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At least 1,261 records · Page 70

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DOE OSTI2021

Plentiful electricity turns wholesale prices negative

In 2020, average wholesale electricity prices in the United States fell to $21/MWh, their lowest level since the beginning of the 21st century. Low natural gas prices and the proliferation of low marginal cost resources like wind and solar had already established a trend toward lower wholesale prices, and this trend was exacerbated by declining electricity demand due to the Covid-19 pandemic in 2020. Negative real-time hourly wholesale prices occurred in about 4% of all hours and wholesale market nodes across the United States, but these were not distributed evenly. Regional clusters emerged, for example, in the Permian Basin in western Texas, and in Kansas and western Oklahoma in the Southwest Power Pool (SPP), negative prices accounted for more than 25% of all hours. Negative electricity prices result either from local congestion of the transmission system leading supply to exceed demand locally or due to system-wide oversupply. Looking at the latter condition in SPP, we find that all major generator types contribute to this excess supply, because of limited ramping flexibility or self-scheduled out-of-market unit commitments. Additional monetary production incentives such as renewable energy credits or tax credits also enable negative bids; indeed, negative prices predominantly occur when demand levels are low and wind production levels are high. Frequent negative prices can inform the value of additional renewable energy investments at specific locations, the need for transmission and storage development, and opportunities load growth or adaptation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM

Demand response (DR) serves an important role in improving the efficiency and stability of power systems. In recent years, with advances in communication and smart device technologies, many aggregators have emerged to facilitate end customer participation in DR programs. These aggregators, equipped with customized optimal control algorithms, are capable of providing various grid services. Among them is load scheduling during DR events, namely following a load signal provided by the utility company while minimizing overall customer discomfort. However, as the number of aggregators keeps increasing, it becomes challenging for utility companies to conduct load scheduling for multiple aggregators and generate reference signals for each of them. This paper proposes an optimization framework using hierarchical alternating direction method of multipliers (H-ADMM) to optimally generate load following signals for multiple aggregators. Under this framework, utility and multiple aggregators work in a cooperative manner, aiming at minimizing an overall system cost from different levels of the power system hierarchy, while protecting user privacy. A case study has been conducted in a system with multiple aggregators, based on control of HVAC loads. Experimental results validate the effectiveness of the proposed algorithm.

ADMM↗

DOE OSTI2025

Unveiling the Hidden Evolution of Crystal Defects and Disorder in Energy Materials

Control of point defects and disorder in functional thin films and 2D materials is critical to realizing their full potential in applications ranging from energy storage to advanced electronics. However, these phenomena are often poorly understood, difficult to characterize, and challenging to direct with precision. This presentation explores emerging multi-modal computer vision to decipher and predict order in materials across multiple length scales in the electron microscope, from the atomic to the nanoscale. By fusing data from diverse sources, these powerful models provide unprecedented insights into materials' lifecycles, enabling the control of defects and their associated properties at a fundamental level. This capability promises to transform materials design and accelerate the development of next-generation technologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM: Preprint

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

In Situ Synthesis of Molybdenum Carbide Nanoparticles Incorporated into Laser‐Patterned Nitrogen‐Doped Carbon for Room Temperature VOC Sensing

Abstract Carbon laser‐patterning (CLaP) is emerging as a new tool for the precise and selective synthesis of functional carbon‐based materials for on‐chip applications. The aim of this work is to demonstrate the applicability of laser‐patterned nitrogen‐doped carbon (LP‐NC) for resistive gas‐sensing applications. Films of pre‐carbonized organic nanoparticles on polyethylenetherephthalate are carbonized with a CO 2 ‐laser. Upon laser‐irradiation a compositional and morphological gradient in the films is generated with a carbon content of 92% near the top surface. The specific surface areas of the LP‐NC are increased by introducing sodium iodide (NaI) as a porogen. Electronic conductivity and surface area measurements corroborate the deeper penetration of the laser‐energy into the film in the presence of NaI. Furthermore, impregnation of LP‐NC with MoC 1− x (<10 nm) nanoparticles is achieved by addition of ammonium heptamolybdate into the precursor film. The resulting doping‐sensitive nano‐grain boundaries between p‐type carbon and metallic MoC 1− x lead to an improvement of the volatile organic compounds sensing response of Δ R / R 0 = −3.7% or −0.8% for 1250 ppm acetone or 900 ppm toluene at room temperature, respectively, which is competitive with carbon‐based sensor materials. Further advances in sensitivity and in situ functionalization are expected to make CLaP a useful method for printing selective sensor arrays.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Turbulence theories and statistical closure approaches

When discussing research in physics and in science more generally, it is common to ascribe equal importance to the three components of the scientific trinity: theoretical, experimental, and computational studies. This review will explore the future of modern turbulence theory by tracing its history, which began in earnest with Kolmogorov’s 1941 analysis of turbulence cascade and inertial range [A.N. Kolmogorov, Dokl. Akad. Nauk SSSR, 30, 299, (1941); 32, 19, (1941)]. The 80th Anniversary of Kolmogorov’s landmark study is a welcome opportunity to survey the achievements and evaluate the future of the theoretical approach of turbulence research. Over the years, turbulence theories have been critically important in laying the foundation of our understanding of the nature of turbulent flows. In particular, the Direct Interaction Approximation (DIA) [R.H. Kraichnan, J. Fluid Mech., 5, 497 (1959)] and its subsequent development, known as the statistical closure approach, can be identified as perhaps the most profound single advancement. The remarkable success of the statistical closure has furnished a platform to study such essential concepts as the energy transfer process and interacting scales, and the roles of the straining and sweeping motions. More recently, the quasi-Lagrangian formulation of V. L’vov & I. Procaccia and Kraichnan’s solvable passive scalar model provided powerful ways to explore another fundamental aspect of turbulent flows, the phenomena of intermittency, and the associated anomalous scaling exponents. In the meantime, the theory of fluid equilibria has been developed to describe the large-scale structures that can emerge from turbulent cascades of two-dimensional and geophysical flows at a later time. And yet, despite all these successes, analytical treatments suffer from mathematical complexities. As a result, the utility of theoretical approaches has been limited to relatively idealized flows. On the other hand, in recent decades, computational abilities and experimental facilities have reached an unprecedented scale. Looking beyond the horizon, the imminent deployment of exascale supercomputers will generate complete datasets of the entire flow field of key benchmark flows, allowing researchers to extract additional measurements concerning fully developed, complex turbulent flow fields far beyond those available from the statistical closure theories. Some other developments that could potentially influence the future course of turbulence theories include the advancement of machine learning, artificial intelligence, and data science; likely disruptions arising from the advent of quantum computation; and the increasingly prominent role of turbulence research in providing more accurate climate scientific data. Finally, turbulence theorists can leverage these developments by asking the right questions and developing advanced, sophisticated frameworks that will be able to predict and correlate vast amounts of data from the other two components of the trinity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality

Abstract Deep neural networks (‘deep learning’) have emerged as a technology of choice to tackle problems in speech recognition, computer vision, finance, etc. However, adoption of deep learning in physical domains brings substantial challenges stemming from the correlative nature of deep learning methods compared to the causal, hypothesis driven nature of modern science. We argue that the broad adoption of Bayesian methods incorporating prior knowledge, development of solutions with incorporated physical constraints and parsimonious structural descriptors and generative models, and ultimately adoption of causal models, offers a path forward for fundamental and applied research.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Metal Chalcogenides for Neuromorphic Computing: Emerging Materials and Mechanisms

The approaching end of Moore's Law scaling has significantly accelerated multiple fields of research including neuromorphic-, quantum-, and photonic computing, each of which possesses unique benefits unobtained through conventional binary computers. One of the most compelling arguments for neuromorphic computing systems is power consumption, noting that computations made in the human brain are approximately 106 times more efficient than conventional CMOS logic. This review article focuses on the materials science and physical mechanisms found in metal chalcogenides that are currently being explored for use in neuromorphic applications. We begin by reviewing the key biological signal generation and transduction mechanisms within neuronal components of mammalian brains and subsequently compare with observed experimental measurements in chalcogenides. With robustness and energy efficiency in mind, we will focus on short-range mechanisms such as structural phase changes and correlated electron systems that can be driven by low-energy stimuli, such as temperature or electric field. We aim to highlight fundamental materials research and existing gaps that need to be overcome to enable further integration or advancement of metal chalcogenides for neuromorphic systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Electric field control of chirality

Polar textures have attracted substantial attention in recent years as a promising analog to spin-based textures in ferromagnets. Here, using optical second-harmonic generation–based circular dichroism, we demonstrate deterministic and reversible control of chirality over mesoscale regions in ferroelectric vortices using an applied electric field. The microscopic origins of the chirality, the pathway during the switching, and the mechanism for electric field control are described theoretically via phase-field modeling and second-principles simulations, and experimentally by examination of the microscopic response of the vortices under an applied field. The emergence of chirality from the combination of nonchiral materials and subsequent control of the handedness with an electric field has far-reaching implications for new electronics based on chirality as a field-controllable order parameter.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Interface-Driven Chiral Magnetism in Ultrathin Metallic Ferromagnets: Towards Skyrmion Spintronics

Magnetic skyrmions are localized chiral magnetic textures in the form of nanoscale vortices or bubbles that are topologically protected from being ‘unwound’. Their topological nature gives rise to rich behaviors including ordered lattice formation, emergent electrodynamics and robust current-driven displacement at remarkably low current densities. However, magnetic skyrmions have so far been restricted to just a few materials and observed only at low temperatures, limiting the experimental accessibility and technological application of these unique topological objects. This project aimed to realize magnetic skyrmions at room temperature in a new class of engineered chiral ferromagnets that exploit broken mirror symmetry at interfaces to generate helical magnetic order. Ultrathin magnetic heterostructures were engineered and patterned into laterally-confined nanostructures in which skyrmions were stabilized, manipulated, and detected for the first time under ambient conditions. Static and dynamic properties were examined using advanced x-ray imaging to provide a fundamental understanding of topological magnetic phases. The interactions between magnetic skyrmions and electron charge and spin currents were studied to identify fundamental new physics and enable device applications. These experimental studies, supported by detailed modeling, will help launch a new subfield of skyrmion-based spintronics in which individual skyrmions can be used to encode, store, and transport information in high-performance, low power memory and logic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Resource Adequacy for State Utility Regulators: Current Practices and Emerging Reforms

This report was developed by staff in the National Association of Regulatory Utility Commissioners (NARUC) Center for Partnerships and Innovation (CPI). Additional support was provided from commissioners, commission staff, and other technical experts to provide foundational information for state utility regulators on the evolving nature of resource adequacy for the electric system. With the changing nature of the system, state commissioners will continue to play a vital role in their respective jurisdictions. Their roles in overseeing resource decisions are growing in complexity, with consideration for customer costs, state and federal environmental requirements, extreme weather events, fuel supply limitations, generation retirements, shifting requirements for system operators, and growing levels of intermittent and energy-limited resources (e.g., wind, solar, and battery storage). Reliability concerns continue to be an urgent and immediate priority for utility regulators in most parts of the United States. The information in this report is designed to support state commissioners and their respective staff members as they navigate an evolving resource adequacy landscape to maintain reliability amidst a rapidly changing system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Plasma Flow Reactor Investigation into Nucleation of Uranium Oxide on Silica Substrates to Better Understand Fallout Formation

Understanding particulate formation in nuclear debris is critical for predicting fallout transport after a nuclear event. Improved characterization of fallout formation and transport could lead to better guidance for emergency response in a post-detonation scenario. By analyzing how U-oxides nucleate onto different forms of SiO 2 (crystalline and amorphous), we can gain insight into how entrained environmental materials may incorporate into fallout. In this experiment a Plasma Flow Reactor (PFR), was used to replicate the high temperature and extreme flow conditions in a nuclear fireball. Uranyl nitrate was injected into the plasma, and PFR-generated Uranium oxides were allowed to condense onto amorphous (nanoparticles of varying sizes) or crystalline (quartz) SiO 2 substrates. SiO 2 substrates were characterized before and after U-oxide deposition using Scanning Electron Microscopy (SEM) based techniques (i.e. EDS) in order to characterize how U-oxides may nucleate onto these substrates. After a collection time of 4 minutes at an RF coil distance of 25cm, both the amorphous SiO 2 nanoparticles and the crystalline structures demonstrated dendritic nucleation of U-oxide species as identified by SEM/EDS.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Next-Generation Intensity-Duration-Frequency Curves for Climate-Resilient Infrastructure Design: Advances and Opportunities

National and international security communities (e.g., U.S. Department of Defense) have shown increasing attention for innovating critical infrastructure and installations due to recurring high-profile flooding events in recent years. The standard infrastructure design approach relies on local precipitation-based intensity-duration-frequency (PREC-IDF) curves that do not account for snow process and assume stationary climate, leading to high failure risk and increased maintenance costs. This paper reviews the recently developed next-generation IDF (NG-IDF) curves that explicitly account for the mechanisms of extreme water available for runoff including rainfall, snowmelt, and rain-on-snow under nonstationary climate. The NG-IDF curve is an enhancement to the PREC-IDF curve and provides a consistent design approach across rain- to snow-dominated regions, which can benefit engineers and planners responsible for designing climate-resilient facilities, federal emergency agencies responsible for the flood insurance program, and local jurisdictions responsible for developing design manuals and approving subsequent infrastructure designs. Further, we discuss the recent advances in climate and hydrologic science communities that have not been translated into actional information in the engineering community. To bridge the gap, we advocate that building climate-resilient infrastructure goes beyond the traditional local design scale where engineers rely on recipe-based methods only; the future hydrologic design is a multi-scale problem and requires closer collaboration between climate scientists, hydrologists, and civil engineers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Zonal Flow and Self-regulating Mechanism in a Hydrodynamic Disk

This study addresses key aspects of momentum transport in hydrodynamic disks, which is critical for understanding zonal flow generation and turbulence in compressible hydrodynamic disks. We find that nonlinear momentum/density transport leads to the formation of zonal flows from the Rossby wave instability in disks. We analytically derive the generation and location of zonal flows and describe a modified Taylor identity applicable to compressible disk flows. We further present a self-regulation model, revealing a dynamic interplay between zonal flow and fluctuations driven by Rossby wave instability that regulates the nonlinear saturation state. This theoretical framework contributes insights into the dynamics of disks such as protoplanetary disks, shedding light on the intricate processes governing momentum/density transport and the emergence of zonal flows in the saturation of protoplanetary disks.

Astrophysical fluid dynamics↗

DOE OSTI2026

Multi-Agent Control Planes for Quantum Networks: A Scalable Architecture for Autonomous Quantum Internet Management

Quantum networks are expected to enable distributed quantum computing, secure communication, and global entanglement distribution. However, operating such networks presents significant challenges, including stochastic quantum processes, fragile entanglement resources, dynamic topology, and cross-layer control requirements. Current quantum network control architectures largely rely on centralized or hierarchical controllers inspired by classical software-defined networking (SDN). While effective for small testbeds, these approaches face scalability, latency, and reliability limitations as quantum networks grow. This paper proposes a multi-agent control plane architecture for quantum networks. In this design, intelligent software agents operate at quantum nodes, repeaters, and orchestration layers, collectively managing entanglement generation, routing, purification, and scheduling. The distributed intelligence of the agent system allows the network to adapt dynamically to quantum hardware variability and environmental noise. We argue that multi-agent systems provide significant advantages over centralized control approaches, including scalability, resilience, local autonomy, and real-time adaptation. The paper discusses architectural design principles, agent coordination mechanisms, and research challenges in deploying multi-agent control planes for the emerging quantum Internet.

Alnajjar, Anees [ORNL] (ORCID:0000000237101601)↗

DOE OSTI2020

Enhanced visible-light-assisted peroxymonosulfate activation on cobalt-doped mesoporous iron oxide for orange II degradation

Sulfate radical-based advanced oxidation processes (SR-AOP) attracted a lot of attention due to their capability and adaptability in wastewater treatment. Although heterogeneous cobalt-based catalysts have been extensively studied and have emerged superior for peroxymonosulfate (PMS) activation, leaching of cobalt is still a major concern. Herein, we report a photo-assisted PMS activation approach using cobalt doped mesoporous iron oxide with exceptional activity and stability up to 7 cycles with very low cobalt leaching (0.5 ppm). The highest activity was obtained by 1 mol % cobalt doped mesoporous iron oxide. Orange II dye was completely degraded by the reactive oxygen species (ROS) generated under visible light irradiation within 1 min. ROS were evaluated using two distinct techniques (Fluorescence probes and Electron Paramagnetic Resonance (EPR). ROS quenching experiments were also used to highlight the dominant pathway. This study correlates the structural and electronic changes induced with cobalt doping to the exceptional activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗