Electro-assisted Molecular Assembly Giving Atomic-Scale Catalytic Active-Site Detection

The artificially accurate design of nonmetal electrocatalysts’ active site has been a huge challenge because no pure active species with the specific structure could be strictly controlled by traditional synthetic methods. Species with a multiconfiguration in the catalyst hinder identification of the active site and the subsequent comprehension of the reaction mechanism. We have developed a novel electro-assisted molecular assembly strategy to obtain a pure pentagon ring on perfect graphene avoiding other reconstructed structures. More importantly, the active atom was confirmed by the subtle passivation process as the topmost carbon atom. Recognition of the carbon-defect electrocatalysis reaction mechanism was first downsized to the single-atom scale from the experimental perspective. It is expected that this innovative electro-assisted molecular assembly strategy could be extensively applied in the active structure-controlled synthesis of nonmetal electrocatalysts and verification of the exact active atom.     

Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.     

Bimetallic Covalent Organic Frameworks for Constructing Multifunctional Electrocatalyst

Covalent organic frameworks (COFs) are a new class of crystalline porous polymers comprised mainly of carbon atoms, and are versatile for the integration of heteroatoms such as B, O, and N into the skeletons. The designable structure and abundant composition render COFs useful as precursors for heteroatom-doped porous carbons for energy storage and conversion. Herein, we describe a multifunctional electrochemical catalyst obtained through pyrolysis of a bimetallic COF. The catalyst possesses hierarchical pores and abundant iron and cobalt nanoparticles embedded with standing carbon layers. By integrating these features, the catalyst exhibits excellent electrochemical catalytic activity in the oxygen reduction reaction (ORR), with a 50 mV positive half-wave potential, a higher limited diffusion current density, and a much smaller Tafel slope than a Pt-C catalyst. Moreover, the catalyst displays superior electrochemical performance toward the hydrogen evolution reaction (HER), with overpotentials of −0.26 V and −0.33 V in acidic and alkaline aqueous solution, respectively, at a current density of 10 mA cm⁻². The overpotential in the catalysis of the oxygen evolution reaction (OER) was 1.59 V at the same current density.     

Novel and stereocontrolled asymmetric synthesis of a new naturally occurring styryllactone, (+)-cardiobutanolide

An efficient and stereodefined strategy is described for the asymmetric synthesis of a new styryllactone from the stem bark of Goniothalamus cardiopetalus, cardiobutanolide. The synthetic process is based on requisite manipulation of the functionalized bicyclic lactol-lactone intermediate incorporating the glucuronolactone-derived skeleton in a complete stereoselective manner.     

On a poisson reduction for Gel'fand-Zakharevich manifolds

We formulate and discuss a reduction theorem for Poisson pencils associated with a class of integrable systems, defined on bi-Hamiltonian manifolds, recently studied by Gel'fand and Zakharevich. The reduction procedure is suggested by the bi-Hamiltonian approach to the separation of variables problem.     

Reductions of interval nonlinear programming problem

A general nonlinear programming problem with interval functions is considered. Two reductions of this problem to the deterministic nonlinear programming problem are proposed, and illustrative examples are discussed.     

Baker＇s Yeast Mediated Reduction of Optically Active Diketone

Baker‘s yeast mediated reduction of optically active diketone is described. The two keto groups are efficiently differentiated and the ee value of the recovered material is considerably raised. It affords highly optically active key intermediates efficiently for the synthesis of natural polyhydroxylated agarofuran products.     

Karhunen–Loeve representations of turbulent channel flows using the method of snapshots

For three‐dimensional flows with one inhomogeneous spatial coordinate and two periodic directions, the Karhunen–Loeve procedure is typically formulated as a spatial eigenvalue problem. This is normally referred to as the direct method (DM). Here we derive an equivalent formulation in which the eigenvalue problem is formulated in the temporal coordinate. It is shown that this so‐called method of snapshots (MOS) has some numerical advantages when compared to the DM. In particular, the MOS can be formulated purely as a matrix composed of scalars, thus avoiding the need to construct a matrix of matrices as in the DM. In addition, the MOS avoids the need for so‐called weight functions, which emerge in the DM as a result of the non‐uniform grid typically employed in the inhomogeneous direction. The avoidance of such weight functions, which may exhibit singular behaviour, guarantees satisfaction of the boundary conditions. The MOS is applied to data sets recently obtained from the direct simulation of turbulence in a channel in which viscoelasticity is imparted to the fluid using a Giesekus model. The analysis reveals a steep drop in the dimensionality of the turbulence as viscoelasticity is increased. This is consistent with the results that have been obtained with other viscoelastic models, thus revealing an essential generic feature of polymer‐induced drag reduced turbulent flows. Published in 2006 by John Wiley & Sons, Ltd.     

空间有源消声的微机控制

本文讨论用通用微机控制空间有源消声．以修正的PID（比例、积分、微分）算法加上逻辑判断构成的控制软件，使得系统收敛迅速，跟踪速度快，消声效果令人满意，而且系统工作稳定可靠，     

Scheduling orders for multiple product types to minimize total weighted completion time

We consider the problem of scheduling orders for multiple different product types in an environment with m dedicated machines in parallel. The objective is to minimize the total weighted completion time. Each product type is produced by one and only one of the m dedicated machines; that is, each machine is dedicated to a specific product type. Each order has a weight and may also have a release date. Each order asks for certain amounts of various different product types. The different products for an order can be produced concurrently. Preemptions are not allowed. Even when all orders are available at time 0, the problem has been shown to be strongly NP-hard for any fixed number (?2) of machines. This paper focuses on the design and analysis of efficient heuristics for the case without release dates. Occasionally, however, we extend our results to the case with release dates. The heuristics considered include some that have already been proposed in the literature as well as several new ones. They include various static and dynamic priority rules as well as two more sophisticated LP-based algorithms. We analyze the performance bounds of the priority rules and of the algorithms and present also an in-depth comparative analysis of the various rules and algorithms. The conclusions from this empirical analysis provide insights into the trade-offs with regard to solution quality, speed, and memory space.