Janus Quasi‑Solid Electrolyte Membranes with Asymmetric Porous Structure for High‑Performance Lithium‑Metal Batteries

Quasi-solid electrolytes(QSEs)based on nanoporous materials are promising candidates to construct high-performance Limetal batteries(LMBs).However,simultaneously boosting the ionic conductivity(σ)and lithium-ion transference number(t^(+)) of liquid electrolyte confined in porous matrix remains challenging.Herein,we report a novel Janus MOFLi/MSLi QSEs with asymmetric porous structure to inherit the benefits of both mesoporous and microporous hosts.This Janus QSE composed of mesoporous silica and microporous MOF exhibits a neat Li^(+) conductivity of 1.5.10^(–4)S cm^(−1) with t^(+) of 0.71.A partially de-solvated structure and preference distribution of Li^(+)near the Lewis base O atoms were depicted by MD simulations.Meanwhile,the nanoporous structure enabled efficient ion flux regulation,promoting the homogenous deposition of Li^(+).When incorporated in Li||Cu cells,the MOFLi/MSLi QSEs demonstrated a high Coulombic efficiency of 98.1%,surpassing that of liquid electrolytes(96.3%).Additionally,NCM 622||Li batteries equipped with MOFLi/MSLi QSEs exhibited promising rate performance and could operate stably for over 200 cycles at 1 C.These results highlight the potential of Janus MOFLi/MSLi QSEs as promising candidates for next-generation LMBs.

Value and Measures of Integrating Local Red Culture into the Ideological and Political Course of Environmental Disciplines under the OBE Concept

Based on output-oriented education,the OBE(Outcome-Based Education)concept integrates local red culture into the ideological and political course of environmental disciplines,and is an important part of training applied talents of environmental disciplines in the new era.This educational model makes an innovation on the traditional educational and teaching concepts and centers on students.This paper analyzes the value of integrating local red culture into the ideological and political course under the OBE concept,and puts forward an effective implementation path.

Towards growth of pure AB-stacked bilayer graphene single crystals

Given its intriguing band structure and unique tunable bandgap,AB-stacked bilayer graphene has great potentials in the applications of high-end electronics,optoelectronics and semiconductors.The epitaxial growth of AB-stacked single-crystal bilayer graphene films requires a strict AB-stacked lattice,identical orientations and seamless stitching of bilayer graphene islands.However,the particles inevitably present on the metal surface that produced during high temperature growth would induce random orientations,twisted stacking islands,and uncontrollable multilayers,which is a great challenge to overcome.Here,we propose a heat-resisting-box assisted strategy to produce nearly pure AB-stacked bilayer graphene single-crystal films on Cu/Ni(111)foils.With our technique,the particles on the Cu/Ni(111)surface are effectively eliminated,which greatly minimizes the occurrence of randomly twisted islands and uncontrollable multilayers.The as-grown AB-stacked bilayer graphene films show>99%alignment and>99%AB stacking order.Our work provides a promising method towards the growth of pure AB-stacked bilayer graphene single crystals and would accelerate its device applications.

低对称性的亚波长阵列增强型的GeSe偏振探测器

偏振敏感光电探测器可通过探测光偏振态的变化从而分辨纹理、应力和粗糙度等多种信息,在安全、医疗诊断和航空航天领域具有独特的优势.基于面内各向异性的二维材料的偏振光探测器可简化传统探测器的复杂透镜系统,促进了光电器件的集成化与小型化.然而,基于面内各向异性的二维材料的偏振光探测器的光电流各向异性比不足(通常小于10),限制了偏振信号的检测分辨率.本文设计了基于二维硒化亚锗(GeSe)的亚波长阵列(SWA)结构,进一步提高其各向异性灵敏度,并将光电流各向异性从1.6提高到18.本研究发现,SWA结构可以进一步增强电荷分布的不对称性,提高GeSe材料在扶手椅方向上的光吸收和光电跃迁概率,从而提高了偏振灵敏度.此外,基于GeSe SWA的光电探测器在808 nm的近红外波长下表现出宽的功率范围(40 dB)和弱光探测能力(0.1 LUX).该工作为提高二维材料的偏振灵敏度提供了可行性指导,将有利于促进高分辨率偏振成像传感器的发展.

基于自判别循环生成对抗网络的人脸图像翻译

人脸跨域翻译是将人脸图像从一个图像域映射到另一个图像域的过程,常见的人脸图像翻译任务包括人脸照片–素描、人脸照片–线条画跨域翻译等,可以广泛应用于现实场景,如协助刑侦、电影制作、数字娱乐.但是成对的人脸图像数据有限,且不同域之间的颜色、纹理差异较大,导致人脸图像跨域翻译仍面临着巨大挑战.现有的方法通常会产生模糊、伪影、结构失真等问题,导致较差的视觉效果.为解决这一问题,我们提出了一个自判别循环生成对抗网络,其中,生成器部分采用编码器–解码器结构,生成器对应的判别器为翻译方向相反的编码器,通过自判别的形式,使编码器(即判别器)巧妙地融合了“真/假”语义判别能力与对像素改变的敏感性,从而增强了模型的稳健性和泛化能力.其次,我们提出了一个新颖的全向像素梯度损失函数,设计的卷积核计算了每个像素周围每个方向的梯度来提取图像的梯度信息,通过约束生成图像与对应真实图像的梯度信息保持一致,从而激励模型有效地学习像素间连续变化的模式,并且该损失函数可以灵活地应用于其他生成模型以提升性能.大量的实验表明本文提出的框架能够在公开的成对的人脸照片–素描数据集(CUFS,CUFSF)以及人脸照片–线条画数据集(APDrawing)上取得优异的结果.此外,通过泛化能力验证实验,我们进一步展示了模型在真实场景数据上的强泛化能力,以及自判别循环生成对抗网络结构在非成对人脸数据集上的出色性能.