Pressure-Driven Ne-Bearing Polynitrides with Ultrahigh Energy Density

Neon（Ne） can reveal the evolution of planets,and nitrogen（N） is the most abundant element in the Earth’s atmosphere.Considering the inertness of neon,whether nitrogen and neon can react has aroused great interest in condensed matter physics and space science.Here,we identify three new Ne-N compounds(i.e.,NeN₆,NeN₁₀,and NeN₂₂) under pressure by first-principles calculations.We find that inserting Ne into N₂ substantially decreases the polymeric pressure...     

Machine-learning-driven on-demand design of phononic beams

The development of phononic crystals, especially their interaction with topological insulators, allows exploration of the anomalous properties of acoustic/elastic waves for various applications. However, rapidly and inversely exploring the geometry of specific targets remains a major challenge. In this work, we show how machine learning can address this challenge by studying phononic crystal beams using two different inverse design schemes. We first develop the theory of phononic beams using the transfer matrix method. Then, we use the reinforcement learning algorithm to effectively and inversely design the structural parameters to maximize the bandgap width. Furthermore, we employ the tandem-architecture neural network to solve the training-difficulty problem caused by inconsistent data and complete the task of inverse structure design with the targeted topological properties. The two inverse-design schemes have different adaptabilities, and both are characterized by high efficiency and stability. This work provides deep insights into the combination of machine learning, topological property,and phononic crystals and offers a reliable platform for rapidly and inversely designing complex material and structure properties.     

Numerical study of dynamic zigzag patterns in migrating epithelial tissue

Collective cell migration plays a crucial role in embryonic development, metastasis, and wound healing. Nevertheless, to the best of our knowledge, how the coordination between the cell motility and deformations affects the collective motion of epithelial cells is not fully understood. In this work, we propose a modified self-propelled Voronoi model for epithelial cell migration incorporating the coupling between the self-propulsion of cells and the polarization of the cell elongation. At a high coupling strength,we observe the emergence of backward traveling band structures formed by highly aligned cells, which can be regulated by cell elongations or shape anisotropy. Increasing the cell shape anisotropy, we find that large bands split into multiple small microbands. The latter essentially forms a dynamic zigzag pattern, in which the angle between the polarization direction of the bands and the migration direction switches alternatively between π/4 and-π/4 because the cells are forced to move preferentially in the anterior direction. We also analyzed the disclinations in the cell monolayer, force distribution near the domain boundaries and the shape alignment of the epithelial monolayer during the formation of this dynamic pattern. The present findings may further our understanding of stripe pattern formations in living systems and inspire potential designs for cell sorting.     

数学定理教学的“转识成智”——以初中“垂径定理”起始课为例北大核心

1问题提出重视定理教学“过程”是核心素养培养的必然要求,也获得了中小学数学教师的广泛赞同,但有些“过程”却事与愿违.以初中“垂径定理”的教学为例,很多教师并没有关注到这是“圆”章节的起始定理,直接让学生沿直径翻折圆形纸片,得出圆的轴对称性,并用动态课件验证(环节1);继而形式化分析证明圆的轴对称性,由此得到“垂径定理”(环节2).     

由超辐射引起的迁移率边和重返局域化

研究了束缚在梯子形光晶格中的中性原子与高精度腔耦合的系统,发现由超辐射引起的准周期调制可以导致迁移率边和重返局域化现象的出现.在平均场近似下,超辐射现象可以引起两种不同频率的准周期调制,它们可以由腔场和泵浦场有效调节.在本文的观测范围内,当高频调制强度小于某一临界值时,系统随着低频调制强度的增加经历一次局域转变.通过数值求解分形维度、密度分布、平均参与率、平均逆参与率以及标度分析,证明了局域转变历经的临界相区存在迁移率边;当高频调制强度大于临界值时,随着低频调制强度的增强,系统依次经历完全扩展相-临界相-完全局域相-临界相-完全局域相,这是一个典型的重返局域化现象.最后给出了局域化相图.该研究结果为超辐射相变和重返局域化现象的研究建立了联系,也为重返局域化的研究搭建了新的平台.     

以催化应用为纽带链接基础化学2课程与多学科的交叉融合

“基础化学2”是面向“基础学科拔尖学生培养计划”大一本科生开设的一门理科专业基础课。针对学生因专业选择余地大容易觉得课程与专业联系不够紧密而学习积极性不高的问题，提出以元素及其化合物的催化应用为纽带，寻找合适的切入点，将化学基础知识与各相关学科研究前沿及工业应用相联系，建设具有学科交叉特色的基础化学教学体系的建议，突出培养学生的学科创新思维能力，体现理论与实践相结合的教学特色。     

AuNP aggregation-induced quantitative colorimetric aptasensing of sulfadimethoxine with a smartphone

A gold nanoparticle(AuNP) aggregation-induced colorimetric aptasensing method for quantitative detection of sulfadimethoxine(SDM) with a smartphone was developed. AuNPs were complexed with aptamers which protected Au NPs from aggregating in high-concentration salt solutions. In the presence of SDM,SDM bound with the aptamer on the surface of Au NPs with higher affinity, which competitively desorbed the aptamer from the AuNP surface and resulted in AuNPs aggregation, accompanied with a color chan...     

High-performance nonfused ring electron acceptor with a steric hindrance induced planar molecular backbone

Three nonfused ring electron acceptors (NFREAs) TTC6,TT-C8T and TT-TC8 were purposefully designed and synthesized.The molecular geometry can be adjusted by the steric hindrance of lateral substituents.According to the DFT calculations,from TTC6 to TT-C8T and TT-TC8,planarity of the molecular backbone is gradually improved,accompanying with the enhancing of intramolecular charge transfer effect.As for TT-TC8,the two phenyl substituents are almost perpendicular to the molecular backbone,which endues the acceptor with good solubility and suppresses it to form over-aggregation.Multidirectional regular molecular orientation and closer molecular stacking are formed in TT-TC8 film.As a result,TT-TC8 based devices afford the highest PCE of 13.13%,which is much higher than that of TTC6 (4.41%) and TT-C8T (10.42%) and among the highest PCE values based on NFREAs.     

基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.