Ultrafast laser spectroscopy of half -metallic chromium dioxide

This thesis presents ultrafast laser pump-probe differential transmission experiments on epitaxial CrO2 (110). The experiments were conducted at the wavelengths of 600 nm, 800 nm and 1200 nm, corresponding to the transition energies of 2 eV, 1.5 eV and 1 eV respectively. The wavelength dependent results, comparing with linear optical absorption, revealed the electronic structure of the material. The experimental results also showed polarization dependence of the probe beams. This is attributed to the electronic orbital anisotropy.;Temperature dependence was observed in the pump-probe experiments. The ultrafast transmission data show similar temperature dependence as ultrafast MOKE (Magneto-Optical Kerr Effect) data. A critical change of transient transmission was observed at the Curie temperature of 386 K. Spin decay processes are discussed based on these temperature dependent time resolved data.;Ultrafast MOKE experiments are also presented. Oscillations of the time resolved MOKE signal corresponding to the ferromagnetic resonance were observed. The magnetic anisotropies of the CrO2 thin film were studied by analyzing these oscillations. A computer program was developed for data analysis.;A general discussion of the relation between magnetic properties and the electronic properties of the material is delivered

Modeling Hydrochemical and Vegetation Responses of High-elevation Forested Watersheds to Future Climate and Atmospheric Deposition Changes in the Southeastern U.S.

Changes in climate and atmospheric acidic deposition alter biogeochemical cycles in forested ecosystems. I investigated the responses of vegetation, soil, and hydro-related processes to changes in climate and acidic deposition at five high-elevation forests in the southeastern U.S. using a biogeochemical model - PnET-BGC model. I focused on change-points and thresholds concepts that were less studied in forest ecosystems as well as seasonal variability of responses and extreme events. I applied principal component analysis (PCA) to reduce the dimensionality of data. I developed a Bayesian multi-level model to derive key biogeochemical variables response to temperature and precipitation (local) and latitude and elevation (regional) with uncertainty accounted for. The first principal components (PC1s) explain 50-60% and 40-50% of the variance in the 17 main biogeochemical variables simulated from the model at the Coweeta Basin (CWT) and Shenandoah National Park (SNP) respectively. PC1s at CWT are highly correlated to transpiration, gross and net primary production (GPP and NPP), soil base saturation, soil Al:Ca ratio, and stream chemistry (Ca2+ and K+), while PC1s at SNP are highly correlated to NPP, transpiration, and stream base cations. The key biogeochemical processes show strong seasonality in their response to future climate change. Higher latitudinal sites have earlier but fewer change-points than lower latitudes from 1931 to 2100. Vegetation at higher-elevation forests appears more sensitive to climate change, while soil and streams are more sensitive at the lower-elevation forests. Flooding and drought will become more frequent, and soil and stream will become more acidic under climate change. Regional analysis demonstrates that temperature tends to drive key biogeochemical variables more significantly than precipitation. Winter shows the least sensitivity to climate change in NPP, transpiration, and acid neutralization capacity 3 (ANC) at all five sites. In addition, latitude and elevation influence the sensitivity of these biogeochemical variables to temperature and precipitation at some degree. Change in acidic deposition will likely shift the biogeochemical processes response to climate change differently, depending on biogeochemical processes, season, and the direction and magnitude of change in acidic deposition. The effect is minimal for NPP, and summer and winter will have the largest shifts

An End-to-End Vehicle Trajcetory Prediction Framework

Anticipating the motion of neighboring vehicles is crucial for autonomous driving, especially on congested highways where even slight motion variations can result in catastrophic collisions. An accurate prediction of a future trajectory does not just rely on the previous trajectory, but also, more importantly, a simulation of the complex interactions between other vehicles nearby. Most state-of-the-art networks built to tackle the problem assume readily available past trajectory points, hence lacking a full end-to-end pipeline with direct video-to-output mechanism. In this article, we thus propose a novel end-to-end architecture that takes raw video inputs and outputs future trajectory predictions. It first extracts and tracks the 3D location of the nearby vehicles via multi-head attention-based regression networks as well as non-linear optimization. This provides the past trajectory points which then feeds into the trajectory prediction algorithm consisting of an attention-based LSTM encoder-decoder architecture, which allows it to model the complicated interdependence between the vehicles and make an accurate prediction of the future trajectory points of the surrounding vehicles. The proposed model is evaluated on the large-scale BLVD dataset, and has also been implemented on CARLA. The experimental results demonstrate that our approach outperforms various state-of-the-art models.Comment: 6 pages, 5 figure

Scheduling of a parcel delivery system consisting of an aerial drone interacting with public transportation vehicles

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This paper proposes a novel parcel delivery system which consists of a drone and public transportation vehicles such as trains, trams, etc. This system involves two delivery schemes: drone-direct scheme referring to delivering to a customer by a drone directly and drone–vehicle collaborating scheme referring to delivering a customer based on the collaboration of a drone and public transportation vehicles. The fundamental characteristics including the delivery time, energy consumption and battery recharging are modelled, based on which a time-dependent scheduling problem for a single drone is formulated. It is shown to be NP-complete and a dynamic programming-based exact algorithm is presented. Since its computational complexity is exponential with respect to the number of customers, a sub-optimal algorithm is further developed. This algorithm accounts the time for delivery and recharging, and it first schedules the customer which leads to the earliest return. Its computational complexity is also discussed. Moreover, extensive computer simulations are conducted to demonstrate the scheduling performance of the proposed algorithms and the impacts of several key system parameters are investigated

Electric-field-induced strong enhancement of electroluminescence in multilayer molybdenum disulfide.

The layered transition metal dichalcogenides have attracted considerable interest for their unique electronic and optical properties. While the monolayer MoS2 exhibits a direct bandgap, the multilayer MoS2 is an indirect bandgap semiconductor and generally optically inactive. Here we report electric-field-induced strong electroluminescence in multilayer MoS2. We show that GaN-Al2O3-MoS2 and GaN-Al2O3-MoS2-Al2O3-graphene vertical heterojunctions can be created with excellent rectification behaviour. Electroluminescence studies demonstrate prominent direct bandgap excitonic emission in multilayer MoS2 over the entire vertical junction area. Importantly, the electroluminescence efficiency observed in multilayer MoS2 is comparable to or higher than that in monolayers. This strong electroluminescence can be attributed to electric-field-induced carrier redistribution from the lowest energy points (indirect bandgap) to higher energy points (direct bandgap) in k-space. The electric-field-induced electroluminescence is general for other layered materials including WSe2 and can open up a new pathway towards transition metal dichalcogenide-based optoelectronic devices

On the Nonlinear Fractional Differential Equations with Caputo Sequential Fractional Derivative

The purpose of this paper is to investigate the existence of solutions to the following initial value problem for nonlinear fractional differential equation involving Caputo sequential fractional derivative Dc0α2Dc0α1yxp-2Dc0α1yx=fx,yx, x>0, y(0)=b0, Dc0α1y(0)=b1, where Dc0α1, Dc0α2 are Caputo fractional derivatives, 0<α1, α2≤1, p>1, and b0,b1∈R. Local existence of solutions is established by employing Schauder fixed point theorem. Then a growth condition imposed to f guarantees not only the global existence of solutions on the interval [0,+∞), but also the fact that the intervals of existence of solutions with any fixed initial value can be extended to [0,+∞). Three illustrative examples are also presented. Existence results for initial value problems of ordinary differential equations with p-Laplacian on the half-axis follow as a special case of our results

ADRC Method for Noncascaded Integral System Based on the Total Derivative of Composite Functions of Several Variables

The standard ADRC controller usually selects the canonical plant in the form of cascaded integrators. However, the condition variables of practical system do not necessarily have the cascaded integral relationship. Therefore, this paper proposes a method of total derivative of composite functions of several variables and a structure, which can convert the state space system of noncascaded integral form into the cascaded integral form. In this way, the converted system can be directly controlled with ADRC. Meanwhile, the control of Chen chaotic system is discussed in detail to show the conversion and the controller design. The control performances under different levels of complication and different strengths of disturbance are comparably researched. The converted system achieves significantly better control effects under ADRC than that of the PID. This converting method solves the control problem of some noncascaded integral systems in both theory and application and greatly expands the application scope of the standard ADRC method

Impact of Climate Change on Hydrochemical Processes at Two High-Elevation Forested Watersheds in the Southern Appalachians, United States

Climate change increasingly affects primary productivity and biogeochemical cycles in forest ecosystems at local and global scales. To predict change in vegetation, soil, and hydrologic processes, we applied an integrated biogeochemical model Photosynthesis-EvapoTranspration and BioGeoChemistry (PnET-BGC) to two high-elevation forested watersheds in the southern Appalachians in the US under representative (or radiative) concentration pathway (RCP)4.5 and RCP8.5 scenarios. We investigated seasonal variability of the changes from current (1986–2015) to future climate scenarios (2071–2100) for important biogeochemical processes/states; identified change points for biogeochemical variables from 1931 to 2100 that indicate potential regime shifts; and compared the climate change impacts of a lower-elevation watershed (WS18) with a higher-elevation watershed (WS27) at the Coweeta Hydrologic Laboratory, North Carolina, United States. We find that gross primary productivity (GPP), net primary productivity (NPP), transpiration, nitrogen mineralization, and streamflow are projected to increase, while soil base saturation, and base cation concentration and ANC of streamwater are projected to decrease at the annual scale but with strong seasonal variability under a changing climate, showing the general trend of acidification of soil and streamwater despite an increase in primary productivity. The predicted changes show distinct contrasts between lower and higher elevations. Climate change is predicted to have larger impact on soil processes at the lower elevation watershed and on vegetation processes at the higher elevation watershed. We also detect five change points of the first principal component of 17 key biogeochemical variables simulated with PnET-BGC between 1931 and 2100, with the last change point projected to occur 20 years earlier under RCP8.5 (2059 at WS18 and WS27) than under RCP4.5 (2079 at WS18 and 2074 at WS27) at both watersheds. The change points occurred earlier at WS18 than at WS27 in the 1980s and 2010s but in the future are projected to occur earlier in WS27 (2074) than WS18 (2079) under RCP4.5, implying that changes in biogeochemical cycles in vegetation, soil, and streams may be accelerating at higher-elevation WS27