CaO-(Na,Li)₂O-SiO₂-CaF₂ with unusually high modifier contents, stabilized by the addition of ∼4 mol% B₂O₃, is studied using ⁷Li, ²³Na, ¹⁹F, ¹¹B, and ²⁹Si magic-angle-spinning (MAS), and ⁷Li{¹⁹F} and ²³Na{¹⁹F} rotational echo double-resonance (REDOR) nuclear magnetic resonance (NMR) spectroscopy. When taken together, the spectroscopic results indicate that the structure of these glasses consists primarily of dimeric [Si₂O₇]⁻⁶ units that are linked to the (Ca,Na,Li)-O coordination polyhedra, and are interspersed with chains of corner-shared BO₃ units. The F atoms in the structure are exclusively bonded to Ca atoms, forming Ca(O,F)_n coordination polyhedra. This structural scenario is shown to be consistent with the crystallization of cuspidine (3CaO·2SiO₂·CaF₂) from the parent melts on slow supercooling. The progressive addition of Li to a Na-containing base composition results in a corresponding increase in the undercooling required for the nucleation of cuspidine in the melt, which is attributed to the frustrated local structure caused by the mixing of alkali ions.     

Dynamic Oscillation via Negative Differential Resistance in Type III Junction Organic/Two-Dimensional and Oxide/Two-Dimensional Transition Metal Dichalcogenide Diodes

Among many of 2D semiconductor-based devices, type III PN junction diodes are given special attentions due to their unique function, negative differential resistance (NDR). However, it has been found uneasy to achieve well-matched type III PN junctions from 2D–2D van der Waals heterojunctions. Here, the authors present other alternatives of type III heterojunctions, using 2D p-MoTe₂/organic n-type dipyrazino[2,3-f:2′,3′-h]quinoxaline-2,3,6,7,10,11-hexacarbonitrile (HAT-CN) and 2D p-WSe₂/n-MoO_x systems. Those junction diodes appear to well-demonstrate static and dynamic NDR behavior via resonant tunneling and electron–hole recombination. Extended to an inverter circuit, p-MoTe₂/n-HAT-CN diode enables multilevel inverter characteristics as monolithically integrated with p-MoTe₂ channel field effect transistor. The same NDR diode shows dynamic LC oscillation behavior under a constant DC voltage, connected to an external inductor. From p-WSe₂/n-MoO_x oxide diode, similar NDR behavior to those of p-MoTe₂/n-HAT-CN is again observed along with LC oscillations. The authors attribute these visible oscillation results to high peak-to-valley current ratios of their organic or oxide/2D heterojunction diodes.     

Approaching Ultrastable High‐Rate Li–S Batteries through Hierarchically Porous Titanium Nitride Synthesized by Multiscale Phase Separation

Porous architectures are important in determining the performance of lithium–sulfur batteries (LSBs). Among them, multiscale porous architecutures are highly desired to tackle the limitations of single‐sized porous architectures, and to combine the advantages of different pore scales. Although a few carbonaceous materials with multiscale porosity are employed in LSBs, their nonpolar surface properties cause the severe dissolution of lithium polysulfides (LiPSs). In this context, multiscale porous structure design of noncarbonaceous materials is highly required, but has not been exploited in LSBs yet because of the absence of a facile method to control the multiscale porous inorganic materials. Here, a hierarchically porous titanium nitride (h‐TiN) is reported as a multifunctional sulfur host, integrating the advantages of multiscale porous architectures with intrinsic surface properties of TiN to achieve high‐rate and long‐life LSBs. The macropores accommodate the high amount of sulfur, facilitate the electrolyte penetration and transportation of Li⁺ ions, while the mesopores effectively prevent the LiPS dissolution. TiN strongly adsorbs LiPS, mitigates the shuttle effect, and promotes the redox kinetics. Therefore, h‐TiN/S shows a reversible capacity of 557 mA h g^?1 even after 1000 cycles at 5 C rate with only 0.016% of capacity decay per cycle.     

Quasi-static compressive behaviour of aluminium cenosphere syntactic foams

In this paper, cenosphere particles embedded in AA2014 aluminium matrix are used to fabricate syntactic foam by stir casting method. The particle size is about 100?µm and foam density is about 1990?kg?m^?3. Compression tests at strain rate 0.001/s are performed on foam samples to characterise their mechanical properties which are then used in numerical analysis on commercial finite element analysis software ABAQUS/CAE with isotropic elastic-plastic material model. Experimental and numerical results show good conformity in deformation behaviour with elastic and plateau zones showing average deviations less than 5% and 20%, respectively. Foams showed high yield stress and energy absorption capabilities that can be useful in making blast and impact resistant structures.     

Solution‐Processable Photonic Inks of Mie‐Resonant Hollow Carbon–Silica Nanospheres

Hollow carbon–silica nanospheres that exhibit angle‐independent structural color with high saturation and minimal absorption are made. Through scattering calculations, it is shown that the structural color arises from Mie resonances that are tuned precisely by varying the thickness of the shells. Since the color does not depend on the spatial arrangement of the particles, the coloration is angle independent and vibrant in powders and liquid suspensions. These properties make hollow carbon–silica nanospheres ideal for applications, and their potential in making flexible, angle‐independent films and 3D printed films is explored.     

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.     

Reliability measure approach for confidence-based design optimization under insufficient input data

Structural and Multidisciplinary Optimization - In most of the reliability-based design optimization (RBDO) researches, accurate input statistical model has been assumed to concentrate on the...     

Succinct Palette and Color Model Generation and Manipulation Using Hierarchical Representation

We propose a new method to obtain the representative colors and their distributions of an image. Our intuition is that it is possible to derive the global model from the local distributions. Beginning by sampling pure colors, we build a hierarchical representation of colors in the image via a bottom‐up approach. From the resulting hierarchy, we can obtain satisfactory palettes/color models automatically without a predefined size. Furthermore, we provide interactive operations to manipulate the results which allow the users to reflect their intention directly. In our experiment, we show that the proposed method produces more succinct results that faithfully represent all the colors in the image with an appropriate number of components. We also show that the proposed interactive approach can improve the results of applications such as recoloring and soft segmentation.     

Automated delineation of non-small cell lung cancer: A step toward quantitative reasoning in medical decision science

Quantitative reasoning in medical decision science relies on the delineation of pathological objects. For example, evidence-based clinical decisions regarding lung diseases require the segmentation of nodules, tumors, or cancers. Non-small cell lung cancer (NSCLC) tends to be large sized, irregularly shaped, and grows against surrounding structures imposing challenges in the segmentation, even for expert clinicians. An automated delineation tool based on spatial analysis was developed and studied on 25 sets of computed tomography scans of NSCLC. Manual and automated delineations were compared, and the proposed method exhibited robustness in terms of the tumor size (5.32–18.24 mm), shape (spherical or irregular), contouring (lobulated, spiculated, or cavitated), localization (solitary, pleural, mediastinal, endobronchial, or tagging), and laterality (left or right lobe) with accuracy between 80% and 99%. Small discrepancies observed between the manual and automated delineations may arise from the variability in the practitioners' definitions of region of interest or imaging artifacts that reduced the tissue resolution.     

Brief Review of Precipitated Iron-Based Catalysts for Low-Temperature Fischer–Tropsch Synthesis

Topics in Catalysis - Fischer–Tropsch synthesis (FTS) is a promising way to produce clean liquid fuels and high value-added chemicals from low-value carbon-containing resources such as coal,...