Surface Reconstruction Engineering with Synergistic Effect of Mixed-Salt Passivation Treatment toward Efficient and Stable Perovskite Solar Cells

Surface passivation treatment is a widely used strategy to resolve trap-mediated nonradiative recombination toward high-efficiency metal-halide perovskite photovoltaics. However, a lack of passivation with mixture treatment has been investigated, as well as an in-depth understanding of its passivation mechanism. Here, a systematic study on a mixed-salt passivation strategy of formamidinium bromide (FABr) coupled with different F-substituted alkyl lengths of ammonium iodide is demonstrated. It is obtained better device performance with decreasing chain length of the F-substituted alkyl ammonium iodide in the presence of FABr. Moreover, they unraveled a synergistic passivation mechanism of the mixed-salt treatment through surface reconstruction engineering, where FABr dominates the reformation of the perovskite surface via reacting with the excess PbI₂. Meanwhile, ammonium iodide passivates the perovskite grain boundaries both on the surface and top perovskite bulk through penetration. This synergistic passivation engineer results in a high-quality perovskite surface with fewer defects and suppressed ion migration, leading to a champion efficiency of 23.5% with mixed-salt treatment. In addition, the introduction of the moisture resisted F-substituted groups presents a more hydrophobic perovskite surface, thus enabling the decorated devices with excellent long-term stability under a high humid atmosphere as well as operational conditions.     

Synthesis of Ionic Ultramicroporous Polymers for Selective Separation of Acetylene from Ethylene

The design of highly stable and efficient porous materials is essential for developing breakthrough hydrocarbon separation methods based on physisorption to replace currently used energy-intensive distillation/absorption technologies. Efforts to develop advanced porous materials such as zeolites, coordination frameworks, and organic polymers have met with limited success. Here, a new class of ionic ultramicroporous polymers (IUPs) with high-density inorganic anions and narrowly distributed ultramicroporosity is reported, which are synthesized by a facile free-radical polymerization using branched and amphiphilic ionic compounds as reactive monomers. A covalent and ionic dual-crosslinking strategy is proposed to manipulate the pore structure of amorphous polymers at the ultramicroporous scale. The IUPs exhibit exceptional selectivity (286.1–474.4) for separating acetylene from ethylene along with high thermal and water stability, collaboratively demonstrated by gas adsorption isotherms and experimental breakthrough curves. Modeling studies unveil the specific binding sites for acetylene capture as well as the interconnected ultramicroporosity for size sieving. The porosity-engineering protocol used in this work can also be extended to the design of other ultramicroporous materials for the challenging separation of other key gas constituents.     

NH_3-OH体系中共沉淀法同时回收钕铁硼废料中Nd-Pr-Co-Fe

为了避免回收单一钕铁硼废料中有价元素带来的操作复杂和资源浪费等问题,本研究采用共沉淀法共沉淀出钕铁硼废料中的有价元素Me(Nd,Pr,Co,Fe),制备可用于生产再生钕铁硼的原料;根据质量守恒和同时平衡原理,采用MATLAB软件建立Me(Nd,Pr,Co,Fe)-OH--NH3热力学模型,绘制lg[Me]-p H曲线模拟共沉淀工艺,并根据模拟结果确立了共沉淀工艺;模拟和实验的结果表明:根据lg[Me]-p H模拟结果可以确立一步共沉淀法的p H:6~10,Fe3+比Fe2+更易于沉淀完全;在上述条件下获得的共沉淀粉末主相均为Nd,Pr,Co,Fe的化合物,且有价元素的百分比含量均大于99.4%;其中,当p H值在8左右时回收率最高,在该条件下金属元素Me(Nd,Pr,Co,Fe)的沉淀效率分别为:98.7%,99.9%,93.6%,99.9%。该结果也表明共沉淀法工艺不仅高效,而且所制备的共沉淀粉末可以满足制备二次钕铁硼的需要。     

几种吸附式致冷新工质对的性能预测

应用吸附平衡基本理论对几种可能的吸附式致冷新工质对的性能进行了预测。结果表明，烷烃系列的低混点工质与沸石的配对体系是不可取的，而沸石－氨、活性炭－丙酮、活性炭－氨及活性炭－乙醇则是沸石－水、活性炭－甲醇体系的适宜的替代物。     

RETRACTED ARTICLE: Intelligent traffic monitoring and traffic diagnosis analysis based on neural network algorithm

Traffic sign recognition and lane detection play an important role in traffic flow planning, avoiding traffic accidents, and alleviating traffic chaos. At present, the traffic intelligent recognition rate still needs to be improved. In view of this, based on the neural network algorithm, this study constructs an intelligent transportation system based on neural network algorithm, and combines machine vision technology to carry out intelligent monitoring and intelligent diagnosis of traffic system. In addition, this study discusses in detail the core of the monitoring system: multi-target tracking algorithm, and introduces the complete implementation process and details of the system, and highlights the implementation and tracking effect of the multi-target tracker. Finally, this study uses case identification to analyze the effectiveness of the algorithm proposed by this paper. The research results show that the proposed method has certain practical effects and can be used as a reference for subsequent system construction.

     

Extension of the DEMATEL method in an uncertain linguistic environment

The decision making trial and evaluation laboratory (DEMATEL) method is a useful tool for analyzing correlations among factors using crisp values. However, the crisp values are inadequate to model real-life situations due to the fuzziness and uncertainty that are frequently involved in judgments of experts. The aim of this paper is to extend the DEMATEL method to an uncertain linguistic environment. In this paper, the correlation information among factors provided by experts is in the form of uncertain linguistic terms. A formula is first presented to transform correlation information from uncertain linguistic terms to trapezoidal fuzzy numbers. Then, we aggregate the transformed correlation information of each expert into group information using the operations of trapezoidal fuzzy numbers. The importance and classification of factors are determined via fuzzy matrix operations. Furthermore, a causal diagram is constructed to vividly show the different roles of factors. Finally, an example is used to illustrate the procedure of the proposed method.     

空间低温氧化物熔体晶体生长的数字模拟研究

地面上 ,由于受浮力对流、分层和沉淀等因素的影响 ,难以阐明晶体生产和凝固现象的本质 ,从而无法获得组份均匀、结构完整和性能优良的材料 ,因此自七十年代以来 ,已进行了大量的空间晶体生长实验 ,但由于对空间环境在晶体生长过程中的流体效应参数缺乏了解 ,实验结果往往与设想的不一致。数字模拟方法可以模拟实际晶体生产过程 ,了解晶体生长参数的变化对晶体生长的影响 ,本文利用数字模拟的方法 ,对本实验室建立的空间三维实时观察装置中 ,低温生产NaNO3熔体晶体中的流体效应及温场进行了数字模拟研究 ,结果表明 ,在地面生长 ,熔体内部存在复杂的双涡流动模式 ,重力对熔体中的温场和速度场的分布产生强烈的作用 ,而在空间 ,当微重力水平达到一定程度时 ,可以使熔体中的流动模式简单化 ,从而降低流动效应对传热、传质造成的不稳定性和不均匀性 ,有利于提高晶体生长的质量。同时通过对流场中的温度分布分析表明 ,降低重力可以明显改变晶体生长固液界面附近的温度梯度 ,并使温场 ,速度场分布朝着稳态生长的方向发展     

基于悬停四旋翼位置姿态信息的风场估计方法研究

基于四旋翼飞行器悬停状态下的位置及姿态信息,提出了一种离线的风场估计方法。首先根据Dryden大气紊流模型建立了四旋翼飞行器所处的风场环境,并通过分析有风情况下旋翼升力的变化,得到旋翼升力与风场信息(风速、风向)的函数关系式;接着利用牛顿-欧拉方法推导出有风扰动下的四旋翼动力学方程,并进一步设计了用于保持飞行器悬停状态的PID控制器;最后,基于悬停状态下四旋翼飞行器的位置姿态信息,计算得到飞行器所处的风场环境信息。MATLAB仿真结果表明所提方法在有紊流干扰的情况下,能够有效地提取出风场环境里的主风信息。     

基于稀疏强特征提取的三维地震数据完备方法

随着复杂储层地震资料特征筛选的机器学习技术的进步,如何有效地对参与地震属性优选和储层反演的地震样本进行采集和分析,成为目前智能地震预测领域的一个研究热点。目前的方法多着重于模型分类算法的改进,在标签的制作和采集方面不仅耗费大量时间进行人工标注,还存在标签不平衡情况下类内可靠性、类间平衡性不强等问题。为此,提出基于稀疏强特征提取的三维地震数据完备方法。首先,基于多数决原则的样本分割(Sample Segmentation Based on Majority Rule, SSMR)寻迹多尺度、多标签三维地震样本,进行采集、自动标注;然后,改进标签洗牌平衡方法(Improved Label Shuffling Balance Method, ILSB),通过“2+1”的样本增广平衡策略进行数据完备处理,改善样本采样不平衡性导致的模型训练偏向性;最后,利用基于最小L₁范数稀疏表示对奇异值分解结果进行强特征提取(Minimum L₁-norm Based Sparse Representation for Feature Extraction, L