InAs基范德华异质结界面电荷转移特性第一性原理计算的研究进展

由低维InAs材料和其他二维层状材料堆叠而成的垂直范德华异质结构在纳米电子、光电子和量子信息等新兴领域中应用广泛。探索跨结界面的电荷转移机制对于全面理解该类器件的非凡特性至关重要。第一性原理计算在揭示界面电荷转移特性与各种能量稳定型InAs基范德华异质结的电、光、磁等原理物理特性和器件性能变化之间的内在关系方面发挥着不可比拟的作用。文中梳理、总结和探讨了近年来InAs基范德华异质结间界面电荷转移特性的理论研究工作与潜在的功能应用,提出在理论方法和计算精度方面大力发展第一性原理计算的几个途径,为更好地开展InAs基范德华异质结的基础科学研究和应用器件设计提供可借鉴的量化研究基础。     

Fine-Tuning Alkyl Chains on Quinoxaline Nonfullerene Acceptors Enables High-Efficiency Ternary Organic Solar Cells with Optimizing Molecular Stacking and Reducing Energy Loss

Material design of guest acceptor is always a big challenge for improving the efficiency of ternary organic solar cells (OSCs). Here, a pair of isomeric nonfullerene acceptors based on quinoxaline core, Qx–p-C₇H₈O and Qx–m-C₇H₈O, is designed and synthesized. By moving the alkoxy chain attached on side phenyl from meta-position to para-position, both π–π stacking distance and crystallinity are enhanced simultaneously. They obtain the uplifted lowest unoccupied molecular orbital level. Compared to Qx–m-C₇H₈O, Qx–p-C₇H₈O exhibits wider absorption spectrum and higher extinction coefficient. Using D18-Cl:N3 as host materials, the addition of guest acceptor Qx–p-C₇H₈O significantly improves the power conversion efficiency (PCE) from 17.61% to 18.49% because of higher open-circuit voltage (0.875 V) and short-circuit current density (27.85 mA cm⁻²). This can be attributed to the faster exciton dissociation, more balanced carrier mobility, fine fiber morphology, and lower energy loss in the ternary devices. However, Qx–m-C₇H₈O-based ternary device achieves relatively low PCE of 17.17% because this device shows extremely low electron mobility. The results indicate that molecular stacking, film morphology, etc., can be effectively modulated by fine-tuning the side chains of guest materials, which may be an effective design rule for further improving the PCE of OSCs.     

In Situ Deformation Topology of COFs with Shortened Channels and High Redox Properties for Li–S Batteries

Covalent organic frameworks (COFs) with various topologies are typically synthesized by selecting and designing connecting units with rich shapes. However, this process is time-consuming and labour-intensive. Besides, the tight stacking of COFs layers greatly restrict their structural advantages. It is crucial to effectively exploit the high porosity and active sites of COFs by topological design. Herein, for the first time, inducing in situ topological changes in sub-chemometric COFs by adding graphene oxide (GO) without replacing the monomer, is proposed. Surprisingly, GO can slow down the intermolecular stacking and induce rearrangement of COFs nanosheets. The channels of D- [4+3] COFs are significantly altered while the stacking of periodically expanded framework is weakened. This not only maximizes the exposure of pore area and polar groups, but also shortens the channels and increases the redox activity, which enables high loading while enhancing host-guest interactions. This topological transformation to exhibit the structural features of COFs for efficient application is an innovative molecular design strategy.     

Creating Atomic Ordering in Electrocatalysis

Catalysis always proceeds in a chaotic fashion. Therefore, identifying the working principles of heterogeneous catalysts is a challenging task. Creating atomic order in heterogeneous catalysts simplifies this task and also offers new opportunities for rationally designing active sites to manipulate catalytic performance. The recent rapid advances in heterogeneous electrocatalysis have led to exciting progress in the construction of atomically ordered materials. Here, the latest progress in electrocatalysts with the periodic atomic arrangement, including intermetallic compounds with long-range order and metal atom-array catalysts with short-range order is summarized. The synthesis principles and the intriguing physical and chemical properties of these electrocatalysts are discussed. Furthermore, the compelling prospects of atomically ordered catalysts in the frontier of catalyst research are outlined.     

BS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking Classifier

For a long time, legal entities have developed and used crime prediction methodologies. The techniques are frequently updated based on crime evaluations and responses from scientific communities. There is a need to develop type-based crime prediction methodologies that can be used to address issues at the subgroup level. Child maltreatment is not adequately addressed because children are voiceless. As a result, the possibility of developing a model for predicting child abuse was investigated in this study. Various exploratory analysis methods were used to examine the city of Chicago’s child abuse events. The data set was balanced using the Borderline-SMOTE technique, and then a stacking classifier was employed to ensemble multiple algorithms to predict various types of child abuse. The proposed approach successfully predicted crime types with 93% of accuracy, precision, recall, and F1-Score. The AUC value of the same was 0.989. However, when compared to the Extra Trees model (17.55), which is the second best, the proposed model’s execution time was significantly longer (476.63). We discovered that Machine Learning methods effectively evaluate the demographic and spatial-temporal characteristics of the crimes and predict the occurrences of various subtypes of child abuse. The results indicated that the proposed Borderline-SMOTE enabled Stacking Classifier model (BS-SC Model) would be effective in the real-time child abuse prediction and prevention process.     

An Optimal Solution for Test Case Generation Using ROBDD Graph and PSO Algorithm

Software testing is one of the most important techniques to examine the behavior of the software products to assure their quality. An effective and efficient testing approach must balance two important but conflicting requirements. One of them is the accuracy that needs a large number of test cases for testing, and the second one is reducing the time and cost, which requires a few test cases. Even for small software, the number of possible test cases is typically very large, and exhaustive testing is impractical. Hence, selecting appropriate test suite is necessary. Cause–effect graph testing is a common black‐box testing technique, which is equivalently representing Boolean relations between input parameters. However, the other traditional black‐box strategies cannot identify the relations that it may result in loss of some of the important test cases. Although the cause–effect graph is regarded very promising in specification testing, it is observed that most of the proposed approaches using the graph are complex or generate impossible and a large number of test cases. This observation has motivated our research to propose an efficient strategy to generate minimal test suite that simultaneously achieves high coverage of input parameters. To do so, at first, we identify major effects from the cause–effect graph using reduced ordered binary decision diagram (ROBDD). ROBDD makes the related Boolean expression of the graph concise and obtains a unique representation of the expression. Using the ROBDD, it is possible to reduce the size of the generated test suite and to perform testing faster. After that, our proposed method utilizes particle swarm optimization (PSO) algorithm to select the optimal test suite, which covers all pairwise combinations of input parameters. The experimental results show that our approach simultaneously achieves high efficacy and reduces cost of testing by selecting appropriate test cases, respectively, to both test size and coverage size. Also, it outperforms some existing state‐of‐the‐art strategies in the black‐box testing. Copyright © 2015 John Wiley & Sons, Ltd.     

形变温度对Fe-20Mn-3Cu-1.3C TWIP钢拉伸变形行为的影响EI北大核心CSCD

运用温控拉伸实验,分析了在-100~200℃范围内变形时形变温度对Fe-20Mn-3Cu-1.3C钢力学性能和形变机理的影响。观察分析了拉伸试样的显微组织,并利用热力学经典模型,估算了温度对孪晶诱发塑性(TWIP)钢层错能的影响。结果表明:随着形变温度的升高,TWIP钢的层错能显著增加,基体中形变孪晶的体积分数逐渐减少,抗拉强度和屈服强度呈下降趋势,而伸长率先升高后降低,塑性变形机制也由孪生为主逐渐转变为以滑移为主。层错能的拟合公式为γSFE=26.73+9.38×10^(-2) T+4.22×10^(-4 )T2-4.47×10^(-7) T^3,与滑移相比,孪生可获得更高的应变硬化率,从而使TWIP钢获得高强度和高塑性。     

基于有序介孔碳/PDDA固定化漆酶的邻苯二酚传感器性能研究

采用有机交联水性环氧树脂为碳源,以SBA-15为模板,制备了有序介孔碳(OMC),并对其电化学性能进行研究。透射电镜结果表明其具有典型的二维有序六角介孔结构,孔径大约为3nm。电化学测试结果表明OMC/Lac/Au电极对邻苯二酚具有很好的电催化氧化活性。将OMC应用于构建漆酶生物传感器,结果表明,传感器对邻苯二酚的线性检测范围为0.67~8.59μmol/L,灵敏度为0.349A/(mol/L),检测限为0.117μmol/L。     

关于镁合金中长周期有序结构的研究综述

系统地介绍了6H、10H、14H、18R、24R型LPSO结构的原子堆垛和RE、Zn的占位特点,探讨了LPSO结构的形成条件和形成机制,分析了含LPSO结构相合金的组织演变过程并概述了组织演变方面最新的研究成果,总结了含LPSO结构相镁合金的室温和高温性能的研究现状,最后对该类合金未来的研究方向进行了展望。     

不同缓冲材料的堆码包装振动特性分析

目的 研究物流运输中采用不同缓冲材料的堆码包装件的振动特性。方法 以缓冲材料聚乙烯泡沫(EPE)和聚苯乙烯泡沫(EPS)为研究对象,采用三维建模软件SoildWorks和有限元仿真软件Workbench建立有限元模型进行模态与谐响应分析,结合扫频振动试验和随机振动试验对各层堆码件的振动响应特性进行分析。结果 2类包装件共振频率处的第一激励能量都大于第二激励能量,振动幅值随层数增加而升高。EPE包装件第一和第二共振频率的激励能量占比分别为35.7%和3%,EPS包装件第一和第二共振频率的激励能量占比分别为26.8%和16.8%。EPE包装件共振区域主要分布于15～40 Hz,而EPS包装件共振频率区域分布于15～40 Hz和60～80 Hz。三层堆码件的中上层包装件受第一共振频率控制,EPS材料的底层包装件受多个共振频率影响,EPE材料的底层包装件受到第二共振频率控制。结论 经过循环载荷作用后的EPE的吸振缓冲性能优于EPS的。通过试验与有限元仿真数据绘制了相应的防振性能曲线,同时验证了有限元仿真的可靠性。这为堆码产品选择不同缓冲材料组合提供了的理论指导。