密度泛函理论方法研究填料表面对聚合物摩擦化学的影响

采用超声分散法制备出氧化铝、高岭土、氧化硅/聚四氟乙烯复合材料, 使用线性往复摩擦磨损试验机对比三种复合材料的摩擦学性能. 结果表明 质量分数10%的氧化铝、高岭土能将聚四氟乙烯的磨损率降低约4个数量级, 而氧化硅仅能降低约3个数量级. 对金属对偶表面形成的转移膜的形貌和化学成分进行分析发现 氧化铝、高岭土/聚四氟乙烯在金属对偶面上形成了高度羧酸盐化的转移膜. 用密度泛函理论对三种填料表面上碳氟分子吸附过程进行模拟, 结果显示氧化铝、高岭土表面的路易斯酸性位点促进了碳氟分子的脱氟过程, 产生了更多的羧酸螯合物的中间产物; 氧化硅缺少路易斯酸性位点, 因此不能促进高度羧酸盐化的转移膜形成.     

Quantum Resources in Heisenberg XX Model Under Noisy Environment

International Journal of Theoretical Physics - In this paper, we investigate Einstein-Podolsky-Rosen steering, Bell non-locality, first-order coherence and concurrence in the spin- $\frac {1}{2}$...     

Highly insulating alkane rings with destructive σ-interference

Science China Chemistry - Destructive quantum interference (DQI) provides a unique approach to controlling the leakage current in the OFF state of molecular devices. However, the DQI in...     

关于两个图的一类新连接图的谱

给定2个图G1和G2，设G1的边集E(G1)={e1,e2,?,em1}，则图G1⊙G2可由一个G1，m1个G2通过在G1对应的每条边外加一个孤立点，新增加的点记为U={u1,u2,?,um1}，将ui分别与第i个G2的所有点以及G1中的边ei的端点相连得到，其中i=?1,2,?,m1。得到：（i）当G1是正则图，G2是正则图或完全二部图时，确定了G1⊙G2的邻接谱（A-谱）。（ii）当G1是正则图，G2是任意图时，给出了G1⊙G2的拉普拉斯谱（L-谱）。（iii）当G1和G2都是正则图时，给出了G1⊙G2的无符号拉普拉斯谱（Q-谱）。作为以上结论的应用，构建了无限多对A-同谱图、L-同谱图和Q-同谱图；同时当G1是正则图时，确定了G1⊙G2支撑树的数量和Kirchhoff指数。     

Weak Galerkin finite element methods with or without stabilizers

The purpose of this paper is to investigate the connections between the weak Galerkin (WG) methods with and without stabilizers. The choices of stabilizers directly affect the convergence rates of the corresponding WG methods in general. However, we observed that the convergence rates are independent of the choices of stabilizers for these WG elements with stabilizers being optional. In this paper, we will verify such phenomena theoretically as well as numerically.

     

Effect of Plane Deformation on Superconducting and structural Properties of YBa2Cu3–yFeyO7–x Ceramics

Russian Physics Journal -     

Uncertain seepage equation in fissured porous media

Fuzzy Optimization and Decision Making - Seepage equation in fissured porous media is a partial differential equation describing the variation of pressure of a given area over time. In traditional...     

Synchronization mechanism of clapping rhythms in mutual interacting individuals

In recent years, clapping synchronization between individuals has been widely studied as one of the typical synchronization phenomena. In this paper, we aim to reveal the synchronization mechanism of clapping interactions by observing two individuals’ clapping rhythms in a series of experiments. We find that the two synchronizing clapping rhythm series exhibit long-range cross-correlations(LRCCs);that is, the interaction of clapping rhythms can be seen as a strong-anticipation process. Previous studies have demonstrated that the interactions in local timescales or global matching in statistical structures of fluctuation in long timescales can be sources of the strong-anticipation process. However, the origin of the strong anticipation process often appears elusive in many complex systems. Here, we find that the clapping synchronization process may result from the local interaction between two clapping individuals and may result from the more global coordination between two clapping individuals. We introduce two stochastic models for mutually interacting clapping individuals that generate the LRCCs and prove theoretically that the generation of clapping synchronization process needs to consider both local interaction and global matching. This study provides a statistical framework for studying the internal synchronization mechanism of other complex systems. Our theoretical model can also be applied to study the dynamics of other complex systems with the LRCCs, including finance, transportation, and climate.     

Adsorption kinetics of Eu(III) and Am(III) onto bentonite: analysis and application of the liquid membrane tidal diffusion model

Journal of Radioanalytical and Nuclear Chemistry - A new liquid membrane tidal diffusion model (LMTD) was applied based on three assumptions to analyze the kinetics of Eu(III) adsorption on...