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At least 199 records · Page 11

Higher symmetry breaking and nonreciprocity in a driven-dissipative Dicke model

Higher symmetries in interacting many-body systems often give rise to new phases and unexpected dynamical behavior. Here, we theoretically investigate a variant of the Dicke model with higher-order discrete symmetry, resulting from complex-valued coupling coefficients between quantum emitters and a bosonic mode. We propose a driven-dissipative realization of this model focusing on optomechanical response of a driven atom tweezer array comprised of 𝑛 subensembles and placed within an optical cavity, with the phase of the driving field advancing stepwise between subensembles. Examining stationary points and their dynamical stability, we identify a phase diagram for 𝑛≥3 with three distinctive features: a ℤ 𝑛 (ℤ 2⁢𝑛 ) symmetry-breaking superradiant phase for even (odd) 𝑛, a normal unbroken-symmetry phase that is dynamically unstable due to nonreciprocal forces between emitters, and a first-order phase transition separating these phases. This 𝑛-phase Dicke model may be equivalently realized in a variety of optomechanical or optomagnonic settings, where it can serve as a test bed for studying high-order symmetry breaking and nonreciprocal interactions in open systems.

Non-reciprocal propagation↗

Rotated-Droop Control for Enhanced Stability and Power Decoupling in Microgrids With Complex Line Impedances

Classical droop control in microgrids predominantly assumes inductive line impedance, which simplifies implementation but causes power coupling and steady-state errors in systems with resistive and inductive lines. This paper proposes a rotated-droop control strategy for grid-forming inverters that reformulates the power equations by incorporating the magnitude and angle of the line impedance within a rotated reference frame. This method enhances the decoupling of active and reactive power dynamics without increasing complexity or requiring communication links. A small-signal state-space model was created to capture the dynamic behavior of the system under varying impedance parameters, preserving the original droop gains by rotating the power control structure. This allows eigenvalue-based stability analysis and enhances damping and transient performance. Simulation and experimental results validated the improved power-sharing performance, faster response, and robustness of the proposed method under different impedance conditions. This approach maintains the decentralized structure of the conventional droop control while enabling greater adaptability and scalability, making it suitable for modern inverter-based microgrids with dynamic topologies.

Campo-Ossa, Daniel Dario [Univ. of Puerto Rico, Ag↗

Curvature-controlled geometrical lensing behavior in self-propelled colloidal particle systems

In many biological systems, the curvature of the surfaces cells live on influences their collective properties. Curvature should likewise influence the behavior of active colloidal particles. We show using molecular simulation of self-propelled active particles on surfaces of Gaussian curvature (both positive and negative) how curvature sign and magnitude can alter the system's collective behavior. Curvature acts as a geometrical lens and shifts the critical density of motility-induced phase separation (MIPS) to lower values for positive curvature and higher values for negative curvature, which we explain theoretically by the nature of parallel lines in spherical and hyperbolic space. Curvature also fluidizes dense MIPS clusters due to the emergence of defect patterns disrupting the crystalline order inside the clusters. Using our findings, we engineer three confining surfaces that strategically combine regions of different curvature to produce a host of novel dynamical behaviors, including cyclic MIPS on spherocylinders, directionally biased cyclic MIPS on spherocones, and position dependent cluster fluctuations on metaballs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗

Fidelity Analysis of Complex Large-Scale Simulation Models of PEs (MARS) in Future Power Grids

With the proliferation of power electronic (PE)-based resources in the electric grid, there have been numerous different kinds of simulation models developed and studied to understand their dynamic behavior. Study of PE-based resources using each simulation model has its own distinct advantages and disadvantages. Therefore it is very important to carefully select the appropriate model for the evaluation of the PE-based resources. In this paper, one such effort is made to analyze the different types of models in the case of a multi-port autonomous reconfigurable solar power plant (MARS). The MARS integrates a hybrid photovoltaic (PV)-energy storage system (ESS) plant to high-voltage direct current (HVdc) system and transmission alternating current (ac) grid. The dynamic models are evaluated under different test cases varying the short-circuit ratio (SCR) and control algorithms. Recommendations are provided on the equipment study needs based on the analysis completed.

Marthi, Phani Ratna Vanamali↗

PV-Fed Smart Inverters for Mitigation of Voltage and Frequency Fluctuations in Islanded Microgrids

The presence of low-inertia distributed generation (DG) units makes islanded microgrids vulnerable to voltage and frequency variations. Besides, the considerable difference between the inertia of synchronous-based and inverter-based DGs results in a power imbalance between supply and demand during abnormal conditions. As a result, both voltage and frequency of microgrid ac-bus start oscillating which might have severe consequences such as blackouts. This paper deploys the traditional controller of photovoltaic (PV) units to improve the dynamic behavior of islanded microgrids by suppressing the voltage and frequency fluctuations. To this end, an adaptive piecewise droop (APD) characteristic is proposed and employed in PV units to attain a faster balance between generation and consumption during transients, leading to an enhanced frequency response. Besides, the reactive-power control loop is equipped with a droop characteristic which enables the PV units to inject/absorb reactive power during transients and participate in voltage-profile enhancement of the system. Case study results are presented using PSCAD/EMTDC to confirm the validity of proposed method in improving the dynamics of islanded microgrids.

Pilehvar, Mohsen S.↗

Analyzing impact of $\mathrm{DER}$ on $\mathrm{FIDVR}$ - comparison of $\mathrm{EMT}$ simulation of a combined transmission and distribution grid with aggregated positive sequence models

The increase in percentage of distributed energy resources (DERs) brings in a degree of uncertainty in bulk power system planning and operations. Further, the presence of 1 - φ induction motors introduces the possibility of motor stalling and fault induced delayed voltage recovery (FIDVR). With newer versions of IEEE Std 1547™ there can be the opportunity to obtain dynamic voltage support from DERs. In this report, the impact of DERs providing dynamic voltage on the dynamic behavior of 1 - φ induction motors is examined in detail along with an exploration of the need for simulation platforms that go beyond positive sequence. The studies discussed here are carried out both in detailed electromagnetic time domain and in positive sequence domain for comparison.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Review of the Serrated-Flow Phenomenon and Its Role in the Deformation Behavior of High-Entropy Alloys

High-entropy alloys (HEAs) are a novel class of alloys that have many desirable properties. The serrated flow that occurs in high-entropy alloys during mechanical deformation is an important phenomenon since it can lead to significant changes in the microstructure of the alloy. In this article, we review the recent findings on the serration behavior in a variety of high-entropy alloys. Relationships among the serrated flow behavior, composition, microstructure, and testing condition are explored. Importantly, the mechanical-testing type (compression/tension), testing temperature, applied strain rate, and serration type for certain high-entropy alloys are summarized. The literature reveals that the serrated flow can be affected by experimental conditions such as the strain rate and test temperature. Furthermore, this type of phenomenon has been successfully modeled and analyzed, using several different types of analytical methods, including the mean-field theory formalism and the complexity-analysis technique. Importantly, the results of the analyses show that the serrated flow in HEAs consists of complex dynamical behavior. It is anticipated that this review will provide some useful and clarifying information regarding the serrated-flow mechanisms in this material system. Finally, suggestions for future research directions in this field are proposed, such as the effects of irradiation, additives (such as C and Al), the presence of nanoparticles, and twinning on the serrated flow behavior in HEAs.

36 MATERIALS SCIENCE↗

Dynamics in Flexible Pillar[ n ]arenes Probed by Solid-State NMR

Pillar[n]arenes are supramolecular assemblies that can perform a range of technologically important molecular separations which are enabled by their molecular flexibility. Here, we probe dynamical behavior by performing a range of variable-temperature solid-state NMR experiments on microcrystalline perethylated pillar[n]arene (n = 5, 6) and the corresponding three pillar[6]arene xylene adducts in the 100–350 K range. This was achieved either by measuring site-selective motional averaged 13 C 1 H heteronuclear dipolar couplings and subsequently accessing order parameters or by determining 1 H and 13 C spin–lattice relaxation times and extracting correlation times based on dipolar and/or chemical shift anisotropy relaxation mechanisms. We demonstrate fast motional regimes at room temperature and highlight a significant difference in dynamics between the core of the pillar[n]arenes, the protruding flexible ethoxy groups, and the adsorbed xylene guest. Additionally, unexpected and sizable 13 C 1 H heteronuclear dipolar couplings for a quaternary carbon were observed for p-xylene adsorbed in pillar[6]arene only, indicating a strong host–guest interaction and establishing the p-xylene location inside the host, confirming structural refinements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

LDRD conclusion poster - Synthesizing Heterometallic Uranium Single Crystals to Understand the Influence of the Secondary Metals on Uranyl Axial Bond Strength

Understanding how transition metals influenced the chemistry of lanthanide and actinide (f-element) materials is critical for advancing separation technologies, materials design, and coordination chemistry. This project examined how incorporating first-row transition metals affected the structural and spectroscopic properties of f-element coordination polymers. In uranium(VI)-based systems synthesized with 2,6-pyridinedicarboxylic acid (PDC) ligands, single-crystal X-ray diffraction and Raman spectroscopy revealed that the presence of transition metals shortened the uranyl axial bond and induced a blue shift in its symmetric stretching vibration—evidence of increased bond strength. Electronic structure analysis, including Density of States (DOS) calculations using density functional theory (DFT), revealed altered orbital overlaps and highlighted the role of transition metal d-orbitals in modulating bonding. Raman modes were modeled using truncated structural fragments in collaboration with the University of Notre Dame, and although the predicted frequencies were lower than experimental values, they remained within expected ranges. In parallel, similar experiments with cerium (Ce) in the presence of cobalt (Co) and PDC demonstrated multi-step single-crystal-to-single-crystal transformations—behavior not observed in the uranium systems. Initial products included light yellow, orange, and polycrystalline materials. Single-crystal X-ray diffraction studies, conducted in collaboration with the Colorado School of Mines, identified the yellow phase as monometallic Ce(PDC)2(H2O)2·4H2O and the orange phase as heterometallic Ce2Co(PDC)4(H2O)6. After standing in solution for one week, both phases fully transformed into a dark yellow crystalline phase, [Ce3(PDC)5(H2O)8].6(H2O). Remarkably, this transformation was reversible—disturbing the equilibrium by removing some crystals caused reversion to the initial Ce(PDC)2(H2O)2·4H2O phase, highlighting dynamic behavior. All three structures were previously unreported. Solid-state UV-visible and Raman spectroscopy further distinguished these phases, revealing ligand-to-metal charge transfer involving Ce and characteristic d–d transitions from Co(II). The precise mechanism driving these transformations remained unclear; however, pH-dependent experiments confirmed that the transformation did not occur when the pH decreased. Overall, the project demonstrated that transition metals could be employed to tune bonding interactions, structural dimensionality, and optical properties in f-element materials, establishing new pathways for designing functional heterometallic systems. The work resulted in several novel structural discoveries and fostered productive collaborations with the University of Notre Dame and the Colorado School of Mines.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Emerging Electrochemical Techniques for Probing Site Behavior in Single-Atom Electrocatalysts

Single-atom catalysts (SACs) have aroused tremendous interest over the past decade, particularly in the community of energy and environment-related electrocatalysis. A rapidly growing number of recent publications have recognized it as a promising candidate with maximum atomic utilization, distinct activity, and selectivity in comparison to bulk catalysts and nanocatalysts. However, the complexity of localized coordination environments and the dispersion of isolated sites lead to significant difficulties when it comes to gaining insight into the intrinsic behavior of electrocatalytic reactions. Furthermore, the low metal loadings of most SACs make conventional ensemble measurements less likely to be accurate on the subnanoscale. Thus, it remains challenging to probe the activity and properties of individual atomic sites by available commercial instruments and analytical methods. In spite of this, continuing efforts have lately focused on the development of advanced measurement methodologies, which are very useful to the fundamental understanding of SACs. There have recently been a number of in situ/operando techniques applied to SACs, such as electron microscopy, spectroscopy, and other analysis methods, which support relevant functions to identify the active sites and reaction intermediates and to investigate the dynamic behavior of localized structures of the catalytic sites. This Account aims to present recent electrochemical probing techniques which can be used to identify single-atomic catalytic sites within solid supports. First, we describe the basic principles of molecular probe methods for the study and analysis of electrocatalytic site behavior. In particular, the in situ probing technique enabled by surface interrogation scanning electrochemical microscopy (SISECM) can measure the active site density and kinetic rate with high resolution. An alternative electrochemical probing technique is further demonstrated on the basis of single-entity electrochemistry, which allows the unique electrochemical imaging of the size and catalytic rate of single atoms, molecules, and clusters. Next, the merits and limitations of different electrochemical techniques are then discussed, along with perspectives for future prospects. Apart from this, we further showcase the powerful capability of emerging electrochemical probing techniques for determining significant effects and properties of SACs for various electrocatalytic reactions, including oxygen reduction and evolution, hydrogen evolution, and nitrate reduction. Overall, electrochemical techniques with atomic resolution have greatly increased opportunities for observing, measuring, and understanding the surface and interface chemistry during energy conversion. In the future, it is anticipated that the development of electrochemical probing techniques will be advanced with innovative perspectives on the behavior and features of SACs. We hope that this Account can contribute in several ways to promoting the fundamental knowledge and technical progress of emerging electrochemical measurements for studying SACs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Summary of GNU Octave Lady Godiva Simulator

A pseudo real-time interactive reactor simulator for the Lady Godiva reactor has been developed using the GNU Octave software package. The simulator tracks the time-dependent power and fuel temperature behavior of the Lady Godiva reactor during sub-prompt critical transients. Users interact with the simulator by controlling reactivity input. This input occurs through users repositioning a control rod as desired during simulator operation. Various reactor parameters are displayed graphically in near “real time,” facilitating user assessment and feedback input. The reactor model consists of a lumped-fuel core, a single control rod, and a simple heat transfer mechanism that allows heat to be rejected from the core. The goal of the simulator is to demonstrate in real-time the system response to reactivity perturbations, the effect of reactivity feedback, and the effect of temperature-dependent equilibrium conditions. The dynamic behavior of the reactor is primarily driven by the relative characteristic time-constants between the delayed neutrons and the overall heat transfer parameter. The simulator will allow users to gain experience performing standard reactor operations, such as establishing steady-state at different fuel temperatures and making power level changes

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Performance of multifunctional piezoelectric energy harvesting microgyroscopes with material degradation

Most microelectromechanical systems (MEMS) are made from brittle materials that are prone to cracking. Damage from the formation of cracks can occur anytime during the manufacturing process or due to mechanical loading of MEMS devices. Cracks can increase the structures flexibility and lead to changes in performance or total failure. Understanding the potential influences cracks in MEMS is necessary for the longevity of these systems. The energy harvesting microgyroscope studied in this work is susceptible to crack propagation in its silicon substrate and lead zirconate titanate piezoelectric patch. To this end, an electromechanical model is developed to capture the impacts of cracks on the performance of a damaged energy harvesting microgyroscope. Numerical methods are used to approximate the damage associated with distributed crack networks. Then, the static and dynamic responses of the damaged microgyroscope are analyzed for two possible multifunctional setups. Here, the current study revealed that cracks can significantly affect the static and dynamic behaviors of the microgyroscope energy harvester. Combinations of cracking and piezoelectric property degradation cause a decrease in the static pull-in voltage and shift the resonance frequencies of the system. Additionally, it is shown that the systems sensitivity to changes in the base rotation and energy harvesting capabilities vary widely depending on the severity of material degradation.

36 MATERIALS SCIENCE↗

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structural behavior

High-frequency (e.g., 10 Hz) eddy covariance measurements are typically used to estimate fluxes at the land–atmosphere interface at timescales of 15–60 min. These multivariate data contain information about the interdependency at high frequency between the interacting variables such as wind, humidity, temperature, and CO 2⁠ . We use data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US, which offers an opportunity to move beyond the traditional spectral analyses to explore causal dependency among variables. In this study, we quantify the structure of inter-dependencies of interacting variables at high frequency represented by a directed acyclic graph (DAG). We compare DAGs to investigate changes in structural differences in causal interactions. We then apply a distance-based classification and -means clustering approach to identify the evolution of the causal structure represented by a DAG. Our method selects an unbiased number of clusters of similar structures and characterizes the similarities and differences between them. We explore a range of dynamic behavior using data from a clear sky day and during a solar eclipse in 2017. Our results show well-defined clusters of similar causal dependencies as the system evolves. Furthermore, our approach provides a methodological framework to understand how causal dependence in turbulence manifests in high-frequency data when represented through a DAG.

54 ENVIRONMENTAL SCIENCES↗

In-situ ion irradiation of fission products in a spent UO 2 fuel

This study investigates the behavior of fission gas bubbles and five metal precipitates (5MPs) (Mo, Ru, Rh, Tc, Pd) in spent uranium dioxide (UO 2 ) fuel under various ion irradiation doses, temperatures, and flux conditions. Utilizing in-situ ion irradiation and advanced transmission electron microscopy, we analyzed the evolution of fission gas bubbles and 5MPs in UO 2 samples from the Belgium Reactor 3 (BR-3). Our findings reveal significant shrinkage of fission gas bubbles and 5MPs with increasing irradiation dose, accompanied by a decrease in pair density. We demonstrate that ion irradiation induces a homogeneous re-solution process where individual atoms are ejected from bubbles and precipitates, leading to their dissolution and subsequent re-precipitation in the matrix. In conclusion, this study provides critical insights into the dynamic behavior of fission products under irradiation, facilitating the development of predictive models and contributing to the optimization of nuclear fuel performance and safety.

Fission products↗

Analysis of AC-DC Converters for Grid-tied High Temperature Steam Electrolysis Systems

Grid-tied HTSE systems have the prospects to produce clean hydrogen enabling power and broad energy systems decarbonization. Most commercially available power electronic converter systems (PECS) are designed for batteries, solar PVs, wind, and other well-established renewable energy resources. Standards (such as IEEE 1547, UL 1741, CA Rule-21, HI Rule-14) exist for PECS used for renewable energy systems such as battery storage and solar PVs. However, those that consider the dynamic behavior of HTSEs and that can be used for large-scale H2 systems are yet to be developed. This paper investigates the performance of these PECS for the HTSE application that are set up at the Idaho National Laboratory for hydrogen production testing, research and development. In particular, the performance analysis of two grid-tied PECS (A and B) is conducted for a 100 kW solid oxide HTSE system. System A consists of 6 units of 30kW MOSFET-switched bidirectional AC-DC rectifier while system B has a single unit of 150kW thyristor-switched ACDC rectifier. Both systems are connected to the HTSE stacks via a DC-DC converter. Different operational conditions of the HTSE system are tested to analyze the dynamic response of the HTSE’s PECS. The experimental results show the need to develop advanced control strategies for PECS that incorporates the dynamics of HTSE systems for improved performance.

08 - HYDROGEN↗

Analysis of AC-DC Converters for Grid-tied High Temperature Steam Electrolysis Systems

Grid-tied HTSE systems have the prospects to produce clean hydrogen enabling power and broad energy systems decarbonization. Most commercially available power electronic converter systems (PECS) are designed for batteries, solar PVs, wind, and other well-established renewable energy resources. Standards (such as IEEE 1547, UL 1741, CA Rule-21, HI Rule14) exist for PECS used for renewable energy systems such as battery storage and solar PVs. However, those that consider the dynamic behavior of HTSEs and that can be used for large-scale H2 systems are yet to be developed. This paper investigates the performance of these PECS for the HTSE application that are set up at the Idaho National Laboratory for hydrogen production testing, research and development. In particular, the performance analysis of two grid-tied PECS (A and B) is conducted for a 100 kW solid oxide HTSE system. System A consists of 6 units of 30kW MOSFET-switched bidirectional AC-DC rectifier while system B has a single unit of 150kW thyristor-switched AC-DC rectifier. Both systems are connected to the HTSE stacks via a DC-DC converter. Different operational conditions of the HTSE system are tested to analyze the dynamic response of the HTSE’s PECS. The experimental results show the need to develop advanced control strategies for PECS that incorporates the dynamics of HTSE systems for improved performance.

High temperature steam electrolysis↗

Cooperative Automated Cohort Driving on Connected Infrastructure, Arterial Roadways, and Highways: Final Project Demonstration and System-of-Systems Model Correlation

This project seeks to synergize vehicle automated driving and connectivity data to improve mobility and energy efficiency of groups of mixed vehicles operating in close proximity (vehicle cohort) on various infrastructure. A custom cellular communication network links vehicles operating as a cohort with infrastructure to a centralized system-of-systems digital twin with an AI-based optimal behavior planner. The data contained in this set are from final testing and technology demonstrations to U.S. Department of Energy staff at the American Center for Mobility. The data contain single-lane, single-light scenarios; multi-lane, multi-light arterial scenarios; and limited-access highway scenarios. All test cases were derived from simulations and replicated on the test track. The project employed two and four light-duty vehicles with connectivity and drive automation for the testing. The baseline scenario without connectivity was run under the control of the system-of-systems centralized planner but operating each vehicle with an intelligent driver model controlling the velocity, lane utilization, and vehicle gap. This was to ensure the highest compatibility with the simulation in terms of dynamic behavior. The connected cohort case utilized AI optimization to perform coordinated and cooperative control for energy, as well as safe, comfortable behavior for the cohort. The dataset is appropriately named with unconnected and connected designations, with comparisons sharing the same run index number. The included PowerPoint and PDF files describe the test setup and provide an overview of results from the project. ![image](de-EE0009209_March_2023_Data_Arterial_Scenario_Results.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗