Recent progress on low dimensional perovskite solar cells

Low dimensional perovskites have recently attracted much attention due to their vertical growth of crys- talline orientation, excellent film morphology, and long-term humidity, light, and heat stability, How- ever, low dimensional perovskites suffer fl＇om low power conversion efficiency （PCE） with respect to their three dimensional analogues. Therefore, it is imperative to find excellent low-dimensional perovskite materials for improving the PCE. Previous work has demonstrated that bulkier organic molecules, e,g., C6Hs（CH2）2NH3＋ （PEA＋）, CH3（CH2）3NH3＋（n-BAT, iso-BA＋）, C2H4NH3 ＋, and polyethylenimine cations （PEI＋）, play an important role in the formation of low-dimensional perovskites. In this review, we review the recent development of low dimensional perovskites for solar cells application in terms of film preparation, photophysics, and stability of perovskites, as well as the related device structure and physics. We have also discussed the future development of low-dimensional perovskites from materials design, fabri- cation processes, and device structure.

Seismic data reconstruction based on low dimensional manifold model

Seismic data reconstruction is an essential and yet fundamental step in seismic data processing workflow,which is of profound significance to improve migration imaging quality,multiple suppression effect,and seismic inversion accuracy.Regularization methods play a central role in solving the underdetermined inverse problem of seismic data reconstruction.In this paper,a novel regularization approach is proposed,the low dimensional manifold model(LDMM),for reconstructing the missing seismic data.Our work relies on the fact that seismic patches always occupy a low dimensional manifold.Specifically,we exploit the dimension of the seismic patches manifold as a regularization term in the reconstruction problem,and reconstruct the missing seismic data by enforcing low dimensionality on this manifold.The crucial procedure of the proposed method is to solve the dimension of the patches manifold.Toward this,we adopt an efficient dimensionality calculation method based on low-rank approximation,which provides a reliable safeguard to enforce the constraints in the reconstruction process.Numerical experiments performed on synthetic and field seismic data demonstrate that,compared with the curvelet-based sparsity-promoting L1-norm minimization method and the multichannel singular spectrum analysis method,the proposed method obtains state-of-the-art reconstruction results.

Studies of Characterization of Microstructures for Low Dimensional Materials

The characterization of microstructure for three kinds of typical low dimensional materials,such as ultrafine particle(zero- dimension),whisker(one- dimension)and thin film(two-dimensions),has been carried out.The methods and criteria for the characterization are investigated and introduced.Some interesting results of the characterization are reported.

Self-assembling nanoarchitectonics of low dimensional semiconductors for circularly polarized luminescence

Recently,the development of materials with circularly polarized luminescence(CPL)has attracted numerous attentions owing to their potential applications in various fields.Among diverse mechanisms for the origin of chiroptical properties in low dimensional semiconductors(LDS),the self-assembly approach provides a powerful technique for acquisition of strong chiroptical activity.Benefiting from this approach,LDS could be endowed with CPL in which the dissymmetry factor,a vital parameter for evaluating the performance of CPL,could be greatly improved.In this review,state-of-the-art of selfassembled LDS will be summarized.The current challenges and perspectives in this emerging field are also presented.This review could not only provide insights of the fundamentals of self-assembled chirality,but also shine light for designing CPL-active functional nanomaterials toward their applications based on novel optoelectronic devices.

Extraction and application of the low dimensional dynamical component from underwater acoustic target radiating noise

Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.

LOW-DIMENSIONAL STRUCTURES:SP ARSE CODING FOR NEURONAL ACTIVITY

Neuronal ensemble activity codes working memory.In this work,we developed a neuronal ensemble sparse coding method,which can effectively reduce the dimension of the neuronal activity and express neural coding.Multichannel spike trains were recorded in rat prefrontal cortex during a work memory task in Y-maze.As discretesignals,spikes were transferred into cont inuous signals by estinating entropy.Then the normalized continuous signals were decomposed via non-negative sparse met hod.The non-negative components were extracted to reconstruct a low-dimensional ensemble,while none of the feature components were missed.The results showed that,for well-trained rats,neuronal ensemble activities in the prefrontal cortex changed dynamically during the.working memory task.And the neuronal ensemble is more explicit via using non-negative sparse coding.Our results indicate that the neuronal ensemblesparse coding method can effectively reduce the dimnension of neuronal activity and it is a useful tool to express neural coding.

Spurious Solutions in the Multiband Effective Mass Theory Applied to Low Dimensional Nanostructures

In this paper we analyze a long standing problem of the appearance of spurious,non-physical solutions arising in the application of the effective mass theory to low dimensional nanostructures.The theory results in a system of coupled eigenvalue PDEs that is usually supplemented by interface boundary conditions that can be derived from a variational formulation of the problem.We analyze such a system for the envelope functions and show that a failure to restrict their Fourier expansion coeffi-cients to small k components would lead to the appearance of non-physical solutions.We survey the existing methodologies to eliminate this difficulty and propose a simple and effective solution.This solution is demonstrated on an example of a two-band model for both bulk materials and low-dimensional nanostructures.Finally,based on the above requirement of small k,we derive a model for nanostructures with cylindrical symmetry and apply the developed model to the analysis of quantum dots using an eight-band model.

Low-Dimensional Halide Perovskites and Their Advanced Optoelectronic Applications

Metal halide perovskites are crystalline materials originally developed out of scientific curiosity. They have shown great potential as active materials in optoelectronic applications. In the last 6 years, their certified photovoltaic efficiencies have reached 22.1%. Compared to bulk halide perovskites, low-dimensional ones exhibited novel physical properties. The photoluminescence quantum yields of perovskite quantum dots are close to 100%. The external quantum efficiencies and current efficiencies of perovskite quantum dot light-emitting diodes have reached 8% and 43 cd A^(-1),respectively, and their nanowire lasers show ultralow-threshold room-temperature lasing with emission tunability and ease of synthesis. Perovskite nanowire photodetectors reached a responsivity of 10 A W^(-1)and a specific normalized detectivity of the order of 10^(12 )Jones. Different from most reported reviews focusing on photovoltaic applications, we summarize the rapid progress in the study of low-dimensional perovskite materials, as well as their promising applications in optoelectronic devices. In particular, we review the wide tunability of fabrication methods and the state-of-the-art research outputs of low-dimensional perovskite optoelectronic devices. Finally, the anticipated challenges and potential for this exciting research are proposed.

Low-dimensional structures formed by irradiation of laser

Some kinds of low-dimensional nanostructures can be formed by irradiation of laser on the pure silicon sample and the SiGe alloy sample. This paper has studied the photoluminescence （PL） of the hole-net structure of silicon and the porous structure of SiGe where the PL intensity at 706nm and 725nm wavelength increases obviously. The effect of intensity-enhancing in the PL peaks cannot be explained within the quantum confinement alone. A mechanism for increasing PL emission in the above structures is proposed, in which the trap states of the interface between SiO2 and nanocrystal play an important role.

Electronic transport properties of topological insulator films and low dimensional superconductors

在这评论，我们在场拓扑的绝缘体(TI ) 和超导的 nanowires 和电影的一些最近的实验的一篇摘要。电子电子相互作用(EEI ) ，弱反本地化(WAL ) 和效果由运输大小在拓扑的绝缘体电影发现了的各向异性的磁致电阻(AMR ) 被报导。然后，在非超导的 nanowires 的超导的电影，桥和 nanowires 和最近效果的运输性质被描述。最后，在拓扑的绝缘体和超导体(SC ) 之间的相互影响也被讨论。

Origin of Luminescent Centers and Edge States in Low-Dimensional Lead Halide Perovskites:Controversies,Challenges and Instructive Approaches

With only a few deep-level defect states having a high formation energy and dominance of shallow carrier non-trapping defects,the defect-tolerant electronic and optical properties of lead halide perovskites have made them appealing materials for high-efficiency,low-cost,solar cells and light-emitting devices.As such,recent observations of apparently deep-level and highly luminescent states in low-dimensional perovskites have attracted enormous attention as well as intensive debates.The observed green emission in 2D CsPb2Br5 and 0 D Cs4PbBr6 poses an enigma over whether it is originated from intrinsic point defects or simply from highly luminescent CsPbBr3 nanocrystals embedded in the otherwise transparent wide band gap semiconductors.The nature of deep-level edge emission in 2D Ruddlesden–Popper perovskites is also not well understood.In this mini review,the experimental evidences that support the opposing interpretations are analyzed,and challenges and root causes forthe controversy are discussed.Shortcomings in the current density functional theory approaches to modeling of properties and intrinsic point defects in lead halide perovskites are also noted.Selected experimental approaches are suggested to better correlate property with structure of a material and help resolve the controversies.Understanding and identification of the origin of luminescent centers will help design and engineer perovskites for wide device applications.

Heat transport in low-dimensional materials: A review and perspective

Heat transport is a key energetic process in materials and devices. The reduced sample size, low dimension of the problem and the rich spectrum of material imperfections introduce fruitful phenomena at nanoscale. In this review, we summarize recent progresses in the understanding of heat transport process in low-dimensional materials, with focus on the roles of defects, disorder, interfaces, and the quantum- mechanical effect. New physics uncovered from computational simulations, experimental studies, and predictable models will be reviewed, followed by a perspective on open challenges.

A low-dimensional crystal growth model on an isotropic and quasi-free sustained substrate

A new crystal growth theoretical model is established for the low-dimensional nanocrystals on an isotropic and quasifree sustained substrate. The driven mechanism of the model is based on the competitive growth among the preferential growth directions of the crystals possessing anisotropic crystal structures, such as the hexagonal close-packed and wurtzite structures. The calculation results are in good agreement with the experimental findings in the growth process of the lowdimensional Zn nanocrystals on silicone oil surfaces. Our model shows a growth mechanism of various low-dimensional crystals on/in the isotropic substrates.

OPTICAL SPECTRA OF LOW-DIMENSIONAL SEMICONDUCTORS

We have studied the optical spectra of low-dimensional semiconductor systems by calculating all possible optical transitions between electronic states. Optical absorption and emission have been obtained under different carrier population conditions and in different photon wavelengths. The line-shapes of the peaks in the optical spectrum are determined by the density of electronic states of the system, and the symmetries and intensities of these peaks can be improved by reducing the dimensionality of the system. Optical gain requires in general a population inversion, whereas for a quantum-dot system, there exists a threshold value of the population inversion.

Three-dimensional multi-constraint route planning of unmanned aerial vehicle low-altitude penetration based on coevolutionary multi-agent genetic algorithm

To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.

POD Analysis and Low-Dimensional Model Based on POD-Galerkin for Two-Dimensional Rayleigh-Bénard Convection

Direct numerical simulation based on OpenFOAM is carried out for two-dimensional RayleighBénard( RB) convection in a square domain at high Rayleigh number of 107 and Pr = 0.71. Proper orthogonal decomposition( POD) is used to analyze the flow and temperature characteristics from POD energy spectrum and eigenmodes. The results show that the energy spectrum converges fast and the scale of vortex structures captured by eigenmodes becomes smaller as the eigenmode order increases. Meanwhile,a low-dimensional model( LDM) for RB convection is derived based on POD eigenmodes used as a basis of Galerkin project of Navier-Stokes-Boussinesq equations. LDM is built based on different number of eigenmodes and through the analysis of phase portraits,streamline and isothermal predicted by LDM,it is suggested that the error between LDM and DNS is still large.

Preparation,Properties,and Applications of Low-Dimensional Molecular Organic Nanomaterials

In recent years, great progress has been made in research and development of small-molecule organic materials with various low-dimensional nanostructures. This paper presents a comprehensive review of recent research progress in this field, including preparation, electronic and optoelectronic properties and applications. First, an introduction gives to the reprecipitation, soft templates methods, and progress in synthesis and morphological control of low-dimensional small-molecule organic nanomaterials. Their unique optical and electronic properties and research progress in these aspects are reviewed and discussed in detail. Applications based on low-dimensional small-molecule organic nanomaterials are briefly described. Finally, some perspectives to the future development of this field are addressed.

基于时空最优低维动力系统的多尺度可压缩湍流数值模拟方法

按照周培源教授关于研究湍流数值模拟建模时必须分析和求解脉动速度场的思想,该研究基于第一性原理,系统地建立了基于时空低维最优动力系统的多尺度可压缩湍流数值模拟方法(LMS方法),并将其应用于多次冲击Richtmyer-Meshkov问题的数值模拟中,首次得到了可压缩湍流的中尺度流场和不同于DNS近似解的湍流近似解.数值结果表明,LMS方法可以用较少的网格获得更精确的湍流近似解.首先解决了研究中遇到的几个问题,为LMS方法的构建铺平了道路.这些问题是:基于湍流的物理特性,提出了湍流大、中、小尺度分解的新概念;找到了box滤波空间相关性的计算方法;指出了湍流建模理论中长期存在的逻辑错误,提出了多尺度湍流模型的概念;讨论了湍流封闭问题的本质和关键,给出了克服湍流封闭问题的数值方法.采用box滤波方法/空间网格平均方法且在大尺度网格的意义下,LMS方法的本质是一种将RANS、LES、DES和DNS等湍流数值模拟方法统一的全新湍流数值模拟方法.需要指出的是,LMS方法也可以作为湍流模型研究的辅助工具,以检验SGS尺度方程/脉动方程中各项所对应的湍流模型是否正确.

基于不同维度低场核磁共振技术的大豆含油率检测与判别

大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油含水率软件检测大豆含油率;核磁共振成像(magnetic resonance imaging,MRI)结合深度学习,建立大豆含油率高低判别模型。引入低场二维核磁共振(low field two-dimensional nuclear magnetic resonance,LF-2D-NMR)技术,定性分析一维波谱中信号重叠无法区分组分的问题。试验结果表明,LF-NMR含油含水率软件能快速准确检测大豆含油率,T1-T2二维核磁图谱成功解决了自由水和油信号重叠问题。利用U-net++深度学习模型对MRI成像的矢状面、冠状面、横截面以及三面混合数据集进行训练,其中横截面评价指标与其他数据集相比更优,语义分割部分中平均交并比(mean intersection over union,mIoU)约0.9058,全局准确率0.9980,训练后的模型能够将MRI图像识别并分割,快速判别大豆含油率高低。试验证明,LF-NMR及MRI能够快速无损掌握大豆含油率信息,为大豆的高油育种提供了新思路和技术支持。

低温温差条件下不同尺寸比例钢化真空玻璃变形特征研究

钢化真空玻璃导热差且具有冷收缩性能,当两侧玻璃温度差异较明显时,在冷收缩作用下,导致钢化真空玻璃弯曲变形,甚至出现真空环境失效,这极大限制了钢化真空玻璃在寒带地区的推广应用。基于此,进行了低温温差下钢化真空玻璃的变形测试和数值模拟,分析了低温温差和不同尺寸比例下,钢化真空玻璃两侧玻璃之间的协同变形规律。结果表明:试验与数值模拟结果相对误差在2%以内,钢化真空玻璃热-力学耦合模型具有可靠性;低温条件下玻璃整体向上弯曲变形,中心点向内凹陷,变形与温差呈正比关系;同一温差下,钢化真空玻璃长边长度相同时,随着长宽比的减小,长边上的最大变形量会增大。能够为钢化真空玻璃在极寒地区的推广应用及生产工艺的改进提供理论依据。