Grain growth behavior of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy during isothermal β heat treatments

Isothermal β heat treatments of Ti-6.5 Al-3.5 Mo-1.5 Zr-0.3 Si alloy were performed at the temperature of1040-1240 ℃ to examine the influence of heating conditions on grain growth of the alloy. The results show that the grain size increases with heating temperature and holding time increasing. Rapid β grain growth of the alloy takes place at the temperature of over 1140 ℃. The grain growth kinetics for the alloy follows the classical isothermal grain growth law.The growth time exponent(n) of 0.5651 and activation energy(Q) of 129.6 kJ mol-1 are determined. Finally, in order to determine the grain size under different heating conditions,the grain growth model of the alloy was established.     

Growth of Aitken mode ammonium sulfate particles by α-pinene ozonolysis

The fraction of Aitken mode particles that grow sufficiently large to act as cloud condensation nuclei is an important factor in understanding the climate impact of atmospheric particles. Elucidating the rate of particle growth in this size range requires a detailed understanding of the mechanisms by which these particles grow. Here, a flow tube reactor is described, characterized and then used to study growth of ammonium sulfate seed particles in the Aitken mode size range by α-pinene ozonolysis under dry conditions (10% RH). When size-selected particles starting at 40, 60, or 80?nm diameter were exposed to α-pinene (11?ppbv) and ozone (five separate mixing ratios between 30 and 250?ppbv), particle growth was found to depend on the amount of α-pinene reacted and the condensation sink, but not directly dependent on the initial seed particle diameter. The observed dependencies are consistent with a condensational growth mechanism, which is not surprising since the dry conditions of the experiment minimized the probability of multiphase chemistry within the seed particles. Combining the measured particle growth with a kinetic model gave a molar yield of 13% for condensable organic molecules produced by the ozonolysis reaction. This value is somewhat higher than previously reported molar yields of highly oxidized molecules (HOMs) measured in the gas phase with chemical ionization mass spectrometry, which are in the 3–7% range. The relationship between molar yields determined from gas phase and particle phase measurements is discussed.

Copyright © 2019 American Association for Aerosol Research     

Anderson Acceleration for Nonconvex ADMM Based on Douglas-Rachford Splitting

The alternating direction multiplier method (ADMM) is widely used in computer graphics for solving optimization problems that can be nonsmooth and nonconvex. It converges quickly to an approximate solution, but can take a long time to converge to a solution of high-accuracy. Previously, Anderson acceleration has been applied to ADMM, by treating it as a fixed-point iteration for the concatenation of the dual variables and a subset of the primal variables. In this paper, we note that the equivalence between ADMM and Douglas-Rachford splitting reveals that ADMM is in fact a fixed-point iteration in a lower-dimensional space. By applying Anderson acceleration to such lower-dimensional fixed-point iteration, we obtain a more effective approach for accelerating ADMM. We analyze the convergence of the proposed acceleration method on nonconvex problems, and verify its effectiveness on a variety of computer graphics including geometry processing and physical simulation.     

Monthly Rainfall Forecasting Using Echo State Networks Coupled with Data Preprocessing Methods

In this paper, two novel methods, echo state networks (ESN) and multi-gene genetic programming (MGGP), are proposed for forecasting monthly rainfall. Support vector regression (SVR) was taken as a reference to compare with these methods. To improve the accuracy of predictions, data preprocessing methods were adopted to decompose the raw rainfall data into subseries. Here, wavelet transform (WT), singular spectrum analysis (SSA) and ensemble empirical mode decomposition (EEMD) were applied as data preprocessing methods, and the performances of these methods were compared. Predictive performance of the models was evaluated based on multiple criteria. The results indicate that ESN is the most favorable method among the three evaluated, which makes it a promising alternative method for forecasting monthly rainfall. Although the performances of MGGP and SVR are less favorable, they are nevertheless good forecasting methods. Furthermore, in most cases, MGGP is inferior to SVR in monthly rainfall forecasting. WT and SSA are both favorable data preprocessing methods. WT is preferable for short-term forecasting, whereas SSA is excellent for long-term forecasting. However, EEMD tends to show inferior performance in monthly rainfall forecasting.     

Design and Synthesis of Novel Chromophore with Multi-Carboxyl Groups

In order to explore the application of organic conjugated small molecules in bioimaging, a novel functional chromophore with A-π-D-π-A structure (Cr-3) was synthesized through Knoevenagel condensation reaction, consisting of carbazole unit as electron donor and cyanoacetic acid as electron acceptor groups. To improve the water solubility of this conjugated molecule, three carboxyl groups were introduced to chromophore Cr-3. Compared to the traditional D-π-A chromophores, chromophore Cr-3 showed the great improvement in water with the solubility of 2000 ppm. Also, the thermal stability of chromophore Cr-3 was also studied. The thermal decomposition temperature (Td) of Cr-3 was approximately 180°C, which was attributed to the dehydration of the carboxyl groups. Though the second harmonic generation (SHG) effect was not very high, it is large enough for the detection of SHG signal in water solution (0.28 pm/V).     

Experimental investigation on the effect of ambient pressure on thermal runaway and fire behaviors of lithium‐ion batteries

To investigate the impacts of ambient pressure on thermal runaway and fire behaviors of lithium‐ion battery (LIB), experimental measurement and theoretical analysis with serial conditions are conducted at two altitudes. The well‐designed experimental equipment and operating conditions have enabled the accurate evaluation of ambient pressure effects. Results show that the first abrupt temperature change in Hefei (ambient pressure 100.8 kPa) is higher than that in Lhasa (64.3 kPa). The difference in ambient pressure at two altitudes leads to different relief valve crack temperature and time. The average burning rate in Hefei is larger than that in Lhasa, and the estimated pressure effect factor is quite different for detailed pack conditions and varies within the range of 0.083‐1.39. The ambient pressure has a greater effect on the heat release rate and total heat release than the mass loss, and the effective combustion heat under the low pressure is lower than that in normal condition. This work can provide more comprehensive and useful data for the safety management of LIBs at low pressure environments.     

Efficient defect passivation for high performance perovskite solar cell by adding alizarin red S

Planar perovskite solar cells (PSCs) have excellent photoelectric properties and show great commercialization potential. However, there are a lot of crystal defects in the perovskite films prepared by solution method, which reduces the development process of solar cells. In this work, alizarin red s (ARS) was doped into MAPbI₃ films to passivate the defect. It was shown that the addition of ARS increased the quality of perovskite film and doped perovskite film exhibited improved light absorption. In addition, it was found that there was a strong interaction between ARS and perovskite, which reduced the density of defect states. The results showed that the passivated perovskite device had improved PL intensity, increased carrier lifetimes and reduced charge recombination. After passivation, the device obtained a higher open-circuit voltage (V_OC) of 1.103 V where the control device was 1.055 V, and the best power conversion efficiency (PCE) of the doped device was 18.82%, which is 11.36% higher than that of the control device of 16.90%.

Graphical abstract

     

Data-driven modeling of mesoscale solids stress closures for filtered two-fluid model in gas–particle flows

This study performs data-driven modeling of mesoscale solids stress closures for filtered two-fluid model (fTFM) in gas–particle flows via an artificial neural network (ANN) based machine learning method. The data used for developing the ANN-based predictive data-driven modeling framework is systematically filtered from fine-grid simulations. The loss function optimization result reveals that coupling two loss functions promotes more accurate predictions of the mesoscale solids stresses than using a single loss function. Further comprehensive assessments of closure markers demonstrate a systematic dependence of the mesoscale solids stresses on the filtered particle velocity and its gradient as additional anisotropic markers, instead of using the conventional isotropic filtered rate of solid phase deformation as a closure marker. An optimal three-marker mesoscale closure is thus proposed. Comparative analysis of the conventional filtered model and present three-marker model shows that the data-driven model can substantially enhance the prediction accuracy.     

N-乙氧基羰基-N,N',N'-三甲基胍高效液相色谱分析方法研究

N-乙氧基羰基-N,N',N'-三甲基胍(简称:三甲基胍)是合成高选择性森林除草剂环嗪酮的主要中间体,国内未见高效液相色谱检测方法的报道,我们采用反相高效液相色谱法对三甲基胍进行了定量分析研究,流动相为:V(水)︰V(乙腈)=90︰10,使用ODSC18为填料的不锈钢柱及具可变波长的紫外检测器.本方法的变异系数为0.19％,标准偏差为0.15,平均回收率为99.56％,经优化后的检测方法简捷、准确,能满足工业化产品定量检测需要.