Highly Robust but Surface‐Active: An N‐Heterocyclic Carbene‐Stabilized Au25 Nanocluster

Surface organic ligands play a critical role in stabilizing atomically precise metal nanoclusters in solutions. However, it is still challenging to prepare highly robust ligated metal nanoclusters that are surface‐active for liquid‐phase catalysis without any pre‐treatment. Now, an N‐heterocyclic carbene‐stabilized Au₂₅ nanocluster with high thermal and air stabilities is presented as a homogenous catalyst for cycloisomerization of alkynyl amines to indoles. The nanocluster, characterized as [Au₂₅(ⁱPr₂‐bimy)₁₀Br₇]²⁺ (ⁱPr₂‐bimy=1,3‐diisopropylbenzimidazolin‐2‐ylidene) ( 1 ), was synthesized by direct reduction of AuSMe₂Cl and ⁱPr₂‐bimyAuBr with NaBH₄ in one pot. X‐ray crystallization analysis revealed that the cluster comprises two centered Au₁₃ icosahedra sharing a vertex. Cluster 1 is highly stable and can survive in solution at 80 °C for 12 h, which is superior to Au₂₅ nanoclusters passivated with phosphines or thiols. DFT computations reveal the origins of both electronic and thermal stability of 1 and point to the probable catalytic sites. This work provides new insights into the bonding capability of N‐heterocyclic carbene to Au in a cluster, and offers an opportunity to probe the catalytic mechanism at the atomic level.     

Optimal Control of Nonlinear Fractional-Order Systems with Multiple Time-Varying Delays

Journal of Optimization Theory and Applications - This paper considers an optimal control problem governed by nonlinear fractional-order systems with multiple time-varying delays and subject to...     

南极假丝酵母在纳米聚苯乙烯上的共价固载及其在微波辅助酯化反应中的应用（英文）

Nanopolystyrene was used as a solid support for the covalent immobilization of Candida antarctica lipase B(Cal B) using the photoreactive reagent 1‐fluoro‐2‐nitro‐4‐azido benzene(FNAB) as a cou‐pling reagent. The obtained derivative was then used as a biocatalyst in a microwave assisted ester‐ification experiment. Factors such as contact time, pH, and enzyme concentration were investigated during immobilization. The hydrolytic activity, thermal, and operational stability of immobi‐lized‐Cal B were determined. The maximum immobilized yield(218 μg/mg support) obtained at pH 6.8 exhibited optimum hydrolytic activity(4.42 × 103 mU p‐nitrophenol/min). The thermal stability of Cal B improved significantly when it was immobilized at pH 10, however, the immobilized yield was very low(93.6 μg/mg support). The immobilized‐Cal B prepared at pH 6.8 and pH 10 retained 50% of its initial activity after incubation periods of 14 and 16 h, respectively, at 60 °C. The opera‐tional stability was investigated for the microwave assisted esterification of oleic acid with metha‐nol. Immobilized‐Cal B retained 50% of its initial activity after 15 batch cycles in the micro‐wave‐assisted esterification. The esterification time was notably reduced under microwave irradia‐tion. The combined use of a biocatalyst and microwave heating is thus an alternative total green synthesis process.     

Development of LBGK and incompressible LBGK‐based lattice Boltzmann flux solvers for simulation of incompressible flows

This paper presents lattice Boltzmann Bhatnagar–Gross–Krook (LBGK) model and incompressible LBGK model‐based lattice Boltzmann flux solvers (LBFS) for simulation of incompressible flows. LBFS applies the finite volume method to directly discretize the governing differential equations recovered by lattice Boltzmann equations. The fluxes of LBFS at each cell interface are evaluated by local reconstruction of lattice Boltzmann solution. Because LBFS is applied locally at each cell interface independently, it removes the major drawbacks of conventional lattice Boltzmann method such as lattice uniformity, coupling between mesh spacing, and time interval. With LBGK and incompressible LBGK models, LBFS are examined by simulating decaying vortex flow, polar cavity flow, plane Poiseuille flow, Womersley flow, and double shear flows. The obtained numerical results show that both the LBGK and incompressible LBGK‐based LBFS have the second order of accuracy and high computational efficiency on nonuniform grids. Furthermore, LBFS with both LBGK models are also stable for the double shear flows at a high Reynolds number of 10⁵. However, for the pressure‐driven plane Poiseuille flow, when the pressure gradient is increased, the relative error associated with LBGK model grows faster than that associated with incompressible LBGK model. It seems that the incompressible LBGK‐based LBFS is more suitable for simulating incompressible flows with large pressure gradients. Copyright © 2014 John Wiley & Sons, Ltd.     

Achieving Molecular Recognition of Structural Analogues in Surface-Enhanced Raman Spectroscopy: Inducing Charge and Geometry Complementarity to Mimic Molecular Docking

Molecular recognition of complex isomeric biomolecules remains challenging in surface-enhanced Raman scattering (SERS) spectroscopy due to their small Raman cross-sections and/or poor surface affinities. To date, the use of molecular probes has achieved excellent molecular sensitivities but still suffers from poor spectral specificity. Here, we induce “charge and geometry complementarity” between probe and analyte as a key strategy to achieve high spectral specificity for effective SERS molecular recognition of structural analogues. We employ 4-mercaptopyridine (MPY) as the probe, and chondroitin sulfate (CS) disaccharides with isomeric sulfation patterns as our proof-of-concept study. Our experimental and in silico studies reveal that “charge and geometry complementarity” between MPY's binding pocket and the CS sulfation patterns drives the formation of site-specific, multidentate interactions at the respective CS isomerism sites, which “locks” each CS in its analogue-specific complex geometry, akin to molecular docking events. Leveraging the resultant spectral fingerprints, we achieve > 97 % classification accuracy for 4 CSs and 5 potential structural interferences, as well as attain multiplex CS quantification with < 3 % prediction error. These insights could enable practical SERS differentiation of biologically important isomers to meet the burgeoning demand for fast-responding applications across various fields such as biodiagnostics, food and environmental surveillance.     

Structure-based design of Aurora A & B inhibitors

The Aurora family of serine/threonine kinases are mitotic regulators involved in centrosome duplication, formation of the bipolar mitotic spindle and the alignment of the chromosomes along the spindle. These proteins are frequently overexpressed in tumor cells as compared to normal cells and are therefore potential therapeutic oncology targets. An Aurora A high throughput screen revealed a promising sub-micromolar indazole-benzimidazole lead. Modification of the benzimidazole portion of the lead to a C2 linker with a phenyl ring was proposed to achieve novelty. Docking revealed that a conjugated linker was optimal and the resulting compounds were equipotent with the lead. Further structure-guided optimization of substituents on the 5 & 6 position of the indazole led to single digit nanomolar potency. The homology between the Aurora A & Aurora B kinase domains is 71% but their binding sites only differ at residues 212 & 217 (Aurora A numbering). However interactions with only the latter residue may be used for obtaining selectivity. An analysis of published Aurora A and Aurora B X-ray structures reveals subtle differences in the shape of the binding sites. This was exploited by introduction of appropriately sized substituents in the 4 & 6 position of the indazole leading to Aurora B selective inhibitors. Finally we calculate the conformational energy penalty of the putative bioactive conformation of our inhibitors and show that this property correlates well with the Aurora A binding affinity.     

A computational method for a class of non-standard time optimal control problems involving multiple time horizons

In this paper, we consider a class of non-standard time optimal control problems involving a dynamical system consisting of multiple subsystems evolving over different time horizons. Different subsystems are required to reach their respective target sets at different termination times. The goal is to minimize the maximum of these termination times. By introducing a discrete variable to represent the system termination ordering, we reformulate this problem as a discrete optimization problem. A discrete filled function method is developed to solve this discrete optimization problem. For illustration, a numerical example is solved.