Fabrication of alumina ceramics with functional gradient structures by digital light processing 3D printing technology

Alumina ceramics with different unit numbers and gradient modes were prepared by digital light processing (DLP) 3D printing technology. The side length of each functional gradient structure was 10 mm, the porosity ratio was controlled to 70%, and the number of units were (1 × 1 × 1 unit) and (2 × 2 × 2 unit) respectively. The different gradient modes were named FCC, GFCC-1, GFCC-2 and GFCC-3. SEM, XRD, and other characterization methods proved that these gradient structures of alumina ceramics had only α-Al2O3 phase and good surface morphology. The mechanical properties and energy absorption properties of alumina ceramics with different functional gradient structures were studied by compression test. The results show that the gradient structure with 1 × 1 × 1 unit has better mechanical properties and energy absorption properties when the number of units is different. When the number of units is the same, GFCC-2 and GFCC-3 gradient structures have better compressive performance and energy absorption potential than FCC structures. The GFCC-2 gradient structure with 1 × 1 × 1 unit has a maximum compressive strength of 19.62 MPa and a maximum energy absorption value of 2.72 × 105 J/m3. The good performance of such functional gradient structures can provide new ideas for the design of lightweight and compressive energy absorption structures in the future.     

Reduction of waste biosolids by RAS-ozonation: Model validation and sensitivity analysis for biosolids reduction and nitrification

Biosolids reduction model by return activated sludge ozonation was validated by simulating nitrification data compiled from our pilot-scale and the literature studies. Then, a global sensitivity analysis (GSA) was performed to identify influential and non-influential parameters for biosolids reduction efficiency, change in specific nitrification activity (SNA), and alteration to expected nitrification stability. In general, the model outputs were sensitive to operational and ozone reaction parameters, but not to biochemical parameters. For operational parameters, mainly temperature and initial solids retention time (SRT) influenced all model outputs. For biosolids reduction, increase in the degradability of the influent COD decreased the reduction efficiency. For SNA, the changes were highly dependent on the influent TKN/COD ratio. Our findings also imply that the stability of the nitrification process in ozonated systems should be enhanced at constant MLVSS for warm temperatures, but could be reduced at temperatures below 12 °C and aerated SRTs below 10 days.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

Sensitivity analysis of Johnson-Cook material parameters on adiabatic shear in different directions

ABSTRACT

This study investigates the effects of strain, strain rates, and forming directions (RD-rolling direction, TD-transverse direction, and ND-normal direction) on adiabatic shear, via dynamic impact compression tests using the Split Hopkinson Pressure Bar (SHPB) apparatus. A modified Johnson-Cook (J-C) constitutive model is proposed, which used to analyse the influence of the constitutive parameters on the sensitivity of adiabatic shear, employing a finite element software. The different sensitivities of adiabatic shear under different directions are explained by combining microscopic analysis and results from mechanical responses. The results show that the sensitivity of adiabatic shear can be related to the time of stress collapse in the following trend: ND?>?TD?>?RD; the sensitivities of these constitutive parameters on adiabatic shear are calculated and compared.     

Y4.67Si3O13-based phosphors: Structure,morphology and upconversion luminescence for optical thermometry

How to improve the sensitivity of the temperature-sensing luminescent materials is one of the most important objects currently. In this work, to obtain high sensitivity and learn the corresponding mechanism, the rare earth (RE) ions doped Y_4.67Si₃O₁₃ (YS) phosphors were developed by solid-state reaction. The phase purity, structure, morphology and luminescence characteristics were evaluated by XRD, TEM, emission spectra, etc. The change of the optical bandgaps between the host and RE-doped phosphors was found, agreeing with the calculation results based on density-functional theory. The temperature-dependence of the upconversion (UC) luminescence revealed that a linear relationship exists between the fluorescence intensity ratio of Ho³⁺ and temperature. The theoretical resolution was evaluated. High absolute (0.083 K⁻¹) and relative (3.53% K⁻¹ at 293 K) sensitivities have been gained in the YS:1%Ho³⁺, 10%Yb³⁺. The effect of the Yb³⁺ doping concentration and pump power on the sensitivities was discussed. The pump-power–dependence of the UC luminescence indicated the main mechanism for high sensitivities in the YS:1%Ho³⁺, 10%Yb³⁺. Moreover, the decay-lifetime based temperature sensing was also evaluated. The above results imply that the present phosphors could be promising candidates for temperature sensors, and the proposed strategies are instructive in exploring other new temperature sensing luminescent materials.     

一种基于小字典不对等语料的跨语言词嵌入方法

双语词嵌入通常采用从源语言空间到目标语言空间映射,通过源语言映射嵌入到目标语言空间的最小距离线性变换实现跨语言词嵌入。然而大型的平行语料难以获得,词嵌入的准确率难以提高。针对语料数量不对等、双语语料稀缺情况下的跨语言词嵌入问题,该文提出一种基于小字典不对等语料的跨语言词嵌入方法,首先对单语词向量进行归一化,对小字典词对正交最优线性变换求得梯度下降初始值,然后通过对大型源语言(英语)语料进行聚类,借助小字典找到与每一聚类簇相对应的源语言词,取聚类得到的每一簇词向量均值和源语言与目标语言对应的词向量均值,建立新的双语词向量对应关系,将新建立的双语词向量扩展到小字典中,使得小字典得以泛化和扩展。最后,利用泛化扩展后的字典对跨语言词嵌入映射模型进行梯度下降求得最优值。在英语—意大利语、德语和芬兰语上进行了实验验证,实验结果证明该文方法可以在跨语言词嵌入中减少梯度下降迭代次数,减少训练时间,同时在跨语言词嵌入上表现出较好的正确率。     

Impact sensitivities of energetic materials: Exploring the limitations of a model based only on structural formulas

Using a comprehensive set of drop weight impact test data (h₅₀) newly compiled from literature for 308 materials, a recent approach to predict impact sensitivities of nitro compounds is generalized to most explosive substances of interest. Compared to previous ones, this procedure is more thoroughly validated and exhibits a good predictive value. Furthermore, it yields new insight into the physical mechanisms involved, explaining for instance the unexpected desensitization of some oxygen-deficient triazoles upon nitration.     

Compensation paradox: the influence of monetary rewards on user behaviour

Many e-commerce companies collect users’ personal data for marketing purposes despite privacy concerns. Information-collecting companies often offer a monetary reward to users to alleviate privacy concerns and ease the collection of personal information. This study focused on the negative effects of monetary rewards on both information privacy concerns (IPC) and information disclosure. A survey approach was used to collect data and 370 final responses were analysed using a two-way analysis of variance and a binomial logistic regression model. The results show that monetary rewards increase IPC when an information-collecting company requires sensitive information. Additional results indicate that building trust is a more effective way of collecting personal data. This study identifies how organisations can best execute information-collection activities and contributes additional insights for academia and practitioners.     

Design and Fabrication of Concentration‐Gradient Generators with Two and Three Inlets in Microfluidic Chips

A simple and low‐cost method for designing and fabricating concentration‐gradient generators with two and three inlets is proposed which can generate different concentration gradients at varying flow velocities. The microchannel structure was designed in S‐shape and left‐right symmetry. The concentration‐gradient generator was simulated based on the finite element method. The microchannels were processed on a computer numerical control (CNC) engraving and milling machine on poly(methylmethacrylate) substrate, and then two concentration‐gradient generators were fabricated by hot bonding technology. The results of experiment and simulation were compared to prove the feasibility of the method. Flow velocity was an important factor for generating different concentration gradients. The concentration‐gradient profiles of the generators with two and three inlets present approximately linear and quadratic curves.     

Bearing Failure Optimization of Composite Double-Lap Bolted Joints Based on a Three-Step Strategy Marked By Feasible Region Reduction and Model Decoupling

To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction, optimization model decoupling and optimization was presented. In feasible region reduction, the dimensions of the feasible design region were reduced by selecting dominant design variables from numerous multilevel parameters by sensitivity analyses, and the feasible regions of variables were reduced by influence mechanism analyses. In model decoupling, the optimization model with a large number of variables was divided into various sub-models with fewer variables by variance analysis. In the third step, the optimization sub-models were solved one by one using a genetic algorithm, and the modified characteristic curve method was adopted as the failure prediction method. Based on the proposed optimization method, optimization of a double-lap single-bolt joint was performed using the ANSYS^® code. The results show that the bearing failure load increased by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of the joint, which validated the effectiveness of the three-step optimization strategy.