Destination-aware metric based social routing for mobile opportunistic networks

Wireless Networks - Although centrality is widely used to differentiate the importance of nodes for social-aware routing in mobile opportunistic networks (MONs), it is destination-agnostic since...     

子集模拟中马尔可夫链蒙特卡洛抽样算法比较

文章着重研究子集模拟中马尔可夫链蒙特卡洛(MCMC)抽样算法的抽样效率与计算精度。首先，阐述可靠度子集模拟的基本原理与中间状态样本生成的各种MCMC抽样算法，在稳态马尔可夫链构造基础上提出延迟拒绝MMH(Modified Metropolis Hasting)算法，通过在MMH算法上增加备选样本的延迟拒绝步提高MMH算法的抽样效率；阐述基于随机游走与基于扩散方程MCMC方法中建议分布的差异，进一步对备选样本接受率为1的preconditioned Crank-Nicolson(pCN)算法和条件抽样(Conditional sampling, CS)算法开展研究，证明两种算法的等价性；推导有效样本量的计算方法，提出采用有效样本量与总样本量的比值定义MCMC方法的抽样效率。通过复杂目标分布的样本生成研究不同MCMC抽样算法建议分布及其参数对备选样本接受率与抽样效率的影响，最后通过计算实例研究子集模拟过程采用不同MCMC抽样算法得到失效概率的相对误差及其变异性，揭示不同MCMC抽样算法对失效概率计算精度的影响。研究表明：不同MCMC抽样算法生成备选样本的接受率及其自相关性受建议分布及其参数影响较大，对于复杂的目标分布，pCN算法和CS算法的抽样效率较高，延迟拒绝MMH算法次之；采用CS算法和延迟拒绝MMH算法进行子集模拟得到的失效概率精度较高且变异性较低；增加子集模拟中间状态样本量可以提高失效概率计算精度并降低其变异性。     

A high-throughput chaotic advection microreactor for preparation of uniform and aggregated barium sulfate nanoparticles

A high-throughput (105.5 g/h) passive four-stage asymmetric oscillating feedback microreactor using chaotic mixing mechanism was developed to prepare aggregated Barium sulfate (BaSO₄) particles of high primary nanoparticle size uniformity. Three-dimensional unsteady simulations showed that chaotic mixing could be induced by three unique secondary flows (i.e., vortex, recirculation, and oscillation), and the fluid oscillation mechanism was examined in detail. Simulations and Villermaux–Dushman experiments indicate that almost complete mixing down to molecular level can be achieved and the prepared BaSO₄ nanoparticles were with narrow primary particle size distribution (PSD) having geometric standard deviation, σ_g, less than 1.43 when the total volumetric flow rate Q_total was larger than 10 ml/min. By selecting Q_total and reactant concentrations, average primary particle size can be controlled from 23 to 109 nm as determined by microscopy. An average size of 26 nm with narrow primary PSD (σ_g = 1.22) could be achieved at Q_total of 160 ml/min.     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

Computational and experimental study of dental resin composites with high filler content

Journal of Materials Science - Nanocomposites have been used in various industries due to their excellent properties. For some of them, high filler content (over 50 wt%) is beneficial to improving...     

Surface Modification of Co3O4 Nanosheets to Promote Peroxymonosulfate Activation for Degradation of Atrazine

Catalysis Letters - This study proposed a new facile route to rational creating oxygen-vacancy (Vo)-rich surface of Co3O4 nanosheets by acetic acid leaching. The acid leached Co3O4 nanosheets was...