Organic mesh template-based laminated object manufacturing to fabricate ceramics with regular micron scaled pore structures

A new aqueous slurry-based laminated object manufacturing process for porous ceramics is proposed: firstly, an organic mesh sheet is pre-paved as a pore-forming template before slurry layer scraping; secondly, the 2D pattern is built with laser outline cutting of the dried mesh–ceramic composite layer; finally, the pore structure is formed after degreasing and sintering. Alumina parts with porosities of 51.5 %, round hole diameters of 80 ± 5 μm were fabricated using 70 wt. % solid content slurry and 100 mesh nylon net. Using an organic mesh as the framework and template not only reduces the risk of damage of the green body but also ensures the regularity, uniformity and connectivity of the micron scaled pore network. The layer-by-layer drying method avoids the delamination phenomenon and improves the paving density. The new method can realize the flexible design of the pore structure by using various organic mesh templates.     

Synthesis of Hollow Three-Dimensional Channels LiNi_(0.5)Mn_(1.5)O_4 Microsphere by PEO Soft Template Assisted with Solvothermal Method

A appropriate size with three-dimension(3 D) channels for lithium diffusion plays an important role in constructing highperforming LiNi_(0.5)Mn_(1.5)O_4(LNMO) cathode materials, as it can not only reduce the transport path of lithium ions and electrons, but also reduce the side effects and withstand the structural strain in the process of repetitive Li~+ intercalation/deintercalation. In this work, an e fficient method for designing the hollow LNMO microsphere with 3 D channels structure by using polyethylene oxide(PEO) as soft template agent assisted solvothermal method is proposed. Experimental results indicate that PEO can make the reagents mingle evenly and nucleate slowly in the solvothermal process, thus obtaining a homogeneous distribution of carbonate precursors. In the final LNMO products, the hollow 3 D channels structure obtained by the decomposition of PEO and carbonate precursor in the calcination can provide abundant electroactive zones and electron/ion transport paths during the charge/discharge process, which benefits to improve the cycling performance and rate capability. The LNMO prepared by adding 1 g PEO possesses the most outstanding electrochemical performance, which presented an excellent discharge capacity of 143.1 mAh g~(-1) at 0.1 C and with a capacity retention of 92.2% after 100 cycles at 1 C. The superior performance attributed to the 3 D channels structure of hollow microspheres, which provide uninterrupted conductive systems and therefore achieve the stable transfer for electron/ion.     

Using deep learning to combine static and dynamic power analyses of cryptographic circuits

Side-channel attacks have shown to be efficient tools in breaking cryptographic hardware. Many conventional algorithms have been proposed to perform side-channel attacks exploiting the dynamic power leakage. In recent years, with the development of processing technology, static power has emerged as a new potential source for side-channel leakage. Both types of power leakage have their advantages and disadvantages. In this work, we propose to use the deep neural network technique to combine the benefits of both static and dynamic power. This approach replaces the classifier in template attacks with our proposed long short-term memory network schemes. Hence, instead of deriving a specific probability density model for one particular type of power leakage, we gain the ability of combining different leakage sources using a structural algorithm. In this paper, we propose three schemes to combine the static and dynamic power leakage. The performance of these schemes is compared using simulated test circuits designed with a 45-nm library.     

Controlled galvanic decoration boosting catalysis: Enhanced glycerol electro-oxidation at Cu/Ni modified macroporous films

We report on glycerol electro-oxidation in alkaline medium at macroporous Ni electrodes decorated with Cu particles. Macroporous Ni film is electrodeposited, using hydrogen bubbles as dynamic templates, atop of a Cu substrate. This film shows good electrocatalytic activity towards glycerol oxidation reaction (GOR). The Ni film is further decorated with Cu via spontaneous deposition from CuSO₄ solution. This is done to enhance the catalytic activity of the film towards GOR. The morphology of the Cu-decorated Ni film is controlled using various additives such as KCl and (NH₄)₂SO₄ which are added to the Cu deposition bath. The as-prepared Cu-decorated Ni films are characterized by electrochemical measurements, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). It is found that these additives have tremendous effects on the morphology and the electrocatalytic activity of the decorating Cu particles.The decorated Ni foam showed superior electrocatalytic activity towards the GOR, as confirmed by the negative shift in the onset oxidation potential (ca. 100 mV) together with an increase in oxidation current that is up to 1.5-fold during the cyclic voltammetry (CV) measurements, compared to the undecorated Ni foam.     

Engineering the Structure of Mesoporous Bioactive Glass Microspheres by the Surface Effect of Inverse Opal Templates and Temperature

The interactions of ions and molecules with material surface are highly dependent on the surface properties of the material. Therefore, the distribution of ions or molecules near the material surface may be affected by the surface properties. This phenomenon can be significant enough for controlling the structure of a material synthesized in the sub‐micrometer scale confinement space of a template. This work confirms that inverse opals are perfect templates for offering confinement space, while their different surface properties can strongly affect ion and block copolymer distribution in the confinement space. This surface effect principle can be used for the controlled synthesis of colloids with complex composition. As an example, four kinds of mesoporous magnetic bioactive glass colloids with ordered mesopores, core–shell structure, open surface pores, or disordered mesopores are prepared by using polystyrene and carbon inverse opal templates. This work reveals that inverse opal templates possess great advantage in controlled synthesizing colloidal structures due to their surface effect on ions and molecules and confinement space.     

同时脱除吡虫啉和啶虫脒农残的虚拟模板表面分子印迹的制备和应用

以吡虫啉和啶虫脒的结构类似物烟酰胺作为虚拟模板分子、α-甲基丙烯酸(α-methyl acrylic acid,MAA)作为功能单体、乙二醇二甲基丙烯酸酯(ethyleneglycol dimethacrylate,EDGMA)作为交联剂,采用表面分子印迹技术(MIT)制备了虚拟模板表面分子印迹聚合物(dummy template surface molelecularly imprinted polymers,DMIP)。在单因素实验的基础上采用响应面优化法对DMIP的制备方法进行优化,利用扫描电子显微镜对优化后的DMIP形态结构进行表征,考察了DMIP对于吡虫啉和啶虫脒的吸附性能。结果表明,DMIP对吡虫啉和啶虫脒具有较高的吸附容量和选择性,对吡虫啉和啶虫脒的最大吸附量分别为41.73和21.95 mg/g。将DMIP作为柱填充材料从茶多酚中脱除吡虫啉和啶虫脒,去除率分别达到96.2%和95.6%。所得DMIP对茶多酚等天然植物提取物生产过程中吡虫啉和啶虫脒的去除具有良好的应用前景。     

Texturing behaviours of (K0.47Na0.51Li0.02)(Nb0.8Ta0.2)O3 piezoelectric ceramics produced using NaNb1-xTaxO3 templates

Textured (K_0.47Na_0.51Li_0.02)(Nb_0.8Ta_0.2)O₃ (KNLNT20) piezoelectric ceramics were prepared using NaNb_1?xTa_xO₃ templates. The highest degree of grain orientation (97%) and piezoelectric constant (342 pC/N) were obtained upon adding 3 wt% of the NaNb_0.8Ta_0.2O₃ (NNT20) template and sintering at 1150 °C for 1 h. Back-scattered scanning electron micrographs of the textured KNLNT20 samples sintered at 1150 °C for 1 h indicated the presence of templates similar in size to the original ones within the cores of the textured grains. The peak value of the dielectric constant corresponding to the NNT20 core decreased after prolonged holding at 1150 °C, owing to a decrease in the size of the NNT20 core because of the interdiffusion of K, Na, and Li ions between the NNT20 core and KNLNT20 shell. This interdiffusion also decreased the piezoelectric constant, d₃₃ value of the textured KNLNT20 samples by inducing a change in the chemical composition of the shell region.     

Template Engineering of CuBi2O4 Single‐Crystal Thin Film Photocathodes

To develop strategies for efficient photo‐electrochemical water‐splitting, it is important to understand the fundamental properties of oxide photoelectrodes by synthesizing and investigating their single‐crystal thin films. However, it is challenging to synthesize high‐quality single‐crystal thin films from copper‐based oxide photoelectrodes due to the occurrence of significant defects such as copper or oxygen vacancies and grains. Here, the CuBi₂O₄ (CBO) single‐crystal thin film photocathode is achieved using a NiO template layer grown on single‐crystal SrTiO₃ (STO) (001) substrate via pulsed laser deposition. The NiO template layer plays a role as a buffer layer of large lattice mismatch between CBO and STO (001) substrate through domain‐matching epitaxy, and forms a type‐II band alignment with CBO, which prohibits the transfer of photogenerated electrons toward bottom electrode. The photocurrent densities of the CBO single‐crystal thin film photocathode demonstrate ?0.4 and ?0.7 mA cm^?2 at even 0 V_RHE with no severe dark current under illumination in a 0.1 m potassium phosphate buffer solution without and with H₂O₂ as an electron scavenger, respectively. The successful synthesis of high‐quality CBO single‐crystal thin film would be a cornerstone for the in‐depth understanding of the fundamental properties of CBO toward efficient photo‐electrochemical water‐splitting.     

Behavior and mechanism of in-situ synthesis of auxiliary electrode for electrochemical sulfur sensor by calcium aluminate system

The behavior and mechanism of in-situ synthesis of the auxiliary electrode for sulfur sensor were investigated in this work, aiming for better application of calcium aluminate system in synthesizing the auxiliary electrode used for sulfur sensor. The in-situ reaction experiment was developed. In addition, the thermodynamic and kinetic calculations were adopted to further study the in-situ reaction possibility and the reaction rate. The results indicated that the value of lg(a_[S]/a_[O]) should be greater than a particular value to ensure the occurrence of the in-situ reaction. After immersion into the molten iron, the CaS phase was synthesized in the calcium aluminate system. The relationship between the reaction rate and reaction time was exponential, and the initial reaction rate was affected by the CaO content incorporated in the calcium aluminate system and the sulfur content in the molten iron. The initial in-situ reaction rate greatly increased with the increase of the CaO content and sulfur content. For example, the initial reaction rate was as high as 14.87 s^-1 when the calcium aluminate system containing 60 wt% of CaO and for a sulfur content of 0.077 wt% in the molten iron. Moreover, the reason that the sulfur sensor fabricated by the ZrO₂(MgO) tube with the calcium aluminate coating with different components had the same response time when measuring the different sulfur contents in the molten iron was further explained.     

Bayesian changepoint and time-varying parameter learning in regime switching volatility models

This paper proposes a combined state and piecewise time-varying parameter learning technique in regime switching volatility models using multiple changepoint detection. This approach is a Sequential Monte Carlo method for estimating GARCH & EGARCH based volatility models with an unknown number of changepoints. Modern auxiliary particle filtering techniques are used to calculate the posterior densities and online forecasts. This approach also automatically deals with the common ancestral path dependence problem faced in these type volatility models. The model is tested on Borsa Istanbul (BIST) formerly known as Istanbul Stock Exchange (ISE) market data using daily log returns. A full structural changepoint specification is defined in which all parameters of the conditional variance of the volatility models are dynamic. Finally, it is shown with simulation experiments that the proposed approach partitions the series into several regimes and learns the parameters of each regime's volatility model in parallel with the multiple changepoint detection process.