Fe3O4 – Glutathione stabilized Ag nanoparticles: A new magnetically separable robust and facile catalyst for aqueous phase reduction of nitroarenes

The heterostructured Ag nanoparticles decorated Fe₃O₄ Glutathione (Fe₃O₄‐Glu‐Ag) nanoparticles (NPs) were synthesized by sonicating glutathione (Glu) with magnetite and further surface immobilization of silver NPs on it. The ensuing magnetic nano catalyst is well characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), powder X‐ray diffraction (PXRD), thermogravimetric analysis (TGA). The prepared Fe₃O₄‐Glu‐Ag nanoparticles have proved to be an efficient and recyclable nanocatalyst with low catalyst loading for the reduction of nitroarenes and heteronitroarenes to respective amines in the presence of NaBH₄ using water as a green solvent which could be easily separated at the end of a reaction using an external magnet and can be recycled up to 5 runs without any significant loss in catalytic activity. Gram scale study for the reduction of 4‐NP has also being carried out successfully and it has been observed that this method can serve as an efficient protocol for reduction of nitroarenes on industrial level.     

Synthesis and characterization of molybdenum (VI) complex immobilized on polymeric Schiff base-coated magnetic nanoparticles as an efficient and retrievable nanocatalyst in olefin epoxidation reactions

In this study, a new polymeric functionalized magnetic nanocatalyst containing a molybdenum Schiff base complex was prepared using a few consecutive steps. Poly (methylacrylate)-coated magnetic nanoparticles were synthesized via radical polymerization of methyl acrylate onto modified magnetic nanoparticles followed by the amidation of the methyl ester groups with hydrazine. Polymeric functionalization efficiently provides the advantage that more catalytic units can be grafted on the surface of magnetic nanoparticles. The functionalization process was continued with salicylaldehyde which introduced Schiff base groups on to the surface of the polymeric support. In the final step, the desired catalytic system was prepared via complexation of the Schiff base groups with MoO₂(acac)₂. The resulting nanoparticles were characterized by infrared spectroscopy, powder X-ray diffraction, scanning and transmission electron microscopy, elemental analysis, inductively coupled plasma optical emission spectrometry, vibrating sample magnetometry and thermogravimetric analysis. This heterogenized catalytic system was also found to be highly active, sustainable and recyclable nanocatalyst in alkene epoxidation. Eventually, the attractive features of the synthesized catalyst such as simple work-up, good stability, magnetic separation, high TOF and high surface area; make it appropriate for oxidation reactions.     

Gorenstein平坦模与Frobenius扩张

设R■A是环的Frobenius扩张,其中A是右凝聚环,M是任意左A-模.首先证明了_AM是Gorenstein平坦模当且仅当M作为左R-模也是Gorenstein平坦模.其次,证明了Nakayama和Tsuzuku关于平坦维数沿着Frobenius扩张的传递性定理的"Gorenstein版本":若_AM具有有限Gorenstein平坦维数,则Gfd_A(M)=Gfd_R(M).此外,证明了若R■S是可分Frobenius扩张,则任意A-模(不一定具有有限Gorenstein平坦维数),其Gorenstein平坦维数沿着该环扩张是不变的.     

求解一类可分离凸规划的对偶显式模型DP-EM方法

推导对偶目标函数的精确显式表达式,可选用更多成熟高效的求解方法,从而进一步提高了非线性规划对偶理论求解结构拓扑优化问题的效率.研究工作来源于非线性凸规划同其对偶规划的间隙为零,可以等价转化为对偶问题求解,通常可以大大地缩小问题的规模,可是二者不具有显式关系却影响了对偶解法的应用.所幸的是,结构优化当中一大类问题包括连续体结构拓扑优化问题,不仅具有凸性,而且具有变量可分离性,于是原变量和对偶变量之间有了显式关系,因此,对偶解法成了38年来被应用的有效方法之一.然而长期以来,对偶问题的目标函数并不是显式,这缘于含参数的极小化问题导致目标函数为隐式表达,常见的显式化方法是进行二阶近似.本文突破了对偶问题难以显式化只能采用近似显式的定势,将我们提出的"对偶规划-显式模型"(DP-EM)方法应用于连续体结构拓扑优化,并与对偶序列二次规划(DSQP)算法及移动渐近线(MMA)算法为求解器的方法进行计算效率对比,结果显示:(1)MMA算法比DP-EM算法和DSQP算法的外部迭代次数均多;(2)DP-EM算法与DSQP算法外循环次数相同,而内循环数显著减少.说明了DP-EM算法具有显式对偶函数的优势.     

A note on monolithic scattered compacta

For a Banach space E, it is well-known that a necessary condition for E to have the controlled separable complementation property (CSCP  , for short) is that the dual unit ball _BE?$B_{E^{?}}$ be monolithic in the weak-star topology. We prove here that when X is a scattered first countable locally compact space, then monolithicity of X   turns out to be sufficient for _C0(X)$C_0(X)$ to enjoy the CSCP.     

随机迭代算法的几乎必然T-稳定性及收敛性

目的是在可分Banach空间的框架下,研究某些类型的-弱压缩型的随机算子的Ishikawa-型及Mann-型随机迭代算法的几乎必然T-稳定性及收敛性.在适当的条件下,证明了该类随机算子的随机不动点的Bochner可积性以及这两类随机迭代算法的几乎必然T-稳定性及收敛性.     

An elegant protocol for the synthesis of N-substituted pyrroles through C–N cross coupling/aromatization process using CuFe2O4 nanoparticles as catalyst under ligand-free conditions

A simple and efficient, ligand-free C–N cross-coupling of aryl halides/benzyl bromides with trans-4-hydroxy-l-proline has been developed to produce aromatized N-substituted pyrroles, using a catalytic amount of magnetically separable and recyclable CuFe₂O₄ nanoparticles, in the presence of Cs₂CO₃ in DMSO at 100 °C.     

磁性可见光催化剂BiVO4/Fe3O4的制备及催化活性

采用超声法将磁基体Fe3O4和BiVO4复合,制备了易于固液分离的磁性可见光催化剂BiVO4/Fe3O4。采用X射线衍射(XRD)、傅立叶转换红外光谱(FTIR)、紫外-可见漫反射光谱(DRS)、透射电子显微镜(TEM)和磁学性质测量系统(MPMS)对产物进行了表征,并以亚甲基蓝为目标降解物,考察了BiVO4/Fe3O4的可见光催化活性。当BiVO4与Fe3O4质量比为5:1时,BiVO4/Fe3O4的催化活性最高,反应经过5 h,对亚甲基蓝的降解率达到92.0%,而单独使用BiVO4为催化剂,降解率仅为72.5%。这表明Fe3O4不仅起到磁基体的作用,还起到助催化剂的作用。BiVO4/Fe3O4在外加磁场的作用下很容易被分离,撤消外加磁场后,通过搅拌又可重新分散。BiVO4/Fe3O4 3次回收后的降解率仍高于80%。     

Inverse optimization for linearly constrained convex separable programming problems

In this paper, we study inverse optimization for linearly constrained convex separable programming problems that have wide applications in industrial and managerial areas. For a given feasible point of a convex separable program, the inverse optimization is to determine whether the feasible point can be made optimal by adjusting the parameter values in the problem, and when the answer is positive, find the parameter values that have the smallest adjustments. A sufficient and necessary condition is given for a feasible point to be able to become optimal by adjusting parameter values. Inverse optimization formulations are presented with ℓ₁ and ℓ₂ norms. These inverse optimization problems are either linear programming when ℓ₁ norm is used in the formulation, or convex quadratic separable programming when ℓ₂ norm is used.