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DOE OSTI2026

Pumped Thermal Energy Storage Using Low-Cost Particles and a Fluid Bed Heat Exchanger for Maximum Power Efficiency

Robust, efficient, cost-effective long-duration electricity storage (LDES) solutions can enhance grid resiliency, support existing transmission and distribution infrastructure, and enable a greater share of low-cost, variable alternative energy sources to penetrate the market. To meet this need, the project team at the National Renewable Energy Laboratory developed a transformative LDES system based on pumped thermal energy storage (TES) using low-cost particles and a fluid bed heat exchanger for maximum power efficiency (PUMP). The PUMP system is composed of high-temperature, low-cost particle TES coupled with an advanced pressurized fluid bed heat exchanger (PFB HX) that supports a high-efficiency pumped thermal energy storage (PTES) system integrated with concentrating solar thermal power (CSP). The PUMP project developed and de-risked a PFB HX and particle CSP system intended to be integrated with reversible turbomachinery and a modeling tool to assess PTES cost and performance.

14 SOLAR ENERGY↗

DOE OSTI2020

Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid

Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Workshop Report for Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications

Artificial intelligence (AI) promises powerful new capabilities in an expansive array of applications. One area is proliferation detection, where AI can provide transformative tools to achieve objectives currently inaccessible using conventional methods. In particular, AI affords the opportunity to use new indicators and process massive amounts of heterogeneous data that can increase sensitivity to proliferant activities and push proliferation detection to the earliest possible stages. However, existing AI tools are not ready to achieve such potential, falling short in regard to some important considerations involved in proliferation detection. One crucial aspect that requires improvement is the explainability of the most powerful AI algorithms (i.e., understanding how the algorithms actually arrive at their conclusions)-the lack of which prevents widespread adoption in national security missions. The Data Science and AI portfolio within the National Nuclear Security Administration's Office of Defense Nuclear Nonproliferation Research and Development is driving the development of next-generation AI for proliferation detection through the expertise and work of the national laboratories and partners in academia. The "Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications" workshop aimed to further this objective. The meeting was held virtually on Sept. 15-16, 2020 and included more than 170 participants, primarily from the national laboratories with additional contributions from university researchers and mission partners. Each day included a keynote presentation, four technical presentations about cutting-edge research in explainability, and a panel to explore considerations in applying explainability and developing AI systems that can accelerate the transition of emerging AI technologies among partners and end users to solve critical mission questions. This report summarizes the Next-Gen AI for Proliferation Detection workshop's content and findings.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2025

Evaluating switch lifetime in soft-switched single-stage differential-mode SST

The reliability of semiconductor switches in single-stage differential-mode solid-state transformers (DM-SSTs) has not been systematically evaluated under soft-switching operation and realistic grid conditions. This paper presents a switch-level reliability analysis for soft-switched and hard-switched DM-SST configurations by integrating converter-specific power loss modeling with empirical lifetime prediction. Analytical derivation of device current profiles specific to the DM-SST is used to characterize electrothermal stress, which is then mapped to lifetime using degradation models obtained from power cycling tests (PCTs). Applied to realistic SST load profiles and grid voltage variations, this approach provides a probabilistic prediction of switch lifetime for the DM-SST. Lifetime estimates for both SiC MOSFETs and Si IGBTs are presented, offering insight into device degradation under converter operating conditions. The results quantify the reliability benefits of soft switching in single-stage SSTs, highlighting how switching dynamics influence long-term switch degradation.

14 SOLAR ENERGY↗

DOE OSTI2024

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters

Smart inverters (SIs) have demonstrated their potential to provide grid services for both transmission and distribution systems. One of these grid services, distribution network voltage regulation by SIs, has the potential to improve network voltage regulation through controlling the reactive and active power output of the SIs. Voltage regulation by SIs will be distributed and might be better suited to controlling local conditions to complement traditional voltage-regulating assets, e.g., tap-changing transformers, capacitor banks, and line voltage regulators. There is a gap in the literature on comparing the SI response characteristics when the SIs are controlled by a local controller or external control signals. This paper presents an experimental study to characterize SI reactive power regulation responses to two different control methods: autonomous control and remote dispatch. We found that SI reactive power regulation responses exhibit important differences between these methods in terms of delays and ramp rate. Finally, power-hardware-in-the-loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL test results show that the SI response characteristics for autonomous control and remote dispatch need to be considered when planning for distribution network voltage regulation using SIs.

autonomous control↗

DOE OSTI2025

A grid-scale study of demand bidding by large industrial users

A demand bidding mechanism for engaging large industrial electricity users in the operation of the power grid is presented. Demand bidding is formulated as an optimization problem based on a modified version of the alternating current optimal power flow problem, and can be interpreted as a tâtonnement process between the grid operator and electricity users. Here, the work provides the first – to the authors’ knowledge – grid-scale case study of demand bidding, using a synthetic grid structure in the footprint of the grid of Texas. Results reveal that the demand bidding lowers overall power generation costs, but economic benefits plateau as the number of participants increases. Transmission line and transformer capacity constraints become the limiting factors, revealing that expanding and fortifying the transmission infrastructure is key to expanding demand-side participation. Demand bidding does not substantially alter the optimal operation of existing bidding entities when the number of bidders increases, thereby supporting existing bidders to stay in the system and encouraging new ones to join.

Chlor-alkali plant↗

DOE OSTI2026

A Unified Off-Board Charger for Three-Phase Inductive and Single-Phase Conductive EV Charging

This paper presents a unified off-board charger integrating a three-phase inductive power transfer (IPT) system and a single-phase conductive (plug-in) charger for electric vehicles (EVs). The proposed charger shares a high-frequency inverter and an integrated magnetic structure that enables three operating modes: conductive charging, inductive charging, and simultaneous charging. The transmitter coils for the three-phase IPT and the high-frequency transformer windings for the conductive charger are arranged on a common ferrite pad while maintaining magnetic decoupling between the two power transfer paths. The proposed unified architecture effectively increases charger utilization and power density without a proportional increase in cost, weight, or volume. Finite-element analysis using Ansys Maxwell confirms negligible coupling between the inductive and conductive coils, and the extracted parameters are employed in PLECS simulations to verify the independent operation of each charging mode.

Jo, Cheolhui [ORNL] (ORCID:0000000322692434)↗

DOE OSTI2023

Time‐Lapse Image Classification Using a Diffractive Neural Network

Diffractive deep neural networks (D 2 NNs), comprised of spatially engineered passive surfaces, collectively process optical input information at the speed of light propagation through a thin diffractive volume, without any external computing power. Diffractive networks were demonstrated to achieve all‐optical object classification and perform universal linear transformations. Herein, a “time‐lapse” image classification scheme using a diffractive network is demonstrated for the first time, significantly advancing its classification accuracy and generalization performance on complex input objects by using the lateral movements of the input objects and/or the diffractive network, relative to each other. In a different context, such relative movements of the objects and/or the camera are routinely being used for image super‐resolution applications; inspired by their success, a time‐lapse diffractive network is designed to benefit from the complementary information content created by controlled or random lateral shifts. The design space and performance limits of time‐lapse diffractive networks are numerically explored, revealing a blind testing accuracy of 62.03% on the optical classification of objects from the CIFAR‐10 dataset. This constitutes the highest inference accuracy achieved so far using a single diffractive network on the CIFAR‐10 dataset. Time‐lapse diffractive networks will be broadly useful for the spatiotemporal analysis of input signals using all‐optical processors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Mössbauer Spectroscopy Investigation of Nickel‐Zinc Ferrites Synthesized by a Self‐Combustion Method for Soft Magnetic Core Applications

Soft ferrites are materials of interest for magnetic cores, as used for wireless charging transformers. Their low permeabilities, high resistivity, and magnetic polarization make them interesting for high-power electric vehicle charging and drive systems. The nickel-zinc-doped ferrites are of particular interest; however, the compositional space is quite large with respect to dopant concentrations, stoichiometric ratios and synthesis technique. Nickel-zinc spinel ferrites with varying nickel-zinc ratios prepared by a self-combustion reaction followed by heat treatment exhibit good crystallinity, and their low-temperature Mössbauer spectra show local magnetism and site occupation in agreement with materials prepared by solid-state reaction. Thus, the combustion synthesis method offers a facile tunability of compositions, which, combined with the possibility of rapid characterization of atomic-scale magnetism by Mössbauer spectroscopy, enables advances in the compositional and processing space at a fast pace. Low-temperature Mössbauer spectroscopy data for samples with increasing nickel content reveals a systematic increase in average hyperfine field (2.8 T/Ni) and decrease in average isomer shift (−0.036 mm/s/Ni) that can determine the nickel/zinc content, even in the absence of applied magnetic field data. Furthermore, a gradual evolution of color is also observed with increasing nickel content, albeit trends in color depend on sintering conditions.

Mössbauer spectroscopy↗

DOE OSTI2020

High Resolution Data Analysis: Plans and Prospects [Book Chapter]

Herein, a report on the progress on the high resolution data analysis of the ADMX experimental results is presented. In this paper, tools are developed and tested on a blind injection mimicking a Maxwellian like signal in the frequency domain. This blind injection will be used as a test bed which can be later implemented on all the high resolution data. The high resolution data is stored in the Fermilab server. In this analysis a PostgreSQL query was made to ensure the blind injection is in the middle of the frequency spectrum and 19 such files were found. The time series data is read using a c++ program. An apodization function is applied on the time series data and zero filled to reduce the frequency spacing in order to achieve a better interpolation. A FFTW header is used to compute the Fourier transform of the time series data. A Savitzky–Golay filter is applied on the unnormalized power which then can be used to remove the spectral shape. Each frequency spectrum has a bandwidth of 50 kHz.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Radicals as Exceptional Electron-Withdrawing Groups: Nucleophilic Aromatic Substitution of Halophenols Via Homolysis-Enabled Electronic Activation

While heteroatom-centered radicals are understood to be highly electrophilic, their ability to serve as transient electron-withdrawing groups and facilitate polar reactions at distal sites has not been extensively developed. Here, we report a new strategy for the electronic activation of halophenols, wherein generation of a phenoxyl radical via formal homolysis of the aryl O-H bond enables direct nucleophilic aromatic substitution of the halide with carboxylate nucleophiles under mild conditions. Pulse radiolysis and transient absorption studies reveal that the neutral oxygen radical (O • ) is indeed an extraor-dinarily strong electron-withdrawing group [σ p - (O • ) = 2.79 vs. σ p - (NO 2 ) = 1.27]. Additional mechanistic and computational studies indicate that the key phenoxyl intermediate serves as an open-shell electron-withdrawing group in these reactions, lowering the barrier for nucleophilic substitution by more than 20 kcal/mol relative to the closed-shell phenol form of the substrate. Finally, by using radicals as transient activating groups, this homolysis-enabled electronic activation strategy provides a powerful platform to expand the scope of nucleophile-electrophile couplings and enable previously challenging transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Photonic integration for UV to IR applications

Photonic integration opens the potential to reduce size, power, and cost of applications normally relegated to table- and rack-sized systems. Today, a wide range of precision, high-end, ultra-sensitive, communication and computation, and measurement and scientific applications, including atomic clocks, quantum communications, processing, and high resolution spectroscopy, are ready to make the leap from the lab to the chip. However, many of these applications operate at wavelengths not accessible to the silicon on insulator-based silicon photonics integration platform due to absorption, power handling, unwanted nonlinearities, and other factors. Next generation photonic integration will require ultra-wideband photonic circuit platforms that scale from the ultraviolet to the infrared and that offer a rich set of linear and nonlinear circuit functions as well as low loss and high power handling capabilities. This article provides an assessment of the field in ultra-wideband photonic waveguides to bring power efficient, ultra-high performance systems to the chip-scale and enable compact transformative precision measurement, signal processing, computation, and communication techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Development of local-power-free, remote α -particle detection using optical fibers

We demonstrate the application of fluorescence optical fiber coupled to a telecom grade fiber as a sensor for alpha particles using alpha-specific ZnS(Ag) scintillation materials whose wavelength is down-shifted into a low-loss region of the telecom grade fiber transmission band. Telecom-grade fiber optics offer a solution for sensing alpha radiation in deep repositories and cask storage for radioactive materials due to the stability of SiO 2 under normal environmental conditions and its relative radiation hardness at low radiation doses. Long-term nuclear waste storage facilities require sensors for the detection of leakage of radioactive materials that are maintenance-free, do not require power and can survive with no ‘wear out’ mechanisms for decades. By accomplishing the wavelength transformation, we maximize efficiencies in the detection of α-particles and signal transport and can detect alpha scintillation at distances on the order of >1 km with a sensor that is ~3% efficient and can be easily scaled as a sensor array. This paper describes the construction and testing of the sensor including manufacture of the controlled thickness films, verification of the wavelength shift from 450 to 620 nm and optimization of the sensitivity as a function of thickness. We also model the relative sensitivity of the film as a function of film thickness, and we demonstrate a signal-to-noise ratio of 10 at a range of greater than 1 km.

alpha particles↗

DOE OSTI2023

A Power Application Developer’s Guide to the Common Information Model: An Introduction for Power Systems Engineers and Application Developers – CIM17v40

A key issue in creating the next generation of energy management system (EMS) and advanced distribution management system (ADMS) platforms will be the ability to represent and exchange power system network model data in a consistent manner. To this end, the Common Information Model (CIM) stands out as the only standardized vocabulary (or ontology) for defining power system network models and asset data in a comprehensive, consistent manner across the generation-transmission-distribution boundary. The CIM is freely available to use and extend. The CIM is maintained by the UCAiug (informally known as the CIM User’s Group) under an Apache 2.0 license. The CIM Users Group collaborates with the IEC and other standards communities for the development of technical and informative specifications. Although portions of the information model are referred to by the corresponding IEC standards naming, it is not necessary to purchase any of the IEC standards to use the CIM information model. This document provides a roadmap for power system engineers and application developers not familiar with semantic modeling to start using the CIM for modeling, simulation, optimization, and development of advanced power applications. The key classes needed for defining power system topology and equipment are explained systematically. Key focus areas include modeling of lines, transformers, generators, switching equipment, loads, and distributed energy resources (DERs).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

DOE Challenges and Opportunities Associated with Accountable Nuclear Material Needs for Development and Commercialization of Fusion Nuclear Energy

Fusion energy represents a transformative opportunity to deliver a safe, plentiful, and carbon-free source of reliable primary power. In recent years, fusion research and development have accelerated significantly, particularly within the US, driven by decades of foundational public investment. Notably, in 2024 the US Department of Energy (DOE) established a comprehensive Fusion Energy Strategy aimed at collaborating with industry partners to enable the deployment of fusion power plants and grid integration by the 2030s. This strategy is chiefly implemented through the DOE Office of Science (SC) Fusion Energy Sciences program. This project was initiated to identify potential approaches for the Office of Environment, Safety, and Health (NA-ESH-12) within DOE’s National Nuclear Security Administration to begin engagement with the fusion community on future accountable material needs. The goal of the project is to inform and influence the supply of and demand for accountable nuclear materials as fusion energy is developed and commercialized. NA-ESH-12 must proactively engage with the fusion community regarding the production and management of accountable nuclear materials. Given the complexity and scale of materials required for research, pilot projects, and eventual commercial reactors, early coordination is vital. The project’s objective is to provide insights that will shape the supply and demand landscape for critical nuclear materials, ensuring that DOE is prepared to effectively support fusion energy development and commercialization. In FY 2025, an initial limited review was conducted to identify the status of the fusion energy community’s progress toward full-scale energy production and the need for accountable nuclear material. This included communications with SC, NA-ESH-12, Savannah River National Laboratory, and Oak Ridge National Laboratory, and attending the Rutgers University–sponsored Supply Chain Workshop: Scaling the Fusion Industry and the International Atomic Energy Agency’s Ninth DEMO Programme Workshop. The review to date indicates that the amounts of tritium, lithium-6, and deuterium required by the fusion industry will be dependent on fuel type, breeding technology, blankets, and R&D improvements. One concern is that the commercial sector does not have a sufficient supply chain to meet the demand for development and commercialization for fusion energy production. The supply and demand estimates for these materials should be routinely reviewed as fusion technologies mature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

UltraSep Acoustic Separation Platform

UltraSep is an intelligent ultrasonic separation platform that transforms solid–liquid separation through real-time eigenfrequency resonance locking and ultra-low power energy optimization. By dynamically matching ultrasonic output to system resonance while maximizing particulate removal per unit of applied energy, UltraSep replaces centrifugation and fouling-prone filtration with precision-controlled acoustic forces that significantly reduce power consumption, mechanical complexity, and operating cost while improving recovery performance. This integrated platform unites patented resonance-based acoustic control and energy-per-removal optimization with chemistry-enhanced separation and proprietary system software into a scalable, high-impact commercial technology.

42 ENGINEERING↗

DOE OSTI2022

Oxidation of Dissolved Tetravalent Selenium by Birnessite: Se Isotope Fractionation and the Effects of pH and Birnessite Structure

Redox reactions control the mobility and bioavailability of selenium (Se) in biogeochemical systems, both modern and ancient. Se isotope ratio measurements (e.g., 82 Se/ 76 Se) have been developed to enhance understanding of biogeochemical transformations and transport of Se. Stable isotope ratios of many elements are known to be powerful indicators of redox reactions, and shifts in 82 Se/ 76 Se have been observed for Se reduction reactions. However, Se isotope shifts caused by naturally relevant oxidation reactions have not been published. Here, we report Se isotope fractionation factors for oxidation of Se(IV) by birnessite. Experiments were conducted at pH = 4.0 and 5.5, with two types of birnessite of contrasting composition at two concentrations of suspended birnessite. The results are consistent with a single 82 Se/ 76 Se fractionation factor, for all times during all experiments, of 0.99767 (±0.0035 2 s.d.). Expressed as ε, the fractionation is 2.33‰ (±0.08‰).

58 GEOSCIENCES↗

DOE OSTI2023

Fabrication and characterization of net-shaped iron nitride-amine-epoxy soft magnetic composites

Soft magnetic composites (SMCs) offer a promising alternative to electrical steels and soft ferrites in high performance motors and power electronics. They are ideal for incorporation into passive electronic components such as inductors and transformers, which require a non-permanent magnetic core to rapidly switch magnetization. As a result, there is a need for materials with the right combination of low coercivity, low magnetic remanence, high relative permeability, and high saturation magnetization to achieve these goals. Iron nitride is an attractive soft magnetic material for incorporation into an amine/epoxy resin matrix. This permits the synthesis of net-shaped SMCs using a “bottom-up” approach for overcoming the limitations of current state-of-the-art SMCs made via conventional powder metal processing techniques. In this work we present the fabrication of various net-shaped, iron nitride-based SMCs using two different amine/epoxy resin systems and their magnetic characterization. The maximum volume loading of iron nitride reached was ~77% via hot pressing, which produced SMCs with a saturation magnetic polarization (J s ) of ~0.9 T, roughly 2–3 times the J s of soft ferrites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗