Re-examination of phase relations between solid solutions in R4Al2O9-R4Si2N2O7-R4Si2O10 (R=Y,Gd, Yb) systems

Samples in Si–Al-R-O-N (R = Y, Gd, Yb) systems were prepared by solid-state reactions using R₂O₃, Al₂O₃, SiO₂ and Si₃N₄ powders as starting materials. X-ray diffraction was done to investigate RAM-J(R) solid solutions [RAM = R₄Al₂O₉, J(R) = R₄Si₂N₂O₇] formation and their equilibrium with RSO (R₄Si₂O₁₀). Phase relations between RAM, J(R) and RSO at 1700 °C were summarized in a phase diagram. It was determined that a limited solid solution of RAM and RSO could be formed along RAM-RSO tie-line, while RAM and J(R) form a continuous solid solution along RAM-J(R) tie-line. In RAM-J(R)-RSO ternary systems, the RAM-J(R) tie-lines were extended towards the RSO corner to form a continuous solid solution area of JRAMss (R = Y, Gd, Yb). The established phase relations in the Si–Al-R-O-N (R = Y, Gd, Yb) systems may facilitate compositional selections for developing JRAMss as monolithic ceramics or for SiC/Si₃N₄ based composites using the solid-solutions as a second refractory phase.     

Underwater image super-resolution using multi-stage information distillation networks

Recently, single image super-resolution (SISR) has been widely applied in the fields of underwater robot vision and obtained remarkable performance. However, most current methods generally suffered from the problem of a heavy burden on computational resources with large model sizes, which limited their real-world underwater robotic applications. In this paper, we introduce and tackle the super resolution (SR) problem for underwater robot vision and provide an efficient solution for near real-time applications. We present a novel lightweight multi-stage information distillation network, named MSIDN, for better balancing performance against applicability, which aggregates the local distilled features from different stages for more powerful feature representation. Moreover, a novel recursive residual feature distillation (RRFD) module is constructed to progressively extract useful features with a modest number of parameters in each stage. We also propose a channel interaction & distillation (CI&D) module that employs channel split operation on the preceding features to produce two-part features and utilizes the inter channel-wise interaction information between them to generate the distilled features, which can effectively extract the useful information of current stage without extra parameters. Besides, we present USR-2K dataset, a collection of over 1.6K samples for large-scale underwater image SR training, and a testset with an additional 400 samples for benchmark evaluation. Extensive experiments on several standard benchmark datasets show that the proposed MSIDN can provide state-of-the-art or even better performance in both quantitative and qualitative measurements.     

WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

Portrait of Cancer Stem Cells on Colorectal Cancer: Molecular Biomarkers,Signaling Pathways and miRNAome

Colorectal cancer (CRC) is a leading cause of cancer death worldwide, and about 20% is metastatic at diagnosis and untreatable. Increasing evidence suggests that the heterogeneous nature of CRC is related to colorectal cancer stem cells (CCSCs), a small cells population with stemness behaviors and responsible for tumor progression, recurrence, and therapy resistance. Growing knowledge of stem cells (SCs) biology has rapidly improved uncovering the molecular mechanisms and possible crosstalk/feedback loops between signaling pathways that directly influence intestinal homeostasis and tumorigenesis. The generation of CCSCs is probably connected to genetic changes in members of signaling pathways, which control self-renewal and pluripotency in SCs and then establish function and phenotype of CCSCs. Particularly, various deregulated CCSC-related miRNAs have been reported to modulate stemness features, controlling CCSCs functions such as regulation of cell cycle genes expression, epithelial-mesenchymal transition, metastasization, and drug-resistance mechanisms. Primarily, CCSC-related miRNAs work by regulating mainly signal pathways known to be involved in CCSCs biology. This review intends to summarize the epigenetic findings linked to miRNAome in the maintenance and regulation of CCSCs, including their relationships with different signaling pathways, which should help to identify specific diagnostic, prognostic, and predictive biomarkers for CRC, but also develop innovative CCSCs-targeted therapies.     

Non-Platinum Group Metal Electrocatalysts toward Efficient Hydrogen Oxidation Reaction

Developing non-platinum group metal (non-PGM) electrocatalysts for the hydrogen oxidation reaction (HOR) represents the efforts towards the more economical use of hydrogen fuel cells and hydrogen energy, which has attracted tremendous attention recently. However, non-PGM electrocatalysts for the HOR are still in their early development stages as compared with the significant advances in those for the oxygen reduction reaction and hydrogen evolution reaction. Herein, this paper summarizes the recent progresses and highlights the key challenges for the rational design of non-PGM electrocatalysts, aiming to promote the development of non-PGM HOR electrocatalysts. Fundamental understandings of the HOR mechanism are firstly reviewed, where theoretical interpretations on the low HOR kinetics in alkaline media, including the hydrogen binding energy theory, the bifunctional mechanism, and the water molecule reorganization, are particularly discussed. Subsequently, progresses of typical non-PGM HOR electrocatalysts in acid and alkaline media are summarized separately. For the HOR under alkaline conditions, the superiorities and challenges of Ni-based catalysts are discussed with a particular focus as they are the most promising non-PGM electrocatalysts. Finally, this paper highlights the challenges and provide perspectives on the future development directions of non-PGM HOR electrocatalysts.     

Electrochemical performance of in situ LiFePO4 modified by N-doped graphene for Li-ion batteries

LiFePO₄ modified by N-doped graphene (NG) with a three-dimensional conductive network structure was synthesized via a one-step in situ hydrothermal method. The effects of N amount of NG on the phase structure, morphology, and electrochemical properties of LiFePO₄ are investigated in this study. X-ray diffraction (XRD) results show that doping suitable N amounts in NG do not alter the crystal structure of LiFePO_4, and scanning electron microscopy (SEM) images show that NG can slightly reduce the particle size of LiFePO₄. The high-resolution transmission electron microscopy (HRTEM) results show that the LiFePO₄ particles are well covered and connected by NG. The electrochemical performance confirms that LiFePO₄ modified by 20% N-doped graphene (named LFP/NG-4) displays a perfect specific capacity of 166.6 mAh·g^?1 at a rate of 0.2C and can reach 125 mAh·g^?1 at a rate of 5 C. Electrochemical impedance spectroscopy (EIS) results illustrate that the charge transfer resistance value of the LFP/NG-4 composite is only 58.6 Ω, which is very low compared with LiFePO₄. Cyclic voltammetry (CV) tests indicate that the addition of 20% N-doped graphene can effectively reduce electrode polarization and improve reversibility. The LFP/NG-4 composite with a three-dimensional conductive network structure can be regarded as a promising cathode material for Li-ion batteries.     

New insights into the mechanisms of carbon dioxide mineralization by portlandite

Portlandite (Ca(OH)₂; also known as calcium hydroxide or hydrated lime), an archetypal alkaline solid, interacts with carbon dioxide (CO₂) via a classic acid–base “carbonation” reaction to produce a salt (calcium carbonate: CaCO₃) that functions as a low-carbon cementation agent, and water. Herein, we revisit the effects of reaction temperature, relative humidity (RH), and CO₂ concentration on the carbonation of portlandite in the form of finely divided particulates and compacted monoliths. Special focus is paid to uncover the influences of the moisture state (i.e., the presence of adsorbed and/or liquid water), moisture content and the surface area-to-volume ratio (s_a/v, mm⁻¹) of reactants on the extent of carbonation. In general, increasing RH more significantly impacts the rate and thermodynamics of carbonation reactions, leading to high(er) conversion regardless of prior exposure history. This mitigated the effects (if any) of allegedly denser, less porous carbonate surface layers formed at lower RH. In monolithic compacts, microstructural (i.e., mass-transfer) constraints particularly hindered the progress of carbonation due to pore blocking by liquid water in compacts with limited surface area to volume ratios. These mechanistic insights into portlandite's carbonation inform processing routes for the production of cementation agents that seek to utilize CO₂ borne in dilute (≤30 mol%) post-combustion flue gas streams.     

Effect of Zr addition on the interfacial reaction of the SiC joint brazed by Inconel 625 powder filler

Ni-based alloys are believed to be the most suitable brazing fillers for SiC ceramic application in a nuclear environment. However, graphite, which severely deteriorates the mechanical property of the joint, is inevitable when Ni reacts with SiC. In this paper, Different amounts of Zr powders are mixed with Inconel 625 powders to braze SiC at 1400 °C. When Zr addition reaches 40 wt%, the brazed seam confirms the absence of graphite. This research proves that Zr can avoid the graphite’s formation by suppressing Ni’s activity. The room-temperature shear strength of the joint with graphite’s absence is tested to be 81.97 MPa, which is almost three times higher than that of the joint with graphite. The interfacial reaction process and mechanism of the SiC joint are investigated and explained in this paper using thermodynamic calculations.     

Re-Looking into the Active Moieties of Metal X-ides (X- = Phosph-, Sulf-, Nitr-, and Carb-) Toward Oxygen Evolution Reaction

Non-precious metal-based catalysts for oxygen evolution reaction (OER) have been extensively studied, among which the transition metal X-ides (including phosph-ides, sulf-ides, nitr-ides, and carb-ides) materials are emerging as promising candidates to replace the benchmark Ir/Ru-based materials in alkaline media. However, it is controversial whether the metal Xides host the real active sites since these metal Xides are thermodynamically unstable under a harsh OER environment—it has been reported that the initial metal Xides can be electrochemically oxidized and transformed into corresponding oxides and (oxy)hydroxides. Therefore, the metal Xides are argued as “pre-catalysts”; the electrochemically formed oxides and (oxy)hydroxides are believed as the real active moieties for OER. Herein, the recent advances in understanding the transformation behavior of metal Xides during OER are re-looked; importantly, hypotheses are provided to understand why the electrochemically formed oxides and (oxy)hydroxides catalysts derived from metal Xides are superior for OER to the as-prepared metal oxides and (oxy)hydroxides catalysts.     

The P-graph approach for systematic synthesis of wastewater treatment networks

Wastewater treatment consists of three or four sequential stages: preliminary, primary, secondary, and tertiary. Each stage can comprise multiple alternative technologies that can perform the same tasks with different efficiencies, operating times, and costs. Thus, we propose a systematic approach for designing wastewater treatment networks by utilizing principles of mathematical modeling and generating an exhaustive enumeration of all the possible technologies and their connections during the early stages of designing a treatment facility. Some of these structures are nonintuitive and include recycling, reprocessing, bypasses, and multiple technologies in parallel or series to remove the same contaminant. The nonintuitive structures with multiple technologies may provide a measure of resilience compared to typical heuristic designs. Thus, the combination of P-graph methodology and the sequence of treatment technologies predicted via the optimization algorithm from the maximal structure is based on holistic considerations and does not lead to suboptimal solutions.