Controllable defects implantation in MoS<Subscript>2</Subscript> grown by chemical vapor deposition for photoluminescence enhancement

Photoluminescence (PL) of transition metal dichalcogenides (TMDs) can be engineered by controlling the density of defects, which provide active sites for electron-hole recombination, either radiatively or non-radiatively. However, the implantation of defects by external stimulation, such as uniaxial tension and irradiation, tends to introduce local damages or structural non-homogeneity, which greatly degrades their luminescence properties and impede their applicability in constructing optoelectronic devices. In this paper, we present a strategy to introduce a controllable level of defects into the MoS₂ monolayers by adding a hydrogen flow during the chemical vapor deposition, without sacrificing their luminescence characteristics. The density of the defect is controlled directly by the concentration of hydrogen. For an appropriate hydrogen flux, the monolayer MoS₂ sheets have three times stronger PL emission at the excitonic transitions, compared with those samples with nearly perfect crystalline structure. The defect-bounded exciton transitions at lower energies arising in the defective samples and are maximized when the total PL is the strongest. However, the B exciton, exhibits a monotonic decline as the defect density increases. The Raman spectra of the defective MoS₂ reveal a redshift (blueshift) of the in-plane (out-of-plane) vibration modes as the hydrogen flux increases. All the evidence indicates that the generated defects are in the form of sulfur vacancies. This study renders the high-throughput synthesis of defective MoS₂ possible for catalysis or light emitting applications.

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Molecular dynamics simulation on flow behavior of nanofluids between flat plates under shear flow condition

Molecular dynamic model of nanofluid between flat plates under shear flow conditions was built. The nanofluid model consisted of 12 spherical copper nanoparticles with each particle diameter of 4 nm and argon atoms as base liquid. The Lennard–Jones (LJ) potential function was adopted to deal with the interactions between atoms. Thus, the motion states of nanoparticles during the process of flowing were obtained and the flow behaviors of nanofluid between flat plates at different moments could be analyzed. The simulation results showed that an absorption layer of argon atoms existed surrounding each nanoparticle and would accompany with the particle to move. The absorption layer contributed little to the flow of nanoparticles but much to the heat transferring in nanofluids. Another phenomenon observed during shear flowing process was that the nanoparticles would vibrate and rotate besides main flowing with liquid argon and these micro-motions could strengthen partial flowing in nanofluids.     

Security analysis of two recently proposed RFID authentication protocols

Radio frequency identification (RFID) systems suffer many security risks because they use an insecure wireless communication channel between tag and reader. In this paper, we analyze two recently proposed RFID authentication protocols. Both protocols are vulnerable to tag information leakage and untraceability attacks. For the attack on the first protocol, the adversary only needs to eavesdrop on the messages between reader and tag, and then perform an XOR operation. To attack the second protocol successfully, the adversary may execute a series of carefully designed challenges to determine the tag’s identification.     

基于ADSP-BF561的英文字符库设计

针对以ADSP-BF561芯片为核心的目标跟踪系统中显示目标运动及提示信息的需要,提出了基于ADSP-BF561的英文字符库的设计方案.该字符库中包括26个小写英文字符(a～z)、10个数字(0～9),以及“:”和空格共计38个符号.该字符库通过使用存储在ADSP-BF561的L2存储器上的数据类型为布尔型、大小为16...     

公交信号优先策略研究

本文介绍了公交优先策略的概念和分类,阐述了绿灯延长、绿灯提前、相位倒转、相位插入、公交通行专用相位等主动优先控制策略的基本原理,并对其进行了适应性和优缺点分析。     

Well-posedness, regularity and exact controllability of the SCOLE model

The SCOLE model is a coupled system consisting of a flexible beam (modelled as an Euler–Bernoulli equation) with one end clamped and the other end linked to a rigid body. Its inputs are the force and the torque acting on the rigid body. It is well-known that the SCOLE model is not exactly controllable with L ² input signals in the natural energy state space H ^c , because the control operator is bounded from the input space \mathbbC²{\mathbb{C}^2} to H ^c , and hence compact. We regard the velocity and the angular velocity of the rigid body as the output signals of this system. Using the theory of coupled linear systems (one infinite-dimensional and one finite-dimensional) developed by us recently in another paper, we show that the SCOLE model is well-posed, regular and exactly controllable in arbitrarily short time when using a certain smoother state space X ì H^c{\mathcal{X}\subset H^c}.     

基于MSP430的二线制高精度表头设计

针对传统的二线制表头在高温下测量精度差、温漂大的特点,提出了一种在高温下的高精度数显表头的设计方案。分别介绍了其软硬件的实现方法,即采用超低功耗微处理器MSP430F4250采集回路中的电流值,采用24位ADC转换器ADS1244进行模数转换,最后将经过运算的变送器输出信号值在LED数码管中加以显示。实测结果证明,该表头在高温下测量精度高、工作可靠、抗干扰性强、实用性强,势必会成为无源二线制仪表的发展方向。     

基于ARM9的分散式数据采集系统的研究

针对传统数据采集系统采集精度与数据处理能力的不足,结合当前广泛应用的嵌入式系统技术和总线技术,基于ARM9处理器S3C2440设计了一种分散式数据采集系统.底层数据采集系统采用了模块化的设计结构,各模块采用统一的总线把数据传送给主控器;最后系统利用ARM9强大的数据处理能力对所有数据进行分析、处理.实际试验证明,该系统数据处理速度快、控制精度高,可满足一般工业现场的要求.     

Adaptive pruning algorithm for least squares support vector machine classifier

As a new version of support vector machine (SVM), least squares SVM (LS-SVM) involves equality instead of inequality constraints and works with a least squares cost function. A well-known drawback in the LS-SVM applications is that the sparseness is lost. In this paper, we develop an adaptive pruning algorithm based on the bottom-to-top strategy, which can deal with this drawback. In the proposed algorithm, the incremental and decremental learning procedures are used alternately and a small support vector set, which can cover most of the information in the training set, can be formed adaptively. Using this set, one can construct the final classifier. In general, the number of the elements in the support vector set is much smaller than that in the training set and a sparse solution is obtained. In order to test the efficiency of the proposed algorithm, we apply it to eight UCI datasets and one benchmarking dataset. The experimental results show that the presented algorithm can obtain adaptively the sparse solutions with losing a little generalization performance for the classification problems with no-noises or noises, and its training speed is much faster than sequential minimal optimization algorithm (SMO) for the large-scale classification problems with no-noises.