A microfluidics-dispensing-printing strategy for Janus photonic crystal microspheres towards smart patterned displays

From the implementation point of view, the printable magnetic Janus colloidal photonic crystals (CPCs) microspheres are highly desirable. Herein, we developed a dispensing-printing strategy for magnetic Janus CPCs display via a microfluidics-automatic printing system. Monodisperse core/shell colloidal particles and magnetic Fe₃O₄ nanoparticles precursor serve as inks. Based on the equilibrium of three-phase interfacial tensions, Janus structure is successfully formed, followed by UV irradiation and self-assembly of colloid particle to generate magnetic Janus CPCs microspheres. Notably, this method shows distinct superiority with highly uniform Janus CPCs structure, where the TMPTA/Fe₃O₄ hemisphere is in the bottom side while CPCs hemisphere is in the top side. Thus, by using Janus CPCs microspheres with two different structural colors as pixel points, a pattern with red flower and green leaf is achieved. Moreover, 1D linear Janus CPCs pattern encapsulated by hydrogel is also fabricated. Both the color and the shape can be changed under the traction of magnets, showing great potentials in flexible smart displays. We believe this work not only offers a new feasible pathway to construct magnetic Janus CPCs patterns by a dispensing-printable fashion, but also provides new opportunities for flexible and smart displays.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

Direct visualization of the nanoscopic three‐phase structure and stiffness of NBR/PVC blends by AFM nanomechanical mapping

The PeakForce Quantitative Nanomechanical Mapping based on atomic force microscope (AFM) is employed to first visualize and then quantify the elastic properties of a model nitrile rubber/poly(vinyl chloride) (NBR/PVC) blend at the nanoscale. This method allows us to consistently observe the changes in mechanical properties of each phase in polymer blends. Beyond measuring and discriminating elastic modulus and adhesion forces of each phase, we tune the AFM tips and the peak force parameters in order to reliably image samples. In view of viscoelastic difference in each phase, a three‐phase coexistence of an unmixed NBR phase, the mixed phase, and PVC microcrystallites is directly visualized in NBR/PVC blends. The nanomechanical investigation is also capable of recognizing the crosslinked rubber phase in cured rubber. The contribution of the mixed phase was quantified and it was found that the mechanical properties of blends are mainly determined by the homogeneity and stiffness of the mixed phase. This study furthers our understanding the structure–mechanical property relationship of thermoplastic elastomers, which is important for their potential design and applications. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 662–669     

Designing Covalent Organic Frameworks with a Tailored Ionic Interface for Ion Transport across One-Dimensional Channels

A strategy based on covalent organic frameworks for ultrafast ion transport involves designing an ionic interface to mediate ion motion. Electrolyte chains were integrated onto the walls of one-dimensional channels to construct ionic frameworks via pore surface engineering, so that the ionic interface can be systematically tuned at the desired composition and density. This strategy enables a quantitative correlation between interface and ion transport and unveils a full picture of managing ionic interface to achieve high-rate ion transport. Moreover, the effect of interfaces was scaled on ion transport; ion mobility is increased in an exponential mode with the ionic interface. This strategy not only sets a benchmark system but also offers a general guidance for designing ionic interface that is key to systems for energy conversion and storage.     

Polypyrrole Shell@3D‐Ni Metal Core Structured Electrodes for High‐Performance Supercapacitors

Three‐dimensional (3D) nanometal films serving as current collectors have attracted much interest recently owing to their promising application in high‐performance supercapacitors. In the process of the electrochemical reaction, the 3D structure can provide a short diffusion path for fast ion transport, and the highly conductive nanometal may serve as a backbone for facile electron transfer. In this work, a novel polypyrrole (PPy) shell@3D‐Ni‐core composite is developed to enhance the electrochemical performance of conventional PPy. With the introduction of a Ni metal core, the as‐prepared material exhibits a high specific capacitance (726 F g^?1 at a charge/discharge rate of 1 A g^?1), good rate capability (a decay of 33 % in C_sp with charge/discharge rates increasing from 1 to 20 A g^?1), and high cycle stability (only a small decrease of 4.2 % in C_sp after 1000 cycles at a scan rate of 100 mV s^?1). Furthermore, an aqueous symmetric supercapacitor device is fabricated by using the as‐prepared composite as electrodes; the device demonstrates a high energy density (≈21.2 Wh kg^?1) and superior long‐term cycle ability (only 4.4 % and 18.6 % loss in C_sp after 2000 and 5000 cycles, respectively).     

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.     

基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。     

基于时变Copula模型的 基金收益率相依关系的应用研究

基于时变Copula模型,获得预测方差,确定单个基金收益率序列的边缘分布.利用常见的静态Copula和时变Copula模型对基金收益率序列间两两相依关系进行建模并进行对比分析.应用研究表明,基于MCMC方法的时变Copula模型能更有效地度量基金收益率序列的风险.     

激光能量对反钙钛矿GaCMn_3薄膜结构与物性的影响

本文采用脉冲激光沉积方法在LaAlO3(001)单晶衬底上制备了反钙钛矿GaCMn3薄膜,通过控制制备过程中脉冲激光的能量,研究了不同激光能量条件对GaCMn3薄膜结构与物理性能的影响.分别利用X射线衍射仪、原子力显微镜、超导量子干涉仪和物理性能测试系统,对所制备的薄膜的晶体结构、表面形貌和磁性、电输运性质进行了研究.结果表明,制备的样品均为具有多个晶面取向的反钙钛矿薄膜,且薄膜结构和物性明显随制备激光能量的变化而变化.当激光能量为450mJ时,制备的薄膜多晶面取向性最弱,结晶性和表面形貌最优良.实验所得的薄膜均表现出顺磁-铁磁-反铁磁相转变,然而转变过程比块材较平缓,同时薄膜的电阻率并未表现出块材中的突变特征,我们推测该现象很可能是由衬底的应力及衬底的晶格膨胀对薄膜反常晶格变化的抑制作用造成的.