Visible-light-induced,autopromoted nickel-catalyzed three-component arylsulfonation of 1,3-enynes and mechanistic insights

Science China Chemistry - A light-induced, nickel-catalyzed three-component arylsulfonation of 1,3-enynes in the absence of photocatalyst is reported. This methodology exhibited mild conditions,...     

Chemical Composition and Antimicrobial Activity of Essential Oil from the Rhizomes of Curcuma pambrosima Growing in Vietnam

Chemistry of Natural Compounds -     

A Novel Ternary Composite of Polyurethane/Polyaniline/Nanosilica with Antistatic Property and Excellent Mechanical Strength: Preparation and Mechanism

Chinese Journal of Polymer Science - Antistatic and strength properties are of vital importance for polyurethane rubber used in moving parts of many industrial instruments. Herein, polyurethane was...     

Event-triggered based $$\pmb {L_{2}-L_{\infty }}$$L2-L∞ filtering for multiagent systems with Markovian jumping topologies under time-varying delays

Nonlinear Dynamics - In this article, we analyze the $$L_{2}-L_{\infty }$$ filtering of multiagent systems for Markovian switch topologies under time-varying delays with an influence of...     

Recent Advances in Spatial Self-Phase Modulation with 2D Materials and its Applications

In recent years, spatial self-phase modulation (SSPM) with two-dimensional (2D) materials has attracted the attention of many researchers as an emerging and ubiquitous nonlinear optical effect. In this review, the state of the art of 2D material-based SSPM is summarized. SSPM measures or tunes the nonlinearity of 2D materials, and it is also an effective approach to study the band structure of 2D materials. Several modified forms of SSPM, such as high-order, white-light-excited, vector field excited, and optically nonlinearly enhanced SSPM are also presented. Subsequently, the physical origin of the SSPM formation mechanism is compared and analyzed. Furthermore, the applications of SSPM with 2D materials, including passive photonic devices, generation of Bessel beams, and identifying the mode of the orbital angular momentum, are listed. Finally, several urgent problems of the SSPM with 2D materials, potential applications, and prospects for future development are presented.     

HgCdTe薄膜的输运特性及其应力调控

窄禁带直接带隙半导体材料碲镉汞(Hg1–xCdxTe)是一种在红外探测与自旋轨道耦合效应基础研究方面都具有重要应用意义的材料.本文对单晶生长的体材料Hg0.851Cd0.149Te进行阳极氧化以形成表面反型层,将样品粘贴在压电陶瓷上减薄后进行磁输运测试,在压电陶瓷未加电压时观察到了明显的SdH振荡效应.对填充因子与磁场倒数进行线性拟合,获得样品反型层二维电子气的载流子浓度为ns=1.25×10^16m^-2.在不同磁场下,利用压电陶瓷对样品进行应力调控,观测到具有不同特征的现象,分析应是样品中存在二维电子气与体材料两个导电通道.零磁场下体材料主导的电阻的变化应来源于应力导致的带隙的改变;而高场下产生类振荡现象的原因应为应力导致的二维电子气能级的分裂.     

Reconstruction of stability for Gaussian spatial solitons in quintic–septimal nonlinear materials under $${{\varvec{\mathcal {P}}}}{\varvec{\mathcal {T}}}$$ P T -symmetric potentials

Nonlinear Dynamics - Gaussian spatial soliton solutions of both the constant-coefficient and variable-coefficient (2 + 1)-dimensional nonlinear Schrödinger equations in...     

Origins of Boosted Charge Storage on Heteroatom-Doped Carbons

Although tremendous efforts have been devoted to understanding the origin of boosted charge storage on heteroatom-doped carbons, none of the present studies has shown a whole landscape. Herein, by both experimental evidence and theoretical simulation, it is demonstrated that heteroatom doping not only results in a broadened operating voltage, but also successfully promotes the specific capacitance in aqueous supercapacitors. In particular, the electrolyte cations adsorbed on heteroatom-doped carbon can effectively inhibit hydrogen evolution reaction, a key step of water decomposition during the charging process, which broadens the voltage window of aqueous electrolytes even beyond the thermodynamic limit of water (1.23 V). Furthermore, the reduced adsorption energy of heteroatom-doped carbon consequently leads to more stored cations on the heteroatom-doped carbon surface, thus yielding a boosted charge storage performance.     

基于深度学习的离轴菲涅耳数字全息非线性重构

针对离轴菲涅耳数字全息图,提出基于深度学习的单幅数字全息非线性重构方法 .采用经典的菲涅耳衍射积分模拟数字全息成像以供给网络训练所需样本,利用深度卷积残差神经网络通过学习数字全息图与相关物像之间的非线性数学映射关系实现全息图的物像重构.数值模拟表明,与传统的频率滤波和四步相移技术实现菲涅耳数字全息重构相比,本文提出的方法可直接消除零级像及孪生像,无需条纹物项抽取预处理步骤,且重构的物像具有较高的质量,针对相同记录参考光下不同衍射距离所生成的测试集亦具有较强的稳健性.