Electronic and Structural Properties of C36_{36} Molecule

The extended SSH model and Bogoliubov-de Gennes(BdeG) formalism are applied to investigate the electronic properties and stable lattice configurations of C$_{36}$. We focus the problem on the molecule's unusual $D_{6h}$ symmetry. The electronic part of the Hamiltonian without Coulomb interaction is solved analytically. We find that the gap between HOMO and LUMO is small due to the long distance hopping between the 2nd and 5th layers. The charge densities of HOMO and LUMO are mainly distributed in the two layers, that causes a large splitting between the spin triplet and singlet excitons. The differences of bond lengths, angles and charge densities among the molecule and polarons are discussed.Comment: 15 pages, 4 figures, 4 Table

Methodology for standard cell compliance and detailed placement for triple patterning lithography

As the feature size of semiconductor process further scales to sub-16nm technology node, triple patterning lithography (TPL) has been regarded one of the most promising lithography candidates. M1 and contact layers, which are usually deployed within standard cells, are most critical and complex parts for modern digital designs. Traditional design flow that ignores TPL in early stages may limit the potential to resolve all the TPL conflicts. In this paper, we propose a coherent framework, including standard cell compliance and detailed placement to enable TPL friendly design. Considering TPL constraints during early design stages, such as standard cell compliance, improves the layout decomposability. With the pre-coloring solutions of standard cells, we present a TPL aware detailed placement, where the layout decomposition and placement can be resolved simultaneously. Our experimental results show that, with negligible impact on critical path delay, our framework can resolve the conflicts much more easily, compared with the traditional physical design flow and followed layout decomposition

Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms

Due to the unmanned aerial vehicle remote sensing images (UAVRSI) within rich texture details of ground objects and obvious phenomenon, the same objects with different spectra, it is difficult to effectively acquire the edge information using traditional edge detection operator. To solve this problem, an edge detection method of UAVRSI by combining Zernike moments with clustering algorithms is proposed in this study. To begin with, two typical clustering algorithms, namely, fuzzy c-means (FCM) and K-means algorithms, are used to cluster the original remote sensing images so as to form homogeneous regions in ground objects. Then, Zernike moments are applied to carry out edge detection on the remote sensing images clustered. Finally, visual comparison and sensitivity methods are adopted to evaluate the accuracy of the edge information detected. Afterwards, two groups of experimental data are selected to verify the proposed method. Results show that the proposed method effectively improves the accuracy of edge information extracted from remote sensing images

Experimental Evidence of Ferroelectric Negative Capacitance in Nanoscale Heterostructures

We report a proof-of-concept demonstration of negative capacitance effect in a nanoscale ferroelectric-dielectric heterostructure. In a bilayer of ferroelectric, Pb(Zr0.2Ti0.8)O3 and dielectric, SrTiO3, the composite capacitance was observed to be larger than the constituent SrTiO3 capacitance, indicating an effective negative capacitance of the constituent Pb(Zr0.2Ti0.8)O3 layer. Temperature is shown to be an effective tuning parameter for the ferroelectric negative capacitance and the degree of capacitance enhancement in the heterostructure. Landau's mean field theory based calculations show qualitative agreement with observed effects. This work underpins the possibility that by replacing gate oxides by ferroelectrics in MOSFETs, the sub threshold slope can be lowered below the classical limit (60 mV/decade)

Large area growth and electrical properties of p-type WSe2 atomic layers.

Transition metal dichacogenides represent a unique class of two-dimensional layered materials that can be exfoliated into single or few atomic layers. Tungsten diselenide (WSe(2)) is one typical example with p-type semiconductor characteristics. Bulk WSe(2) has an indirect band gap (∼ 1.2 eV), which transits into a direct band gap (∼ 1.65 eV) in monolayers. Monolayer WSe(2), therefore, is of considerable interest as a new electronic material for functional electronics and optoelectronics. However, the controllable synthesis of large-area WSe(2) atomic layers remains a challenge. The studies on WSe(2) are largely limited by relatively small lateral size of exfoliated flakes and poor yield, which has significantly restricted the large-scale applications of the WSe(2) atomic layers. Here, we report a systematic study of chemical vapor deposition approach for large area growth of atomically thin WSe(2) film with the lateral dimensions up to ∼ 1 cm(2). Microphotoluminescence mapping indicates distinct layer dependent efficiency. The monolayer area exhibits much stronger light emission than bilayer or multilayers, consistent with the expected transition to direct band gap in the monolayer limit. The transmission electron microscopy studies demonstrate excellent crystalline quality of the atomically thin WSe(2). Electrical transport studies further show that the p-type WSe(2) field-effect transistors exhibit excellent electronic characteristics with effective hole carrier mobility up to 100 cm(2) V(-1) s(-1) for monolayer and up to 350 cm(2) V(-1) s(-1) for few-layer materials at room temperature, comparable or well above that of previously reported mobility values for the synthetic WSe(2) and comparable to the best exfoliated materials

Bridge structure deformation prediction based on GNSS data using Kalman-ARIMA-GARCH model

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing technolog

Engineering Oxygen Vacancy-Rich CeOx overcoating Onto Ni/Al2O3 by Atomic Layer Deposition for Bi-Reforming of Methane

Atomic Layer Deposition (ALD) Was Applied to Develop CeOx-Overcoated Ni/Al2O3 Catalyst for Bi-Reforming of Methane (BRM), as the Combination of Dry Reforming of Methane (DRM) and Steam Reforming of Methane (SRM). Non-Stoichiometric CeOx Thin Films Were Successfully Deposited on Ni/Al2O3 Particles by ALD, Which Constructed a Beneficial Ni-CeOx Interface and Modified the Catalyst Property. Ascribed to the Unique ALD Growth Mode, a High Amount of Ce(III) and Oxygen Vacancies Existed in the ALD-Deposited CeOx overcoating. a Reduction Process Before the BRM Reaction Contributed to the Further Reduction of Ce(IV) to Ce(III), Resulting in More Oxygen Vacancies. the Oxygen Vacancies at the Ni-CeOx Interface Enabled a High Rate of CO2 Activation and Enabled the Balance between the Activation of CO2 and H2O for BRM. Due to its Oxygen Vacancies as Activation Sites for CO2 and H2O, CeOx ALD overcoating Significantly Improved the Activity of Ni/Al2O3 Catalyst and Achieved a Better Control in the H2/CO Ratio with a Suitable Ratio of H2O/CO2/CH4 Feed. CeOx overcoatings Enhanced the Reducibility of Ni(II) Sites and Assisted in Preventing Ni from Oxidation during the BRM Reaction. Less Carbon Deposition Was Achieved by the Ni/Al2O3 Catalyst with CeOx overcoating as Ascribed to its Better Reactant Activation Capacity