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DOE OSTI2024

Addressing Failures in Molten Salt Thermal Energy Storage Tank for Central Receiver Concentrating Solar Power Plants

The thermal energy storage (TES) system is a critical component in concentrated solar power (CSP) plants that increases the plant's capacity factor and economic competitiveness by reducing the levelized cost of energy (LCOE) while simultaneously increasing the value of the delivered energy. Failures including molten-salt leaks and diverse localized cracking after several months to a few years of operation have been reported in hot tanks for CSP plants operating around the world. A model of a molten salt thermal energy storage tank was developed and validated to analyze the impact of different tank design features on the temperature and stress distributions as a function of typical plant operation conditions. Design features included the floor plate thicknesses, friction coefficients between the tank floor and the foundation, and the sparger ring location. Maximum stresses in the tank floor frequently surpassed the yield point of the material during operation, leading to a detriment of the tank's lifetime. Recommendations on design features to improve the reliability of new molten salt tanks for CSP plants are provided.

concentrating solar power↗

DOE OSTI2024

Leveraging NREL's ResStock & ComStock Dataset to Evaluate Building Stock Electrification: Preprint

Residential and commercial buildings accounted for 40% of U.S. energy consumption in 2022 and represent a significant opportunity for decarbonization through energy efficiency and electrification, and for grid planning. Building stock energy modeling is a powerful tool that can evaluate what-if scenarios as utilities, municipalities, policymakers, building owners and others work towards equitable building decarbonization and climate goals. This presentation will highlight several high-impact use cases of the National Renewable Energy Laboratory (NREL)'s highly granular, bottom-up building stock energy modeling tools, ResStock and ComStock. These use cases cover a wide range of project scale, from neighborhood electrification analysis and municipality long-term energy planning, to state energy code development and national policy evaluation. This presentation will showcase specific real-world applications for which ResStock and ComStock have been utilized across the country, including California codes and standards cost-effectiveness analysis, New York City affordable housing electrification cost gap analysis, and California targeted electrification and gas decommissioning analysis. For each use case, this presentation will illustrate how ResStock and ComStock played a crucial role in accurately characterizing regional building stocks, providing discrete and aggregated end-use load shapes, and calculating lifecycle consumption, emissions, and costs for a variety of building electrification strategies and scenarios. Finally, this presentation will demonstrate how the data provided by ResStock and ComStock can help unlock significant outcomes for these use cases, including but not limited to, customer bill impact, incentive and program design, and energy equity analyses.

building stock modeling↗

DOE OSTI2026

Artificial Intelligence Research at Fermilab

The unique challenges of high-energy physics research present opportunities for advancing AI technologies. From the principles of fundamental physics underlying massive and rich data sets to building and operating some of the world’s most complex detector and accelerator systems, the technologies we are developing have potential connections to a broad domain of cutting-edge AI research.

Fermilab, Fermilab↗

DOE OSTI2026

Optimization-based approaches to control of connected and automated vehicles: Principles, complexities, applications, challenges, and outlook

Safe and optimal motion control for connected and automated vehicles (CAVs) poses a fundamental optimization challenge at the intersection of system complexity, environmental uncertainty, and stringent real-time constraints. Existing surveys address this challenge in isolation – focusing either on specific control techniques or individual uncertainty sources – without providing a unified framework that characterizes the trade-offs among computational tractability, performance verifiability, and adaptive generalization across paradigms. This review addresses that gap by presenting a cohesive analytical framework concentrated on the decision-making and trajectory optimization layers of the CAV autonomy stack. We systematically analyze three major optimization paradigms – first-principles model-based optimization, data-driven methods, and hybrid synergistic architectures – evaluating each against four core complexity axes: problem formulation, constraint handling, optimality guarantees, and robustness. Key applications including platooning, trajectory planning, collision avoidance, and cooperative control are examined to reveal recurring methodological patterns and critical operational constraints that limit real-world performance. Our synthesis identifies verifiable hybrid architectures, incentive-aligned multi-agent cooperation, and hardware-algorithm co-design as the defining research frontiers, and distills a targeted agenda for developing CAV control systems that are simultaneously safe, computationally efficient, and deployable in the full complexity of real-world traffic environments.

Muzahid, Abu Jafar Md [University of Tennessee, Kn↗

DOE OSTI2020

Conventional and Next Generation Treatment Technologies for PFAS - 20067

In 2016, the United States Environmental Protection Agency (USEPA) established a Health Advisory Limit (HAL) for perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) (individually and the summation) of 70 nanograms per liter (ng/L) based on developing toxicological information. These two compounds are among several thousand per- and polyfluoroalkyl substances (PFAS). Due to a multitude of commercially beneficial physical and chemical properties, the availability of PFAS-relevant and practical water treatment technologies is limited. The use of conventional adsorbents, such as activated carbon (AC) and anion exchange (AIX) resins, have become a 'de facto' interim measure to immediately address drinking water above this criterion. However, these adsorbents can have marginal long-term efficiency and are relatively unproven against the diversity of polyfluorinated compounds. Additionally, geochemical and/or co-contaminant competition can significantly impede adsorption based PFAS removal. These challenges may be addressed using engineered filtration, such as reverse osmosis or nanofiltration (RO/NF); however, for larger flow systems RO/NF may have unacceptable reject ratios as high as 35% and the capital cost may preclude these technologies. Extending these technologies to natural waters, which have various degrees of geochemical and co-contaminant competition, often requires a treatment train, combining conventional adsorbents or engineered filtration with pretreatment and more innovative and emerging remediation solutions for PFAS. Conventional and Next Generation water treatment technologies for PFAS generally employ one of three mechanisms (adsorption, separation, or destruction). These mechanisms include many types of technologies for both municipal drinking water and extracted natural water applications. The previously mentioned AC, AIX, and RO/NF are commercially available technologies that are actively being deployed for PFAS treatment. Research and development around these technologies is focused on optimization, and ultimate destruction of PFAS is achieved through incineration. Next Generation water treatment technologies include PFAS-specific flocculants, foam fractionation, novel AIX resins, new engineered adsorptive media, electrochemical treatment, sonolysis, and photolysis, radiation, and plasma (forms of advanced reductive processes [ARP]). Research and development around these technologies is focused on proof of concept and assimilation to real world applications. As the PFAS-relevant destructive technologies (such as incineration, electrochemical treatment, sonolysis, and ARP) are energy intensive, the state of the practice for PFAS water treatment is to focus adsorption/separation based technologies on reducing and concentrating the volume of water requiring destructive treatment. This enables more flexibility with respect to circulation frequency, residence time, and more control over energy usage. Water treatment for PFAS presently requires multiple technologies (i.e. a treatment train) to protect human health in a cost-conscious manner. An investment in research and development to explore new technologies is part of a key initiative for efficient protection of human health. This presentation attempts to review PFAS-relevant water treatment technologies and provide perspective as to their status with respect to applicability and commercial relevance. (authors)

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗

DOE OSTI2020

2020 State of the Science Report, Chapter 1: Marine Renewable Energy and Ocean Energy System

Research, development, and deployment of marine renewable energy (MRE) conversion technologies that harvest all forms of ocean renewable resources are being advanced around the world. The potential benefits derived from capturing the abundant energy of tides, waves, ocean currents, as well as thermal and salinity gradients, continue to drive the development of the emerging MRE industry. Stakeholder understanding of the potential benefits of MRE as a renewable energy source is informed by increased science-based understanding of the potential effects of MRE installations worldwide. The international Ocean Energy Systems (OES)-Environmental collaboration continues to promote global technology cooperation and information exchange to accelerate environmentally acceptable development of viable ocean energy systems. https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-1-MRE-OES

13 HYDRO ENERGY↗

DOE OSTI2021

Materials and Fuels Complex Five-Year Mission Strategy (FY21- FY25)

The Idaho National Laboratory (INL), through its designated mission of advancing innovative nuclear energy solutions, is actively engaged in the research, development, demonstration and deployment of advanced nuclear technology, as well as in fostering private-public partnership for technology development. Key to the success of INL’s mission is the Materials and Fuels Complex (MFC), the only complex in the U.S. that hosts a world-class assemblage of facilities, capabilities and instruments for handling, testing, and characterizing radioactive materials. Driven by its mission/vision of “Engineering and Experiments that Drive the World’s Nuclear Energy Future,” MFC is at the center of INL’s – and indeed the Department of Energy’s – advanced nuclear technology development initiatives, providing essential capabilities such as engineering-scale high-assay low-enriched uranium (HALEU) fuel production, reactor demonstration facilities, post-irradiation examination, and transient irradiation testing. Furthermore, MFC provides an ideal environment for test beds that are utilized for research, development and demonstration (RD&D) activities on used fuel treatment, nuclear non-proliferation, forensics, and nuclear power sources used for space exploration missions conducted by the National Aeronautics and Space Administration (NASA).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Materials and Fuels Complex (FY2021-2025 Five-Year Mission Strategy)

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

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

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

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Parametric Study of SANSMIC Input and Resulting Impact on Predicted Cavern Geometry and Leaching Efficiency

The Sandia Solution Mining Code (SANSMIC) has been used for many years to examine the development of salt cavern geometry, both in a confirmatory manner with comparisons made to real-world sonar data and in a predictive manner when updated sonar data are not available. SANSMIC models require some modeling choices in order to incorporate real-world data. Key modeling choices include the vertical resolution of cavern geometry to implement, as well as how to incorporate daily raw water injection data into the SANSMIC model. This report documents five studies that address the impact of the modeling choices on the predicted cavern geometries and calculated leaching efficiencies. In most cases, hypothetical cylindrical initial cavern geometries are used to provide a common baseline against which to test the systematic variation of input variables including cavern radius, oil-brine-interface (OBI) depth, vertical cell size, raw water injection rate, raw water injection duration, workover time, and number of leaching stages. The use of smaller cell sizes is recommended moving forward to provide a better one-to-one relationship between sonar data and the modeled cavern. A new methodology for incorporating raw water injection data is also recommended, in order to more closely model real-world injection and workover times. Overall, the systematic studies performed here have increased our confidence in previous SANSMIC model results, as well future use of the code for predicting leaching effects on cavern geometries. Some minor changes to modeling choices are recommended, which can easily be applied with the version of SANSMIC currently under development.

42 ENGINEERING↗

DOE OSTI2020

Machine Learning for Synchrophasor Analysis

The report presents results from the development of a cloud-based, Big Data analysis framework for power systems. The computational pipeline uses the Apache Spark framework running in an OpenStack cloud infrastructure. A real-world phasor measurement unit (PMU) dataset has been used to carry out the analysis. Several Machine Learning (ML) methods have been developed and implemented for event and anomaly detection and classification. Actual examples of power system events detection and analysis using synchrophasor data are presented. It has been shown that applications of the cloud-based computing environment and the Apache Spark framework enable a significant increase in the computational efficiency of large-scale PMU data analysis.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Integral Nuclear Data and Benchmarking Needs for Fusion Energy Systems

Fusion energy systems are currently being designed and optimized using radiation transport codes. To deal with the unique environment inside a fusion-based system, many of these designs incorporate novel materials able to withstand the high radiation fields, ensure adequate cooling and thermal protection, and produce tritium. Validation plays a vital role in building trust in the predictive power of these models and computational methods. Validation of a code consists of modeling documented real-world experiments and comparing the code-predicted response to the measured response. Adequate validation requires measured responses from real-world experiments, also known as integral data, that mimic the system being designed, including materials, impinging radiation, and temperature, among other variables. The most trusted integral data are experimental responses that have been through a rigorous benchmarking process that develops a recommended computational model and evaluates all experimental uncertainties. Finally, there are a few research groups around the world that have been producing integral data for fusion applications, but a substantial investment is needed to address the unique validation needs of the fusion community.

Fusion↗

DOE OSTI2023

Development of the Safe and Broad‐Spectrum Aldehyde and Ketoamide Mpro inhibitors Derived from the Constrained α, γ‐AA Peptide Scaffold

Abstract SARS‐CoV‐2 is still wreaking havoc all over the world with surging morbidity and high mortality. The main protease (M pro ) is essential in the replication of SARS‐CoV‐2, enabling itself an active target for antiviral development. Herein, we reported the design and synthesis of a new class of peptidomimetics‐constrained α, γ‐AA peptides, based on which a series of aldehyde and ketoamide inhibitors of the M pro of SARS‐CoV‐2 were prepared. The lead compounds showed excellent inhibitory activity in the FRET‐based M pro enzymatic assay not only for the M pro of SARS‐CoV‐2 but also for SARS‐CoV and MERS‐CoV, along with HCoVs like HCoV‐OC43, HCoV‐229E, HCoV‐NL63 and HKU1. The X‐ray crystallographic results demonstrated that our compounds form a covalent bond with the catalytic Cys145. They also demonstrated effective antiviral activity against live SARS‐CoV‐2. Overall, the results suggest that α, γ‐AA peptide could be a promising molecular scaffold in designing novel M pro inhibitors of SARS‐CoV‐2 and other coronaviruses.

Chemistry↗

DOE OSTI2020

A Scintillating Xenon Bubble Chamber for Dark Matter Detection. Final Report

This report describes the progress in the search for particle dark matter achieved under DOE award DE-SC0012161, as well as the invention of a new dark matter and neutrino detection technique. Work supported by this award follows in three distinct thrusts: (1) the successful completion of the Generation-1 Direct Detection experiment PICO-60, which set the world-leading limit on the spin-dependent coupling of dark matter to protons and achieved a precise understanding of the response of bubble chambers to nuclear-recoil signals and electron-recoil backgrounds; (2) the construction of the Generation-2 Direct Detection experiment LZ, which will soon be the world's most sensitive dark matter detector; and (3) the demonstration of the first scintillating bubble chamber. The development of a scintillating liquid noble bubble chamber was the primary goal of the proposed work, with the aim of combining the excellent background rejection of a PICO-style bubble chamber with the event-by-event energy resolution of a liquid-noble detector such as LZ. This work produced the first ever observation of coincident scintillation and bubble nucleation by a nuclear recoil in a superheated fluid and also revealed an unexpected benefit to the use of noble liquids in a bubble chamber, namely the ability to increase the degree of superheat by an order of magnitude beyond that achievable in PICO-style detectors while maintaining PICO's world-leading background rejection. This discovery has led to new projects in the US and Canada, developing noble liquid bubble chambers both as detectors for low-mass dark matter and as detectors of coherent elastic neutrino-nucleus scattering (CEvNS) by neutrinos produced at nuclear reactors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data

Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real -world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi -physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle's Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time -resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively.

Lopez-Juarez, Marcos↗

DOE OSTI2026

Development of Post-Consumer Textile Waste Degradation Protocol and Related Downstream Transformations: Cooperative Research and Development (Final Report)

Tereform, Inc. (Tereform) is developing molecular deconstruction processes to transform waste materials into chemical building blocks. During the CRADA, Tereform deconstructed real-world post-consumer substrates into chemical monomers, validated their performance on laboratory scales, demonstrated feasibility of the degradation products in downstream transformations, and successfully scaled the reaction to kilogram-scale. These results were used to develop and refine technoeconomic analysis and lifecycle assessments to evaluate the economic feasibility and environmental impacts of the process.

36 MATERIALS SCIENCE↗