Preparation of Mesoporous Yttria-Stabilized Zirconia (YSZ) and YSZ-NiO Using a Triblock Copolymer as Surfactant

Mesoporous yttria-stabilized zirconia (YSZ) and YSZ-NiO have been prepared for the first time using Pluronic P103 as a structure-directing agent and inorganic chlorides as precursors in a nonaqueous medium. After being fired at 500°C for 2 h, mesostructured YSZ has a BET surface area of about 146 m2 g-1, with an average pore size of 3.8 nm, while mesostructured YSZ-NiO has a BET surface area of about 108 m2 g-1, with an average pore size of 4.5 nm

Preparation of Mesoporous Tin Oxide for Electrochemical Applications

Mesoporous tin oxide stable up to 500 °C has been prepared for the first time using both cationic and neutral surfactants

Reduced-Temperature Solid Oxide Fuel Cells Fabricated by Screen Printing

Electrolyte films of samaria-doped ceria (SDC, Sm0.2Ce0.8O1.9) are fabricated onto porous NiO-SDC substrates by a screen printing technique. A cathode layer, consisting of Sm0.5Sr0.5CoO3 and 10 wt % SDC, is subsequently screen printed on the electrolyte to form a single cell, which is tested at temperatures from 400 to 600°C. When humidified (3% H2O) hydrogen or methane is used as fuel and stationary air as oxidant, the maximum power densities are 188 (or 78) and 397 (or 304) mW/cm2 at 500 and 600°C, respectively. Impedance analysis indicates that the performances of the solid oxide fuel cells (SOFCs) below 550°C are determined primarily by the interfacial resistance, implying that the development of catalytically active electrode materials is critical to the successful development of high-performance SOFCs to be operated at temperatures below 600°C

Preparation of Mesoporous SnO\u3csub\u3e2\u3c/sub\u3e-SiO\u3csub\u3e2\u3c/sub\u3e Composite as Electrodes for Lithium Batteries

Mesoporous SnO2–SiO2 composite stable up to 600 °C with a BET surface area of 350 m2 g-1 and an average pore size of 3.4 nm is successfully prepared, which exhibits promising cycling properties as anodes for lithium batterie

Why KDAC? A general activation function for knowledge discovery

Deep learning oriented named entity recognition (DNER) has gradually become the paradigm of knowledge discovery, which greatly promotes domain intelligence. However, the current activation function of DNER fails to treat gradient vanishing, no negative output or non-differentiable existence, which may impede knowledge exploration caused by the omission and incomplete representation of latent semantics. To break through the dilemma, we present a novel activation function termed KDAC. Detailly, KDAC is an aggregation function with multiple conversion modes. The backbone of the activation region is the interaction between exponent and linearity, and the both ends extend through adaptive linear divergence, which surmounts the obstacle of gradient vanishing and no negative output. Crucially, the non-differentiable points are alerted and eliminated by an approximate smoothing algorithm. KDAC has a series of brilliant properties, including nonlinear, stable near-linear transformation and derivative, as well as dynamic style, etc. We perform experiments based on BERT-BiLSTM-CNN-CRF model on six benchmark datasets containing different domain knowledge, such as Weibo, Clinical, E-commerce, Resume, HAZOP and People's daily. The evaluation results show that KDAC is advanced and effective, and can provide more generalized activation to stimulate the performance of DNER. We hope that KDAC can be exploited as a promising activation function to devote itself to the construction of knowledge.Comment: Accepted by Neurocomputin

Electrode Design for Low Temperature Direct-Hydrocarbon Solid Oxide Fuel Cells

In certain embodiments of the present disclosure, a solid oxide fuel cell is described. The solid oxide fuel cell includes a hierarchically porous cathode support having an impregnated cobaltite cathode deposited thereon, an electrolyte, and an anode support. The anode support includes hydrocarbon oxidation catalyst deposited thereon, wherein the cathode support, electrolyte, and anode support are joined together and wherein the solid oxide fuel cell operates a temperature of 600.degree. C. or less

Host-Guest Interaction Dictated Selective Adsorption and Fluorescence Quenching of a Luminescent lightweight Metal-Organic Framework toward Liquid Explosives

In this article, we report the successful preparation of a Mg-based luminescent MIL-53 metal–organic framework (MOF), namely [Mg2(BDC)2(BPNO)]·2DMF (1) (BDC = 1,4-benzene dicarboxylate, BPNO = 4,4’- dipyridyl-N,N’-dioxide, DMF = N,N-dimethylformamide) in a mixed solvent containing a 2 : 3 volume ratio of DMF and ethanol (EtOH) under solvothermal conditions. Desolvated compound 1a can be used as an absorbent for selective adsorption and separation of liquid explosives, including nitroaromatic (nitrobenzene (NB)) and nitroaliphatic (nitromethane (NM) and nitroethane (NE)) compounds, through single crystal-to-single crystal (SC–SC) transformations. As one of the weakly luminescent MOFs, the luminescence of compound 1a could be quenched by the incorporation of the three liquid nitro explosives. On the basis of single crystal analysis, we provide direct evidence that both the selective adsorption and fluorescence quenching of the desolvated compound 1a are dictated by host–guest interactions between guest liquid explosives and the host framework. Such findings differ from those reported in previous works, which were dominated by surficial close contact interactions. Moreover, based on the experimentally obtained single-crystal structures, we explain that the luminescence of 1a follows the intraligand π*→π emission states or weak ligand to ligand charge transfer (LLCT), with little incorporation of intraligand charge transfer (ILCT)

Dynamic Structured Illumination Microscopy with a Neural Space-time Model

Structured illumination microscopy (SIM) reconstructs a super-resolved image from multiple raw images captured with different illumination patterns; hence, acquisition speed is limited, making it unsuitable for dynamic scenes. We propose a new method, Speckle Flow SIM, that uses static patterned illumination with moving samples and models the sample motion during data capture in order to reconstruct the dynamic scene with super-resolution. Speckle Flow SIM relies on sample motion to capture a sequence of raw images. The spatio-temporal relationship of the dynamic scene is modeled using a neural space-time model with coordinate-based multi-layer perceptrons (MLPs), and the motion dynamics and the super-resolved scene are jointly recovered. We validate Speckle Flow SIM for coherent imaging in simulation and build a simple, inexpensive experimental setup with off-the-shelf components. We demonstrate that Speckle Flow SIM can reconstruct a dynamic scene with deformable motion and 1.88x the diffraction-limited resolution in experiment

High Performance Low Temperature Solid Oxide Fuel Cells with Novel Electrode Architecture

In this study, we have fabricated high performance low temperature solid oxide fuel cells (LT-SOFCs) with both acicular anodes and cathodes with thin Gd-doped ceria (GDC) electrolyte film. The acicular Ni-Gd0.1Ce0.9O2−δ (Ni-GDC) anode was prepared using freeze drying tape casting, while the hierarchically porous cathode with nano-size Sm0.5Sr0.5CoO3 (SSC) particles covering an acicular GDC skeleton was prepared by a combination of freeze drying tape casting and self-rising approaches. The acicular electrodes with 5–200 μm pores/channels enhance mass transport, while SSC particles of about 50 nm in the cathode promote electrochemical reactions. Cells which have this novel electrode architecture show a significantly high power output of 1.44 W cm−2 and an extremely low cell polarization resistance of 0.0379 Ω cm2 at 600 °C

Distributions of Nobel Metal Pd and Pt in Mesoporous Silica

Mesoporous silicananostructures have been synthesized and loaded with Pd and Pt catalytic noble metals. It is found that Pd forms small nanoclusters (3–5 nm) on the surface of the mesoporous structure whereas Pt impregnation results in the inclusion of Pt nanostructures within the silica hexagonal pores (from nanoclusters to nanowires). It is observed that these materials have high catalyticproperties for CO–CH4CO–CH4CO–CH4 combustion, even in a thick film form. In particular, results indicate that the Pt and Pd dispersed in mesoporous silica are catalytically active as a selective filter for gas sensors