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At least 1,297 records · Page 72

Mechanisms of adsorbing hydrogen gas on metal decorated graphene

Hydrogen is a key player in global strategies to reduce greenhouse gas emissions. In order to make hydrogen a widely used fuel, we require more efficient methods of storing it than the current standard of pressurized cylinders. An alternative method is to adsorb H 2 in a material and avoid the use of high pressures. Among many potential materials, layered materials such as graphene present a practical advantage as they are lightweight. However, graphene and other 2D materials typically bind H 2 too weakly to store it at the typical operating conditions of a hydrogen fuel cell, meaning that high pressure would still be required. Modifying the material, for example by decorating graphene with adatoms, can strengthen the adsorption energy of H 2 molecules, but the underlying mechanisms are still not well understood. In this work, we systematically screen alkali and alkaline-earth metal decorated graphene sheets for the static thermodynamic adsorption of hydrogen gas from first principles and focus on the mechanisms of binding. We show that there are three mechanisms of adsorption on metal decorated graphene and each leads to distinctly different hydrogen adsorption structures. The three mechanisms can be described as weak van der Waals physisorption, metal adatom facilitated polarization, and Kubas adsorption. Among these mechanisms, we find that Kubas adsorption is easily perturbed by an external electric field, providing a way to tune H 2 adsorption. In conclusion, this work is foundational and builds our understanding of H 2 adsorption under idealized conditions.

36 MATERIALS SCIENCE↗

Dynamic, symmetry-preserving, and hardware-adaptable circuits for quantum computing many-body states and correlators of the Anderson impurity model

We present a hardware-reconfigurable ansatz on N q -qubits for the variational preparation of many-body states of the Anderson impurity model (AIM) with N imp + N bath = N q /2 sites, which conserves total charge and spin z component within each variational search subspace. The many-body ground state of the AIM is determined as the minimum over all minima of O(N$^2_ q$) distinct charge-spin sectors. Hamiltonian expectation values are shown to require ω(N q ) < N meas. $\leqslant$ O(N imp N bath ) symmetry-preserving, parallelizable measurement circuits, each amenable to postselection. To obtain the one-particle impurity Green’s function we show how initial Krylov vectors can be computed via midcircuit measurement and how Lanczos iterations can be computed using the symmetry-preserving ansatz. For a single-impurity Anderson model with a number of bath sites increasing from one to seven, we show using numerical emulation that the ease of variational ground-state preparation is suggestive of linear scaling in circuit depth and subquartic scaling in optimizer complexity. We therefore expect that, combined with time-dependent methods for Green’s function computation, our ansatz provides a useful tool to account for electronic correlations on early fault-tolerant processors. Finally, with a view towards computing real materials properties of interest like magnetic susceptibilities and electron-hole propagators, we provide a straightforward method to compute many-body, time-dependent correlation functions using a combination of time evolution, midcircuit measurement-conditioned operations, and the Hadamard test.

36 MATERIALS SCIENCE↗

Quasiprobabilistic Readout Correction of Midcircuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Quantum measurements are a fundamental component of quantum computing. However, on present-day quantum computers, measurements can be more error prone than quantum gates and are susceptible to nonunital errors as well as nonlocal correlations due to measurement crosstalk. While readout errors can be mitigated in postprocessing, this is inefficient in the number of qubits due to a combinatorially large number of possible states that need to be characterized. In this work, we show that measurement errors can be tailored into a simple stochastic error model using randomized compiling, enabling the efficient mitigation of readout errors via quasiprobability distributions reconstructed from the measurement of a single preparation state in an exponentially large confusion matrix. We demonstrate the scalability and power of this approach by correcting readout errors without matrix inversion on a large number of different preparation states applied to a register of eight superconducting transmon qubits. Moreover, we show that this method can be extended to midcircuit measurements used for active feedback via quasiprobabilistic error cancellation, and we demonstrate the correction of measurement errors on an ancilla qubit used to detect and actively correct bit-flip errors on an entangled memory qubit. Our approach enables the correction of readout errors on large numbers of qubits and offers a strategy for correcting readout errors in adaptive circuits in which the results of midcircuit measurements are used to perform conditional operations on nonlocal qubits in real time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Development of a versatile electrochemical cell for in situ grazing-incidence X-ray diffraction during non-aqueous electrochemical nitrogen reduction

In situ techniques are essential to understanding the behavior of electrocatalysts under operating conditions. When employed, in situ synchrotron grazing-incidence X-ray diffraction (GI-XRD) can provide time-resolved structural information of materials formed at the electrode surface. In situ cells, however, often require epoxy resins to secure electrodes, do not enable electrolyte flow, or exhibit limited chemical compatibility, hindering the study of non-aqueous electrochemical systems. Here, a versatile electrochemical cell for air-free in situ synchrotron GI-XRD during non-aqueous Li-mediated electrochemical N 2 reduction (Li-N 2 R) has been designed. This cell not only fulfills the stringent material requirements necessary to study this system but is also readily extendable to other electrochemical systems. Under conditions relevant to non-aqueous Li-N 2 R, the formation of Li metal, LiOH and Li 2 O as well as a peak consistent with the α-phase of Li 3 N was observed, thus demonstrating the functionality of this cell toward developing a mechanistic understanding of complicated electrochemical systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Data driven drift correction for complex optical systems

To exploit the thousand-fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise beam trajectory. Maintaining the optimal trajectory over several hours of an experiment with the needed precision necessitates active drift control. Here, we outline time varying Bayesian optimization (TVBO) as a data driven approach for robust drift correction, and illustrate its application for a split and delay optical system composed of six crystals and twelve input dimensions. Using numerical simulations, we exhibit the application of TVBO for linear drift, non-smooth temporal drift as well as constrained TVBO for multi-objective control settings, representing real-life operating conditions. This approach can be easily adapted to other X-ray beam conditioning and guidance systems, including multi-crystal monochromators and grazing-incidence mirrors, to maintain sub-micrometer and nanoradian beam stability over the course of an experiment spanning several hours.

Bayesian optimization↗

Summary of Working Group 3: Laser and High-Gradient Structure-Based Acceleration

Accelerating particles at high gradients with high efficiencies is essential for reduction of size and cost of future accelerators for science and industry. This includes a future multi-TeV e+e- collider for particle, free-electron lasers for basic energy sciences and national security, industrial accelerators for energy and environmental applications, and accelerators for other applications. One way to achieve this is to use advanced externally-powered structures, both laser and RF driven. Working Group 3 (WG3) discussed novel accelerating structures with new geometries, new materials, frequencies from microwave to THz and optical spectrum, and operating conditions from room temperature to cryogenic. Presentations included recent advances in understanding RF breakdown and multipactor phenomena at different frequencies and materials, and other physics limitations to the accelerating gradient. Other relevant topics, such as developing high-gradient photoinjectors, high-efficiency RF power sources, and RF structures for a potential muon collider were discussed also. More details on each of the WG3 topics can be found in the articles published in these proceedings.

43 PARTICLE ACCELERATORS↗

Coupled Induction Machine and HVAC Models for Simulating HVAC Performance Considering Grid Dynamics in Buildings

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R 2 ) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Phase Drifts and Signal Dispersion in Coaxial Cables

Phase reference distribution is a critical challenge in modern linear particle accelerators, such as European Spallation Source (ESS), European X-ray Free Electron Laser (E-XFEL), or Proton Improvement Plan II (PIP-II). Similar issues may also arise in other RF systems that need to synchronize many independent circuits. Achieving low phase drift of the reference signal requires careful selection of cables and their environmental operating conditions. Due to the limited data provided by cable manufacturers, it is necessary to characterize the cable performance. This article investigates the phase drifts in coaxial cables and presents a dedicated measurement methodology. The dispersion characteristics of the cables are also examined. The measurement results of various coaxial cables are presented, along with conclusions and practical guidelines for designers of phase reference distribution lines.

coaxial cables↗

A Control Scheme to Mitigate the Dead-Time Effects in a Wireless Power Transfer System

In practice, a dead-time is always provided between the complementary switching instances of the inverter phase-leg devices. At higher operating frequencies, the dead-time issues in wireless power transfer (WPT) systems become critical, especially as the power level increases. In certain operating conditions, the dead-time effect in wireless power transfer system affects the switching characteristics. Consequently, the switching losses in the power semiconductor devices increase and also impact the efficiency of the overall system. In this paper, a simple control scheme is proposed to eliminate the dead-time effect (or voltage polarity reversal) in the WPT inverter. The proposed control scheme monitors the inverter output voltage, and the switching frequency is auto-tuned to eliminate the undesired switching instances in the inverter voltage. The proposed control scheme is validated using the closed-loop simulations in PLECS, and the experimental results on a 5.6 kW WPT prototype are also presented. After eliminating the voltage-polarity-reversal at the inverter output, the inverter losses were reduced by ~40%, and the overall system losses were reduced by ~17%.

Kavimandan, Utkarsh↗

Modeling Multi-View Impedance-Based Cross-Geometry SOH Estimator for Li-ion Batteries

Abstract: Accurately estimating battery’s State of Health (SOH) remains challenging when models must generalize across cell designs and operating conditions. Most Electrochemical Impedance Spectroscopy (EIS)-based approaches either (i) hand-engineer a few Nyquist-plot features for shallow models—fast but does not generalize across geometries—or (ii) learn directly from Nyquist plots with deep networks, which removes manual feature extraction, yet still limited to a single plot type. As a result, cross-geometry robustness and deployability on constrained Internet of Things (IoT) devices remain open problems. We propose a compact Convolutional Neural Network (CNN) (∼ 10k parameters) that takes multi-representation EIS inputs—Nyquist (real/imaginary) and phase–magnitude (|Z|/ϕ) stacked as four channels, so the model can learn complementary degradation signatures while remaining small enough for fast inference. We build a dataset from cyclic aging of two geometries (LG INR18650MJ1 cylindrical cells and LIR2032 coin cells), acquire EIS every ten cycles from 10 kHz to 10 mHz (10 points/decade), and evaluate with leave-one-cell-out testing strategy. We further study fusion vs. single-representation inputs and assess feasibility for on-device deployment (e.g., NVIDIA Jetson device). The results show that training on multiple EIS representations improves SOH estimation accuracy and cross-geometry generalization compared to single-representation models, which uses only Nyquist or phase–magnitude plots. This design targets accurate, generalizable SOH prediction without manual feature engineering while enabling practical real-time use.

Bakr, Ahmed [The University of Alabama (UA)]↗

Experimental Results for an Inverter Integrated with A High-Speed Surface Permanent Magnet External Rotor Motor

This work presents the prototyping and testing of a high-speed outer rotor surface permanent magnet motor. The motor employs non-heavy rare-earth permanent magnets and operates at a rated speed of 6,666 rpm. In-slot ceramic heat exchangers are used to cool the windings. The external rotor configuration provides substantial space within the stator bore, which is used for power electronics integration. This integration introduces several design and thermal management challenges that are discussed in the paper. The machine has been prototyped and tested under various operating conditions, and both simulation and experimental results are presented.

Rallabandi, Vandana [ORNL] (ORCID:0000000236241901↗

Machine Learning-based False Data Injection Attack Detection and Localization in Power Grids

Cyberattacks on critical infrastructures can be catastrophic and bring nations to their knees. Therefore, detecting these attacks is crucial and challenging. This paper presents a novel approach for detecting and locating cyberattacks affecting an electrical power system. The adversary employs a man-in-the-middle technique to inject false data into the communication between distributed energy resources (DER) and Microgrid Controller (MGC) with the goal of disrupting power delivery. The approach for detection and localization is based on integrating multiple machine learning-based anomaly detection models that combine network traffic data and grid measurements. Experiments are performed to assess the method's performance using a hardware-in-the-loop real-time simulation testbed which includes Modbus TCP/IP communication. Power system topology and operating conditions are based on actual topology and real-world data provided by the Holy Cross Energy utility network. Results confirm that the method can be successfully employed for detecting and localizing cyberattacks.

Leao, Bruno P.↗

Comparison of Simulation of Dual-Active Bridge in Different Simulators and Using Different Simulation Methods

The accuracy of states measured from simulation of a dual-active bridge (DAB) converter with an open-loop controller has been used for comparing simulation software and algorithms. The accuracy of the measured states is sensitive to simulation settings and parameters chosen. In this paper, the simulation of the DAB converter with open-loop control is run in the MATLAB/Simscape Electrical, PLECS, and PSCAD software environments, with various simulation settings. The simulation results are also compared with a new simulation algorithm proposed for DAB simulations. Different simulation settings are evaluated, including different solver types, operating conditions, and the on-state resistance values of the MOSFET switches. The simulation results are compared with the theoretical calculations. It is shown that unexpected divergence and DC offset may occur in some cases. This paper provides guidelines to simulate the DAB converter with open-loop control.

Yin, Shiyuan↗

Synchronverter-based Control of Multi-Port Autonomous Reconfigurable Solar Plants (MARS)

Control of integrated photovoltaic (PV) plants with energy storage systems (ESSs) has become an important research and development topic in recent times. In this context, a Multi-port Autonomous Reconfigurable Solar (MARS) plant that integrates PV and ESS to alternating current transmission grid and high-voltage direct current (HVdc) link is studied in this paper. With penetration of power electronic based resources in the grid, the grid’s capability to recover from frequency or voltage disturbances are reduced. Therefore, one of the vital objectives of any new grid integrated power electronic resource is to provide advanced control functions like voltage and frequency support to the grid during disturbances. In this research work, a detailed implementation of a synchronverter-based control algorithm of MARS is presented. The proposed control algorithm and the MARS control architecture are evaluated through simulations on PSCAD/EMTDC simulation platform to showcase the performance in different operating conditions. In addition, they are evaluated in Opal-RT offline simulation models which can also be used to perform control-hardware-in-the-loop (cHIL) tests.

Marthi, Phani Ratna Vanamali↗

Characterization and Analysis of Insulated Metal Substrate-Based SiC Power Module for Traction Application

This paper presents the electrical characterization and drive cycle--based thermal analysis of an insulated metal substrate (IMS)--based silicon carbide power module for high-power traction inverters. The substrate was constructed using a thin layer of polymer--ceramic blend dielectric material with a thick copper core to improve transient thermal performance. The cooling performance of this module has already been validated with promising results. In this paper, an experimental test bed was set up to evaluate the dynamic and static electrical performance of the designed module under a wide range of operating conditions. The characterization results were then used to develop a drive cycle--based thermal model to validate the performance compared to the traditional direct bonded copper--based power module. The results indicate that the IMS-based power module is a suitable solution for high-power traction applications.

Chowdhury, Shajjad↗

Comprehensive Efficiency Analysis of Current Source Inverter Based on CSI-Type Double Pulse Test and Genetic Algorithm

A current-source inverter (CSI) has a natural output voltage boost feature that can be advantageous for traction applications. Switching frequency is one of the easily-controlled variables that can be adjusted to improve the CSI efficiency at different operating points when the boost function is used. This paper investigates a CSI-based double-pulse test (DPT) measurement that mimics normal operation of the CSI. A loss model of the CSI is developed based on the CSI-type DPT experimental results. The impacts of the switching frequency and voltage boost ratio on the CSI efficiency and output voltage ripple are investigated. Based on the loss model, a genetic algorithm has been introduced that makes it possible to optimize the CSI's switching frequency and modulation index to maximize its efficiency under any desired operating condition.

current-source inverter, genetic algorithm, SPM ma↗

Dynamic Adaptive Relaying for Distribution Grids with High Inverter-Based Generation

The penetration of distributed energy resources (DERs) in distribution systems is rapidly increasing. This can lead to large variations in the operating load and the fault current seen by a relay, which can impact the reliability of overcurrent protection. Adaptive overcurrent relaying (AOCR) can address this concern by enabling the relay to adjust its pickup settings based on the system operating conditions. This paper presents a novel dynamic AOCR approach that allows the relays to locally estimate the pickup settings and dynamically modify them. The approach is based on a two-stage estimation algorithm that uses local measurements and system information to estimate the worst-case fault current and the relay pickup settings. The relay pickup settings are then dynamically modified based on the estimated fault current. The performance of the proposed approach is evaluated on multiple configurations of the EPRI J1 feeder and the IEEE 13-bus system. The results show that the proposed approach can effectively improve the reliability of overcurrent protection in distribution systems with DERs.

adaptive overcurrent protection↗

DC Microgrid Reliability Enhancement with Adaptive Converter Thermal Management

Due to the different device selections, aging levels, and thermal dissipation performance, some converters may take additional thermal stress on switching devices than others in paralleled converter systems, which will reduce system reliability. To address this problem, this paper proposes a power-sharing strategy with adaptive thermal management. First, the temperature-based power loss model and electrical-thermal model are established. Based on that, a high-accuracy IGBT junction temperature estimate considering the power loss-temperature coupling can be achieved. Further, the thermal-sharing for all the switching devices in paralleled converters can be achieved with the proposed adaptive thermal management strategy. The proposed strategy can change the power-sharing ratio adaptively according to the system operation conditions, which will contribute to the system reliability enhancement. The effectiveness of the proposed strategy is verified through PLECS thermal simulation and joint real-time simulation with Dspace and RT-box.

DC microgrid↗