熔化法YBaKCuO块材的制备和性能

成功地制备了K掺杂的MTG-YBKCO单畴块材, 在70K时,Jc随H单调下降.但在55K时,Jc-H曲线在(2～4)T范围内呈现了第二峰即峰值效应,使能在较宽磁场中仍保持高Jc值.     

Theoretical study of thermoelectric properties of MoS2Theoretical study of thermoelectric properties of MoS2Theoretical study of thermoelectric properties of MoS2

We systematically studied the thermoelectric properties of MoS2 with doping based on the Boltzmann transport theory and first-principles calculations. We obtained an optimal doping region （around 1019 cm-3） for thermoelectric properties along in-plane and cross-plane directions. MoS2 in the optimal doping region has a vanishingly small anisotropy of ther- mopower possibly due to the decoupling of in-plane and cross-plane conduction channels, but big anisotropies of electrical conductivity cr and electronic thermal conductivity ke arising from the anisotropic electronic scattering time. The ~ is comparable to the lattice counterpart k1 in the plane, while tq dominates over tee across the plane, The figure of merit ZT can reach 0.1 at around 700 K with in-plane direction preferred by doping.     

移动机器人履行系统配置优化研究——基于闭排队网络理论

本文对移动机器人履行系统中货架调度任务的履行过程进行分析,根据机器人在货架装载、搬运、拣选、卸载四个过程的作业特点建立闭排队网络模型。采用近似平均值分析算法求解,实现系统绩效的迅速评估。通过与仿真计算实验的对比证明,模型对系统绩效的评估误差不超过5%。利用闭排队网络模型评估拣选台、机器人利用率和调度任务履行能力,实现对系统设施配置的讨论和优化。研究表明,拣选台均匀分布于仓库较长的两侧能提高系统履行绩效;系统存在最优机器人投放数量使系统整体利用率较高。     

基于博弈论的移动机会网络节点的自私行为的分析与研究

移动机会网络具有多跳性,其中的数据传输需要借助中介节点的转发。信息共享中也存在节点的数据传输。但是由于资源的有限性易造成节点自私行为的产生,文章针对自私节点,提出了一种基于博弈论的移动机会网络自私节点的检测算法,并提供一定有效的惩戒手段,鼓励自私节点传递数据,在一定程度上解决了节点的自私行为,更好地维护网络环境。     

Unconventional lattice dynamics in few-layer h-BN and indium iodide crystals

Unusual quadratic dispersion of flexural vibrational mode and red-shift of Raman shift of in-plane mode with increasing layer-number are quite common and interesting in low-dimensional materials, but their physical origins still remain open questions. Combining ab initio density functional theory calculations with the empirical force-constant model, we study the lattice dynamics of two typical two-dimensional(2 D) systems, few-layer h-BN and indium iodide(In I). We found that the unusual quadratic dispersion of flexural mode frequency on wave vector may be comprehended based on the competition between atomic interactions of different neighbors. Long-range interaction plays an essential role in determining the dynamic stability of the 2 D systems. The frequency red-shift of in-plane Raman-active mode from monolayer to bulk arises mainly from the reduced long-range interaction due to the increasing screening effect.     

多电平积累技术的研究

研究了多电平积累技术在不同Swerling模型下的性能及其实现方法,并且对比了不积累、双回路积累和多电平积累在不同Swerling模型下的性能。仿真结果表明,多电平积累技术的性能接近于双回路积累,但从工程实现角度考虑,多电平积累技术实现复杂度要远远低于双回路积累。     

关于智能公交定位报时查询系统的论述

对于公交车的具体位置信息,我们可以获得,但对于公交车何时到达指定地点、到达下一站的大概时间等信息,我们不一定可以轻松地获得,而现今对于等公交车的人们来讲,遇到的一个问题是在等公交车的时候不知道公交车大概何时到达,也不知道公交车大概何时到达自己所要去的目的地等,这样,对与乘坐公交车的人们来讲,他们的出行将会显得不便,文章就实现人们可以通过自己的手机客户端来获取公交车的预计到达时间、下一站位置等信息进行讨论。     

基于程序切片和BiGRU的代码搜索

代码复用可以有效缩短软件开发的时间,而代码搜索是代码复用的主要途径.提出了一种基于程序切片和BiGRU的代码搜索方法,该方法通过构建源代码的程序依赖图,以程序依赖图中出度最大的节点作为兴趣点构建前向切片.将程序切片与源代码的其他相关特征一起构成代码特征.把代码特征和代码的功能描述通过嵌入模块输入到BiGRU网络中,结合注意力机制训练BiGRU模型.用户输入功能查询语句,模型返回向量值最接近的代码.为了验证该模型的可行性和有效性,从开源代码库下载了Java项目,构建了数据集并进行实验.实验结果表明,提出的基于程序切片和BiGRU的方法在代码搜索的准确率和相关性排名等方面都有所改进.     

Stacking stability of MoS_2 bilayer: An ab initio study

The study of the stacking stability of bilayer MoS2 is essential since a bilayer has exhibited advantages over single layer MoS2 in many aspects for nanoelectronic applications. We explored the relative stability, optimal sliding path between different stacking orders of bilayer MoS2, and （especially） the effect of inter-layer stress, by combining first-principles density functional total energy calculations and the climbing-image nudge-elastic-band （CI-NEB） method. Among five typical stacking orders, which can be categorized into two kinds （I： AA＇, AB and II： AA＇, AB＇, A＇B）, we found that stacking orders with Mo and S superposing from both layers, such as AA＇ and AB, is more stable than the others. With smaller computational efforts than potential energy profile searching, we can study the effect of inter-layer stress on the stacking stability. Under isobaric condition, the sliding barrier increases by a few eV/（uc.GPa） from AA＇ to ABt, compared to 0.1 eV/（uc.GPa） from AB to [AB]. Moreover, we found that interlayer compressive stress can help enhance the transport properties of AA＇. This study can help understand why inter-layer stress by dielectric gating materials can be an effective means to improving MoS2 on nanoelectronic applications.     

Fundamental band gap and alignment of two-dimensional semiconductors explored by machine learning

Two-dimensional(2D)semiconductors isoelectronic to phosphorene have been drawing much attention recently due to their promising applications for next-generation(opt)electronics.This family of 2D materials contains more than 400members,including(a)elemental group-V materials,(b)binary III–VII and IV–VI compounds,(c)ternary III–VI–VII and IV–V–VII compounds,making materials design with targeted functionality unprecedentedly rich and extremely challenging.To shed light on rational functionality design with this family of materials,we systemically explore their fundamental band gaps and alignments using hybrid density functional theory(DFT)in combination with machine learning.First,calculations are performed using both the Perdew–Burke–Ernzerhof exchange–correlation functional within the generalgradient-density approximation(GGA-PBE)and Heyd–Scuseria–Ernzerhof hybrid functional(HSE)as a reference.We find this family of materials share similar crystalline structures,but possess largely distributed band-gap values ranging approximately from 0 eV to 8 eV.Then,we apply machine learning methods,including linear regression(LR),random forest regression(RFR),and support vector machine regression(SVR),to build models for the prediction of electronic properties.Among these models,SVR is found to have the best performance,yielding the root mean square error(RMSE)less than 0.15 eV for the predicted band gaps,valence-band maximums(VBMs),and conduction-band minimums(CBMs)when both PBE results and elemental information are used as features.Thus,we demonstrate that the machine learning models are universally suitable for screening 2D isoelectronic systems with targeted functionality,and especially valuable for the design of alloys and heterogeneous systems.