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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2024

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗
DOE OSTI2025

Test Results of the LQXFA/B02 and LQXFA/B03 Cryo-Assemblies for the High Luminosity LHC Upgrade

Here, the US High-Luminosity LHC Accelerator Upgrade Project (AUP) is responsible for delivering cryo-assemblies for the Q1/Q3 quadrupole optical components of the High Luminosity LHC upgrade at CERN. Total of 10 cryo-assemblies containing two Nb3Sn quadrupole magnets per cold mass will be delivered within this program. After the successful test of the first pre-series cryo-assembly in 2023, two more cryo-assemblies were tested at Fermilab's horizontal test facility. Production overview and the test results of the LQXFA/B02 and LQXFA/B03 cryo-assemblies are summarized in this paper. After the first test, to increase the capability of the horizontal test facility, various improvements have been made. These improvements are also described in this paper.

Chlachidze, Guram [Fermi National Accelerator Labo↗
DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗
DOE OSTI2024

Simulation of Particulate Transport for Delivery of Solid Amendments into the Subsurface: FY24 Status Report

For particulate-based amendments to be viable for field-scale remediation at the Hanford Site (e.g., 200 DV-1 Operable Unit), particles need to be delivered a sufficient radial distance from an injection well and retained at concentrations high enough for effective treatment. An accurate description of the particle radius of influence (ROI) is critical for developing an overall remediation strategy. However, field-scale particle simulations are currently limited due to insufficient simulation capabilities and a lack of experimental data to validate and parameterize particle transport models. To help build toward field-scale deployment, this fiscal year (FY) we have (1) developed a pre screening tool to estimate particle transport, (2) implemented particle transport models within PFLOTRAN, and (3) conducted preliminary estimations of particle ROI. While field-scale numerical simulations will ultimately be necessary before remedy design and field implementation, we have developed a pre-screening tool that offers valuable estimations of expected particle injectability and ROI in a 1-D system. The advantage of the tool is that it does not require extensive laboratory experiments and instead makes predictions based solely on routine laboratory measurements. This tool can assist in down-selection and decision-making by identifying which particle amendment systems are worth pursuing in future laboratory experiments, such as 1-D column tests and beyond. With any system, scaling up from the lab to the field presents challenges. Currently, there is no field data available for model calibration or validation. However, the theoretical particle models being developed herein are the best tools available to guide progress toward field deployment. To help bridge this gap and verify model predictions, larger-scale lab experiments are being proposed. To advance simulation capabilities, six particle transport models are being integrated into the reactive transport simulator PFLOTRAN. These include colloid filtration theory (CFT) and five additional particle transport models (M1-M5). Each model, from M1 to M5, progressively incorporates additional particle transport and retention processes. Ultimately, the simplest model capable of accurately describing 1-D column data will be selected and parameterized. During FY24, the CFT and M1 model have been fully implemented within PFLOTRAN. Using an existing 1 D column experiment, the two currently implemented particle transport models (CFT and M1), and associated parameters, were fit to this experiment. While simpler model formulations are helpful for estimations, these formulations could not fully describe particle transport and retention behavior in the previous 1-D column experiment. Thus, additional complexities will need to be considered, which will be accounted for in the M2-M5 model formulations. Additionally, because a viscous, shear thinning fluid was required to keep particles in suspension, considerations for flow will also need to also be accounted for. Therefore, a new immiscible two-phase flow mode is currently being implemented in PFLOTRAN. With some modifications, this new flow module could also support simulation of non-Newtonian liquid amendments, foams, and emulsions. We also estimated the expected ROI of solid amendments using 1-D simulations. The average predicted ROI was approximately 15 ft for micron-sized zero valent iron (mZVI) suspended in xanthan gum (XG). Using the pre screening tool and ROI estimates, additional amendment-delivery laboratory characterization and experiments are proposed. The results from additional experiments can be used to validate and parametrize particulate transport model formulations, which will ultimately provide predictive capabilities for field amendment-delivery systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Demonstration of a Novel Technology to Manage Electricity Demand in Grid-Independent Military Microgrids

This research was conducted by the National Renewable Energy Laboratory (NREL) in collaboration with the S&C Electric Inc. through funding provided by the ESTCP. The project demonstrates use of cybersecure Automated Demand Response (ADR) technology to effectively manage microgrid loads during grid-independent, also known as "islanded," operation. When military microgrids become isolated from the main electrical grid, they are required to balance electricity supply and demand locally. Given that local generation may be constrained, the prevailing strategy involves shedding all but the most critical loads by tripping smart circuit breakers, which then necessitate manual resetting. This approach is generally implemented at the building level, which means that the buildings with mission-critical activities are exempt from load management and remain fully powered, whereas those deemed non-critical can experience a complete loss of service. In this research we developed a method that allows building automation systems to selectively control their assets in response to load shedding request from a microgrid controller, avoiding total loss of service in contrast to the conventional control approach. A commercial OpenADR client server by GridFabric is used for communication between the microgrid controller and the building management system (BMS). The microgrid controller monitors both generation capacity and various assets within the microgrid and issues a demand reduction request when necessary. This request is communicated to the OpenADR server via Modbus. Upon receiving the request, the OpenADR server forwards it to the BMS utilizing the OpenADR protocol. The BMS is pre-configured with various levels of load reduction strategies based on the controllable assets available, allowing for a nuanced approach to demand reduction. Both lab and field tests were performed that considered load shedding needed to achieve closed transition into island mode and to accommodate changing loads and power source availability while islanded. A commercial microgrid controller was used for these tests with normal programming within the expected constraints of the system capabilities. That is, the solution did not require any specialized modification to the code base of the controller. Given the latency of the round-trip communication path between the microgrid controller and the various devices involved with the load shed processes, there are certain scenarios for which the demonstrated solution are appropriate and some which are not. The methods described in this report can be used for load shedding/restoration during transitions between islanded and grid-tied modes of operation, as well as accommodating normal variations in load and the need to remove a power source from operation for maintenance. These methods should not be used for scenarios that require load shedding within a second or two such as sudden and unanticipated significant load increases or loss of power sources through equipment faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Co-Simulation of PSS/E, OpenDSS, and PSCAD for Power Systems Stability Analysis With Inverter-Based Resources: Preprint

The increasing penetration of inverter-based resources (IBRs) is reshaping the dynamic behavior of power systems. IEEE standard 1547-2018 suggests that distributed energy resources (DERs) should provide grid services such as voltage and frequency supports. On the other hand, dynamic events caused by IBRs such as sub-synchronous oscillation have been reported. These developments necessitate improvement in the current modeling capabilities to better understand the interdependencies within power systems. These include interactions between transmission and distribution systems, among IBRs themselves, and between IBRs and conventional resources. In this paper, we present a co-simulation model integrating PSS/E, OpenDSS, and PSCAD to analyze IBR impacts on the stability of transmission and distribution systems. A key challenge in developing a co-simulation model is ensuring interoperability among different simulators (interfacing and data flow) while maintaining accurate results. Using the developed model, we simulate the impact of IBRs on power systems in two test cases: 1) fault ride through (FRT) capability during a generation trip contingency; 2) IBR-induced sub-synchronous oscillation. The results show the effectiveness of the co-simulation model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Concrete Thermal Energy Storage Enabling Flexible Operation without Coal Plant Cycling

The work described in this report is responsive to the Office of Fossil Energy program “Energy Storage for Fossil Power Generation.” The pilot plant built as a result of this project demonstrated the feasibility and performance of a concrete thermal energy storage (CTES) system integrated with a supercritical coal power plant. The 10 MWh electrical (>25 MWh thermal) CTES unit, developed by Storworks Power, was designed to enable flexible operation of coal plants without cycling damage. The project's key technical achievements showcase a significant advancement in energy storage technology. A modular CTES system using 42 “Bolderblocs” units was successfully designed and constructed at Alabama Power’s Plant Gaston Unit 5, with each block containing embedded stainless-steel coils in specialized, cost-effective high-temperature concrete. The system interfaced seamlessly with the plant's 3500 psig (241 barg), 1000°F (538°C) supercritical steam, demonstrating operational flexibility. Over 86 full cycles, the CTES exhibited rapid charging and discharging capabilities, effectively mimicking steam turbine feed conditions and handling varying load profiles and storage durations. Performance validation confirmed the system's ability to consistently meet design target steam conditions of 75 bar-a and ~400°C for nominal baseline discharge. The concrete material withstood repeated thermal cycling without degradation, validating earlier lab-scale tests. Integration of balance of plant components, including a condensate management system with storage tank and air-cooled condenser, minimized plant interfaces and water consumption. A robust control scheme ensured safe, automated operation across various scenarios. Key learnings from the project were invaluable: 1. Initial concrete drying and commissioning procedures were refined for future deployments, enhancing efficiency in subsequent installations. 2. System flexibility exceeded expectations, with rapid response to changing conditions. 3. Design improvements were identified including optimized insulation and piping that will enhance overall system efficiency in future deployments 4. Full cycle thermal roundtrip efficiencies exceeded 88%. While the roundtrip electrical efficiency was somewhat limited by known challenges using input steam, such constraints may be mitigated by swapping steam for hot air as thermal input. 5. A summary of key performance parameters for the pilot test and predicted performance of a full scale commercial system with specified improvements determined from the pilot are shown in Section 8. The project faced challenges, including COVID-19 delays and host plant availability constraints. However, these were overcome through adaptive planning and execution. The successful management of these obstacles demonstrated the resilience and adaptability of the project team and the robustness of the CTES technology. This successful pilot demonstrates the potential for CTES to enhance coal plant flexibility, supporting grid stability as renewable penetration increases. The validated design and operational data provide a solid foundation for scaling up to utility-scale implementations, potentially transforming how thermal plants operate in evolving energy landscapes. The system's ability to rapidly respond to changing grid conditions while maintaining high efficiency makes it a promising solution for balancing intermittent renewable energy sources. Furthermore, the project highlighted the potential for even greater efficiencies in future iterations. The use of air as an input medium could potentially eliminate the limitations observed with steam input, opening new possibilities for energy storage applications beyond coal plant integration. In conclusion, this pilot project not only achieved its primary goals but also uncovered additional benefits and potential applications of the CTES technology. It represents a significant step forward in addressing the challenges of grid stability and flexibility in an increasingly renewable-driven energy landscape.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Tunable Solid‐State Properties and Anisotropic Charge Mobility in Hydrogen‐Bonded Diketopyrrolopyrrole Polymers via Automated Device Fabrication and Characterization

The optoelectronic properties of semiconducting polymers and device performance rely on a delicate interplay of design and processing conditions. However, screening and optimizing the relationships between these parameters for reliably fabricating organic electronics can be an arduous task requiring significant time and resources. To overcome this challenge, Polybot is developed—a robotic platform within a self‐driving lab that can efficiently produce organic field‐effect transistors (OFETs) from various semiconducting polymers via high‐throughput blade coating deposition. Polybot not only handles the fabrication process but also can conduct characterization tests on the devices and autonomously analyze the data gathered, thus facilitating the rapid acquisition of data on a large scale. This work leverages the capabilities of this platform to investigate the fabrication of OFETs using hydrogen bonding‐containing semiconducting polymers. Through high‐throughput fabrication and characterization, various data trends are analyzed, and large extents of anisotropic charge mobility are observed in devices. The materials are thoroughly characterized to understand the role of processing conditions in solid state and electronic properties of these organic semiconductors. The findings demonstrate the effectiveness of automated fabrication and characterization platforms in uncovering novel structure–property relationships, facilitating refinement of rational chemical design, and processing conditions, ultimately leading to new semiconducting materials.

automated fabrication and characterization↗
DOE OSTI2026

Lab-Scale Cable-Driven Parallel Robot Prototype for Automated Prefabricated Component Manipulation

This paper presents the design and evaluation of a lab-scale cable-driven parallel robot (CDPR) developed as a flexible platform for automated installation of prefabricated components onto exterior building envelopes. Traditional manual installation methods for prefabricated components, which depend on scaffolding, cranes, cherry pickers, and verbal coordination, are not only labor-intensive and error-prone but also face significant limitations in dense urban environments due to site access constraints. To address these challenges, we developed a lab-scale CDPR platform capable of autonomously transporting building envelope components from a designated pickup zone to their target installation location, minimizing the need for human intervention. This study describes the system’s mechanical design, actuation architecture, real-time feedback system, and control strategy of the CDPR, and evaluates its performance in a laboratory environment. The robot’s actuation system uses torque control for end-effector manipulation. The robot’s real-time pose feedback comes from a construction-grade total station and a wireless inertial measurement unit (IMU), which together support precise end-effector control. Experimental results demonstrate the successful integration of the hardware, sensing, state estimation, and control subsystems. Preliminary tests showed that our lab-scale prototype can position the end effector with an error of less than 3 mm, which is a level of precision not previously achieved by existing CDPRs in construction applications. The key findings are twofold: (1) torque-only control is necessary but not sufficient for minimizing final pose error, and (2) incorporating real-time pose feedback can achieve the desired placement accuracy.

Liu, Yifang [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2024

Progress on the Autonomous Event Detection System For the Laser Particulate Counter

Field emission is one of the most important issues that limits the performance of the superconducting radio frequency (SRF) systems and leads to SRF cavity trips at the Continuous Electron Beam Accelerator Facility at Jefferson Lab. Studies have confirmed that particulates are the dominant source of field emitters and the particulates can be transported into a cavity from other parts of the accelerator. To monitor the transportation of the particulates, a prototype of a novel, non-invasive laser particulate counter (LPC) has been developed and tested. Experiments have been done to validate the capability of the LPC. We are developing autonomous event detection system to continuously monitor the readout from the LPC and to recognize real events generated by particulates from noises using machine learning model. In this report, we will present how the data are prepared and how the model is trained. We will also discuss the performance of the model.

Zhang, H.↗
DOE OSTI2024

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

NLR CSP Optical Facilities: Illuminating the Path Forward Through Innovation and Impact: Agreement 38490

This initiative is a multi-faceted project at the National Laboratory of the Rockies (NLR) aimed at strengthening its Concentrating Solar Power (CSP) Optical Facilities to advance the development of low-cost, high-performance materials for solar and other applications. The project's strategy is built on three pillars: strategic stakeholder engagement, diligent facility maintenance and utilization, and the development of new research capabilities. The overarching goal is to ensure the facilities remain state-of-the-art resources for industry and academia, thereby accelerating the conversion of concentrated sunlight into energy. A key driver of the project is an international Advisory Board, which provides critical guidance on research priorities and industry needs, leading to new collaborations and secured funding. This external engagement, combined with proactive outreach to industry partners, ensures the lab's work remains aligned with real-world challenges, including materials durability and performance certification. Significant efforts in facility maintenance have addressed challenges with aging infrastructure. Notable achievements include the complete refurbishment of the hail-damaged Ultra-Accelerated Weathering System (UAWS) and the successful replacement of a failing 15-year-old Lambda 1050 spectrophotometer with a new-generation model, substantially upgrading material characterization capabilities. These maintenance activities were complemented by achieving a prestigious ISO 9001:2015 certification for the Advanced Optical Materials Labs, formally recognizing the quality and reliability of NLR's measurement capabilities. Despite these successes, challenges remain, including high demand for the High Flux Solar Furnace (HFSF) and intermittent failures of other key instruments. The project has delivered major advancements in research techniques and capabilities. At the Flatirons campus, a new indoor laboratory, was established to house advanced deflectometry and photogrammetry systems for heliostat characterization. For on-sun testing, a novel, actively cooled turning mirror was developed for the HFSF, enabling more realistic testing of particle receivers and components. A collaboration with Virginia Tech successfully demonstrated the high-temperature durability of a new solar absorber coating through extensive cyclic testing. Concurrently, new modeling took place to better predict material degradation on rough, fractal surfaces. In summary, this project has systematically enhanced NLR's CSP Optical Facilities through strategic upgrades, rigorous maintenance, and stakeholder-guided research. By overcoming equipment failures, budgetary constraints, and logistical hurdles, the project has reinforced NLR's role as a central hub for CSP innovation and materials testing. Future work will focus on securing diverse funding, expanding collaborations, and continuing to provide the critical infrastructure needed to accelerate the development and deployment of next-generation technologies.

14 SOLAR ENERGY↗
DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗
DOE OSTI2025

Wide-field microwave magnetic field imaging with nitrogen-vacancy centers in diamond

Non-invasive imaging of microwave (MW) magnetic fields with microscale lateral resolution is pivotal for various applications, such as MW technologies and integrated circuit failure analysis. Diamond nitrogen-vacancy (NV) center magnetometry has emerged as an ideal tool, offering micrometer-scale resolution, millimeter-scale field of view, high sensitivity, and non-invasive imaging compatible with diverse samples. However, up until now, it has been predominantly used for imaging of static or low-frequency magnetic fields or, concerning MW field imaging, to directly characterize the same microwave device used to drive the NV spin transitions. In this work, we leverage an NV center ensemble in diamond for wide-field imaging of MW magnetic fields generated by a test device employing a differential measurement protocol. The microscope is equipped with a MW loop to induce Rabi oscillations between NV spin states, and the MW field from the device-under-test is measured through local deviations in the Rabi frequency. This differential protocol yields magnetic field maps of a 2.57 GHz MW field with a sensitivity of ∼9 μT Hz −1/2 for a total measurement duration of T=357 s, covering a 340 × 340 μm 2 field of view with a micrometer-scale spatial resolution and a device-under-test input power dynamic range of 30 dB. This work demonstrates a novel NV magnetometry protocol, based on differential Rabi frequency measurement, that extends NV wide-field imaging capabilities to imaging of weak MW magnetic fields that would be difficult to measure directly through standard NV Rabi magnetometry.

crystallographic defects↗
DOE OSTI2025

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗
DOE OSTI2025

Findings on subtask 3.3 – applicability of automated brine chemistry determinations for treatment and recovery processes through facility automation/modularization: engineering design study

Under the Energy & Environmental Research Center’s (EERC’s) ~$\$$22 million Phase II Brine Extraction and Storage Test (BEST) Program, a multimillion-dollar brine treatment technology test bed facility was established in western North Dakota to provide a platform for evaluating developing technologies and approaches for brine treatment and volume reduction. The initial facility, and associated research effort, was funded by the U.S. Department of Energy (DOE), with in-kind contributions provided by several industry participants and the state of North Dakota. Since its opening, the Brine Technology Test Facility (BTTF) has supported performance evaluations of desalination technologies capable of treating high-salinity produced water (PW) and enabled data collection for multiple approaches of PW management and critical material recovery. As part of the decommissioning process for the original project, facility ownership and liability were transferred to Select Water, which is providing the EERC with a continuing site access option for state or federal research and/or commercial technology development. This report documents the findings from a design study conducted by the EERC and the engineering firm that was originally contracted to design and construct the facility (Advanced Engineering and Environmental Services, LLC [AE2S]) that evaluated the current status of BTTF and its systems and developed a retrofit design to increase the facility’s capabilities through automation and modularization of its PW treatment infrastructure. The proposed retrofit will provide DOE and industry with an expanded range of conditioned PW that can be produced at the facility for evaluating fit-for-purpose water treatment technologies, online instrumentation for brine chemistry determination, and systems that recover critical materials like lithium and magnesium. The current facility consists of an 9600-square-foot facility that includes a 40-foot by 65-foot Class 1, Division 2-rated demonstration area and associated control rooms and lab-ready space capable of sourcing oil and gas PW and wastewater from industrial sources or tailoring brine compositions up to 300,000 mg/L total dissolved solids (TDS) and supplying them at rates up to 25 gpm for extended-duration technology demonstrations. The colocation of the facility with Select Water’s water management facilities allows for access and unloading of more than 10,000 bbl/day of trucked water delivered to site and associated access to on-site Class I and Class II brine disposal wells and nearby hazardous waste landfills operated and/or contracted by Select Water to dispose of concentrate and/or effluents associated with the testing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Development Status of the KIPM Detector Consortium

A kinetic inductance phonon-mediated detector is a calorimeter that uses kinetic inductance detectors (KIDs) to read out phonon signals from the device substrate. We have established a consortium comprising university and national lab groups dedicated to advancing the state of the art in these detectors, with the ultimate goal of designing a detector with sub-eV threshold on energy deposited in the substrate, enabling searches for both light dark matter and low-energy neutrino interactions. This consortium brings together experts in KID design, phonon and quasi-particle dynamics, and noise modeling, along with specialized fabrication facilities, test platforms, and unique calibration capabilities. Recently, our consortium has demonstrated a resolution on energy absorbed by the sensor of 2.1 eV, the current record for phonon-sensitive KIDs. However, due to ∼ 1% phonon collection efficiency, the overall detector resolution was limited to 320 eV. Finally, the current focus of the consortium is modeling and improving the phonon collection efficiency and implementing low-T c superconductors, both of which serve to improve the overall energy resolution and threshold of the detectors.

Temples, Dylan J. [Fermi National Accelerator Labo↗