Stoichiometry control and automated growth of alkali antimonide photocathode films by molecular beam deposition
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photocathodes, stoichiometry, thin film growth↗
SEARCH · Engineering Papers
Results for “controlled”
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Continuously tunable uniaxial strain control of van der Waals heterostructure devices
Uniaxial strain has been widely used as a powerful tool for investigating and controlling the properties of quantum materials. However, existing strain techniques have so far mostly been limited to use with bulk crystals. Although recent progress has been made in extending the application of strain to two-dimensional van der Waals (vdW) heterostructures, these techniques have been limited to optical characterization and extremely simple electrical device geometries. Here, we report a piezoelectric-based in situ uniaxial strain technique enabling simultaneous electrical transport and optical spectroscopy characterization of dual-gated vdW heterostructure devices. Critically, our technique remains compatible with vdW heterostructure devices of arbitrary complexity fabricated on conventional silicon/silicon dioxide wafer substrates. We demonstrate a large and continuously tunable strain of up to –0.15% at millikelvin temperatures, with larger strain values also likely achievable. We quantify the strain transmission from the silicon wafer to the vdW heterostructure, and further demonstrate the ability of strain to modify the electronic properties of twisted bilayer graphene. Our technique provides a highly versatile new method for exploring the effect of uniaxial strain on both the electrical and optical properties of vdW heterostructures and can be easily extended to include additional characterization techniques.
Electrical properties and parameters↗
Ensemble-based uncertainty quantification for coordination and control of thermostatically controlled loads
This paper presents a general uncertainty quantification (UQ) framework that provides a systematic analysis of the uncertainty involved in the modeling of a control system, and helps to improve the performance of a control strategy.
ensemble-based method↗
Structural and electrochemical investigation of crystallite size controlled zinc ferrite (ZnFe2O4)
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99 GENERAL AND MISCELLANEOUS↗
Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii
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Gargouri, Mahmoud↗
Voltage-Controlled Sensitivity of the Spin Seebeck Effect in Pt/Y 3 Fe 5 O 12 /MgO/(PbMg 1/3 Nb 2/3 O 3 ) 0.7 (PbTiO 3 ) 0.3 Multiferroic Heterostructures
The characteristics of pure spin current from the longitudinal spin Seebeck effect are investigated at room temperature in Pt / Y 3 Fe 5 O 12 deposited on the ( Pb Mg 1 / 3 Nb 2 / 3 O 3 ) 0.7 ( Pb Ti O 3 ) 0.3 substrate, through which electrostrain can be controllably applied. The applied voltage enables the modification of magnetic anisotropy in the magnetic insulating Y 3 Fe 5 O 12 layer, and thus the sensitivity of the spin Seebeck effect at small magnetic fields, without suppressing the spin Seebeck effect and the inverse spin Hall effect. This is due to the robust intrinsic physical parameters in Pt / Y 3 Fe 5 O 12 . In conclusion, our results pave the way for the application of voltage-controlled pure spin-current devices.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Predictive Control over Charge Density in the Two-Dimensional Electron Gas at the Polar-Nonpolar NdTiO 3 / SrTiO 3 Interface
Through systematic control of the Nd concentration, we show that the carrier density of the twodimensional electron gas (2DEG) in SrTiO3=NdTiO3=SrTiO3 ð001Þ can be modulated over a wide range. We also demonstrate that the NdTiO3 in heterojunctions without a SrTiO3 cap is degraded by oxygen absorption from air, resulting in the immobilization of donor electrons that could otherwise contribute to the 2DEG. This system is, thus, an ideal model to understand and control the insulator-to-metal transition in a 2DEG based on both environmental conditions and film-growth processing parameters.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Helicity-Selective Enhancement and Polarization Control of Attosecond High Harmonic Waveforms Driven by Bichromatic Circularly Polarized Laser Fields
High harmonics driven by two-color counter-rotating circularly-polarized laser fields are a unique source of bright, circularly-polarized, extreme ultraviolet and soft x-ray beams, where the individual harmonics themselves are completely circularly polarized. Here, we demonstrate the ability to preferentially select either the right or left circularly polarized harmonics simply by adjusting the relative intensity ratio of the bichromatic circularly polarized driving laser field. In the frequency domain, this significantly enhances the harmonic orders that rotate in the same direction as the higher intensity driving laser. In the time domain, this helicity-dependent enhancement corresponds to control over the polarization of the resulting attosecond waveforms. Here, this helicity control enables the generation of circularly-polarized high harmonics with a user-defined polarization of the underlying attosecond bursts. In the future, this technique should allow for the production of bright highly elliptical harmonic supercontinua as well as the generation of isolated elliptically polarized attosecond pulses.
74 ATOMIC AND MOLECULAR PHYSICS↗
On Reverse Stackelberg Game and Optimal Mean Field Control for a Large Population of Thermostatically Controlled Loads
This paper studies a multi-stage pricing problem for a large population of thermostatically controlled loads. The problem is formulated as a reverse Stackelberg game that involves a mean field game in the hierarchy of decision making. In particular, in the higher level, a coordinator needs to design a pricing function to motivate individual agents to maximize the social welfare. In the lower level, the individual utility maximization problem of each agent forms a mean field game coupled through the pricing function that depends on the average of the population control/state. We derive the solution to the reverse Stackelberg game by connecting it to a team problem and the competitive equilibrium, and we show that this solution corresponds to the optimal mean field control that maximizes the social welfare. Realistic simulations are presented to validate the proposed methods.
Li, Sen↗
Vulnerability Detection Methodology for a Digital Signal Processor Micro-Controller at Edge Level Distributed Energy Resource Controller
Integration of renewable energy and energy storage based Distributed Energy Resource (DER) assets to the grid has seen an upsurge over the past few decades. Traditionally, energy would be generated at a thermal or nuclear power plant and then transmitted over long distance through the transmission grid and then supply to the customers at the distribution grid. Modern renewable energy based DER assets have brought energy production at the edge of distribution grid, which has made the grid vulnerable to cyber intrusion as the power flow controllers for such DER assets are now distributed across the grid from distribution level to transmission level. This paper discusses the vulnerability posed by such power flow controllers of DER assets and demonstrates a detection methodology for unauthorized access and manipulation of system configuration for Digital Signal Processor based Microcontrollers. Experimental results proving efficacy of the methodology have been shown in paper.
Bhowmik, Pankaj↗
Optimizing Traffic Signal Control to Enhance Transportation Efficiency and Maximize Pedestrian Benefits in the Road Network
Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.
Kumarasamy, Vijayalakshmi K [The University of Ten↗
Modeling Stationary Lithium-Ion Batteries for Optimization and Predictive Control
Accurately modeling stationary battery storage behavior is crucial to understand and predict its limitations in demand-side management scenarios. In this paper, a lithium-ion battery model was derived to estimate lifetime and state-of-charge for building-integrated use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. In order to achieve these goals, a mixed modeling approach was taken, which incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. A comparison of the proposed battery model output to actual data from the manufacturer validates the modeling approach taken in the paper. Additionally, a dynamic test case demonstrates the effects of using regression models to represent internal resistance and capacity fading.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
EMS and DMS Integration of the Coordinative Real-time Sub-Transmission Volt-Var Control Tool under High DER Penetration
This paper proposes an applicable approach to deploy the Coordinative Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT), and a holistic system integration framework considering both the energy management system (EMS) and distribution system management system (DMS). This provides an architectural basis and can serve as the implementation guideline of CReST-VCT and other advanced grid support tools, to co-optimize the operation benefits of DERs and assets in both transmission and distribution networks. Potential communication protocols for different physical domains of a real application is included. Performance and security issues are also discussed, along with specific considerations for field deployment. Finally, the paper presents a viable pathway for CReST-VCT and other advanced grid support tools, which could be integrated in an open-source standardized-based platform that supports distribution utilities.
Nguyen, Quan H.↗
Development of a Host-Based Intrusion Detection and Control Device for Industrial Field Control Devices
Industrial control systems contain a multitude of devices deployed into the field to observe and control a physical process. Currently, most of these devices lack common host-based cybersecurity features, which can lead them to be seen as vulnerable targets. The Cymbiote device was developed to address this problem by examining multiple streams of data to determine what might indicate a potential threat, and to evaluate and execute appropriate response actions. This paper discusses the evolution of the Cymbiote device in response to evaluation and testing done on real-world hardware. Experimental results are discussed, as are the new developments that have been made to the device in response to the findings. In addition, we describe future research directions for this approach along with the experimental setup changes in response to the requirements for statistical rigor.
Rice, Theora R.↗
Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint
Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.
adversarial threats↗
Model Reduction for Inverters With Current Limiting and Dispatchable Virtual Oscillator Control
Not provided.
Energy & Fuels↗
Cybersecurity of Wide Area Monitoring, Protection and Control Systems for HVDC Applications
The flexibility provided by High Voltage Direct Current (HVDC) systems can be further extended by Wide Area Monitoring, Protection, and Control (WAMAPC) systems. WAMPAC systems enable many HVDC applications and, on the other hand, inevitably introduce cybersecurity concerns that need to be addressed. In this work, a security domain layer and decision framework is reported to detect and mitigate the impact of false data injection (FDI) attacks targeting HVDC stations. Specifically, a rule-based cyber-attack detection method is introduced and implemented on Raspberry Pi and tested on the real-time HVDC simulation facility on the real-time digital simulator (RTDS) platform at ABB U.S. Corporate Research Center.
cybersecurity↗