掺锗提高VO2薄膜的相变温度机理研究

二氧化钒(VO₂)作为一种长久以来备受关注的新型可逆相变材料,发展潜力巨大,其相变温度(T_MIT)的调控一直是研究热点。本文主要利用锗离子作为掺杂离子探索其对VO₂薄膜T_MIT的影响,并尝试解释其内部作用机理。在约1 cm²大小抛光的氧化铝薄片上沉积了一系列含不同比例锗离子VO₂薄膜。研究发现锗离子作为掺杂离子确实有利于T_MIT的提高(本课题T_MIT最大可达84.7 ℃)。T_MIT提高的主要原因是锗离子的引入能够强化单斜态V-V二聚体的稳定性,进而增强单斜态的稳定性,使得低温单斜态向四方金红石态转变更加困难。     

原位液相透射电子显微镜及其在 纳米粒子表征方面的应用

近年来,基于透射电子显微技术、微纳加工技术和薄膜制造技术的发展,原位液相透射电子显微技术产生,为构建多种纳米级分辨率尺度下的微实验平台,发展新型纳米表征技术和众多领域的相关研究提供了途径.本文首先介绍了应用于原位液相透射电子显微技术的液体腔设计要求,然后介绍了液体腔的发展和典型的制备工艺,最后综述了近年来液体腔透射电子显微镜在纳米粒子成核和生长方面的应用研究,并探讨了该技术前沿发展面临的机遇和挑战.本文将为提高我国先进纳米表征技术和原子精准构筑技术提供相关讨论和支持.     

室温铁磁性Sr3YCo4O10.5+δ多晶有序化的烧结工艺及电磁性能

采用固相反应法制备了不同烧结温度(950~1 180 ℃)、烧结时间、烧结次数共7种工艺的Sr₃YCo₄O_10.5+δ多晶块材,通过热分析、XRD、SEM确定了有序化相变和最佳烧结工艺(1 180 ℃/24 h+1 180 ℃/24 h),并研究了多晶的电磁性能。结果表明,964 ℃完全晶化的四方相Sr₃YCo₄O_10.5在1 042 ℃吸氧(δ)完成有序化,生成Sr₃YCo₄O_10.5+δ,而1 100 ℃和1 180 ℃烧结的样品均出现(103)、(215)超结构峰,验证了其结构的有序性。块材均呈半导体电输运行为,二次烧结晶格完整性提高,晶粒长大,300 K时电阻率仅为0.06 Ω·cm,居里温度(T_c)~335 K,零场冷曲线(ZFC)上的Hopkinson峰源于低温时被冻结的磁矩随温度升高转向磁场方向,磁化强度在298 K达到最大,随后受热扰动的影响减小。室温铁磁性源于有序结构导致的中自旋或高自旋态Co³⁺的e_g轨道有序。     

On pointwise decay rates of time‐periodic solutions to the Navier–Stokes equation

We study the existence of a time‐periodic solution with pointwise decay properties to the Navier–Stokes equation in the whole space. We show that if the time‐periodic external force is sufficiently small in an appropriate sense, then there exists a time‐periodic solution $\{u,p\}$ of the Navier–Stokes equation such that $|{?}^j{u(t,x)|=O(|x|}^{1?n?j})$ and $|{?}^j{p(t,x)|=O(|x|}^{?n?j})(j=0,1,\dots )$ uniformly in $t\in \mathbb{R}$ as $|x|\to \infty$. Our solution decays faster than the time‐periodic Stokes fundamental solution and the faster decay of its spatial derivatives of higher order is also described.     

Shedding vortex simulation method based on viscous compensation technology research

Owing to the influence of the viscosity of the flow field, the strength of the shedding vortex decreases gradually in the process of backward propagation. Large-scale vortexes constantly break up, forming smaller vortexes. In engineering, when numerical simulation of vortex evolution process is carried out, a large grid is needed to be arranged in the area of outflow field far from the boundary layer in order to ensure the calculation efficiency. As a result, small scale vortexes at the far end of the flow field cannot be captured by the sparse grid in this region, resulting in the dissipation or even disappearance of vortexes. In this paper, the effect of grid scale is quantified and compared with the viscous effect through theoretical derivation. The theoretical relationship between the mesh viscosity and the original viscosity of the flow field is established, and the viscosity term in the turbulence model is modified. This method proves to be able to effectively improve the intensity of small-scale shedding vortexes at the far end of the flow field under the condition of sparse grid. The error between the simulation results and the results obtained by using fine mesh is greatly reduced, the calculation time is shortened, and the high-precision and efficient simulation of the flow field is realized.     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Design,synthesis and evaluation of novel dehydroabietic acid-dithiocarbamate hybrids as potential multi-targeted compounds for tumor cytotoxicity

In the present study, novel representatives of the important group of biologically-active, dehydroabietic acid-bearing dithiocarbamate moiety, were synthesized and characterized by ¹H NMR, ¹³C NMR, HR-MS. The in vitro antiproliferative activity evaluation (MTT) indicated that these compounds exhibited potent inhibitory activities in various cancer cell lines (HepG-2, MCF-7, HeLa, T-24, MGC-803). Particularly, compound III-b possessed extraordinary cytotoxicity with low micromolar IC₅₀ values ranging from 4.07 to 38.84 µM against tested cancer cell lines, while displayed weak cytotoxicity on two normal cell lines (LO-2 and HEK 293 T). Subsequently, the potential mechanisms of representative compound III-b were elementarily investigated by Transwell experiment, which showed III-b can inhibit cancer cells migration. Annexin-V/PI dual staining showed that the compound can induce HepG-2 cells apoptosis in a dose-dependent manner. Meanwhile this apoptosis may be related to the upregulated protein expression of cleaved-caspase 3, cleaved-caspase 9, Bax and downregulated of Bcl-2 indicated by Western Blot. Later study further confirmed that ROS levels in HepG-2 cells increased significantly with the rise of concentrations. In addition, through the network pharmacology data analyzing, the core targets and signaling pathways of compound III-b for treatment of liver neoplasms were forecasted. Molecular docking model showed that compound III-b had high affinity with hub targets (CASP3, EGFR, HSP90AA1, MAPK1, ERBB2, MDM2), suggesting that compound III-b might target the hub protein to modulate signaling activity. Taken together, these data indicated that dehydroabietic acid structural modification following the “Molecular hybridization” principle is a feasible way to discover the potential multi-targeted antitumor compounds.