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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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At least 181 records · Page 10

Hydropower Supply Chain Gap Analysis

In 2022, DOE conducted supply chain "deep dives" for renewable energy technologies, including hydropower (Uria-Martinez, Hydropower Industry Supply Chain Deep Dive Assessment 2022). The deep dive identified several challenges in the current hydropower supply chain. In addition, Nguyen et. al (2022) conducted an analogous deep-dive assessment on large (> 100-MW) power transformers (LPTs), a critical component of hydropower installations, and concluded that the LPTs as well as several upstream components and materials also have domestic supply chain challenges. These deep dives were the initial high-level assessments of these supply chains and were focused on identifying the biggest issues. Both recommended further investigation. In the two years since the deep dives were published, the Water Power Technologies Office (WPTO) has focused on improving our understanding of the hydropower supply chain and developing strategies for addressing these challenges. Because the challenges outlined above are most acute for large hydropower systems, most of the report and specifically, this report concentrates on the larger > 100-MW hydropower systems. Early in 2023, DOE's Secretary of Energy asked the Water Power Technologies Office (WPTO) to engage the hydropower community and seek input on strategies to secure and encourage domestic manufacturing. WPTO has established three focus areas for engagement: 1) Define the market for planned rehabilitations and new construction of the domestic fleet, 2) Provide insights for policies, incentives, loan programs, and technology investments to encourage domestic content, and 3) Define the existing and required domestic hydropower manufacturing capabilities and workforce. This report summarizes these efforts and complements the earlier work by further exploring the identified challenges and identifying potential actions to address these challenges. Furthermore, we conducted a detailed gap analysis of the domestic hydropower supply chain, down to the component level. From this analysis, we then make specific, actionable recommendations for closing these gaps. Section 2 of the report summarizes recent (i.e., since 2021) legislation impacting hydropower deployment and/or its supply chain. It then describes the efforts of WPTO to assess and improve the hydropower supply chain since the publication of the deep-dive assessments. In Section 3, the report updates the earlier supply chain and market studies, identifying specific capabilities by company and location. Section 4 outlines the hydropower demand signal for both new builds due to clean energy goals as well as refurbishments and upgrading of the current domestic fleet. Section 5 is a detailed gap analysis while Section 6 provides actionable recommendations for closing the gaps. Section 7 concludes the report by linking the recommendations to the identified gaps and discusses future efforts.

13 HYDRO ENERGY↗

Electric Drive Technologies Research: ELT223 Component Modeling, Co-Optimization, and Trade-Space Evaluation Annual Report

This project is intended to support the development of new traction drive systems that meet the targets of 100 kW/L for power electronics and 50 kW/L for electric machines with reliable operation to 300,000 miles. To meet these goals, new designs must be identified that make use of state-of-the-art and next-generation electronic materials and design methods. Designs must exploit synergies between components, for example converters designed for high-frequency switching using wide band gap (WBG) devices and ceramic capacitors. This project included: (1) a survey of available technologies; (2) investigating new technologies, that for example, reduce volume of thermal management or magnetic components; (3) the development of computer aided design tools that consider the converter volume, reliability, and electrical performance; (4) exercising the design software to evaluate performance gaps and predict the impact of certain technologies and design approaches, i.e. GaN semiconductors, ceramic capacitors, ceramic thermal management components, and select topologies; (5) building and testing hardware prototypes to validate models and concepts. The design tools enable co-optimization of the power module and passive elements and provide some design guidance. At the end of the project, new advanced computing methods, such as machine learning approaches, were considered.

33 ADVANCED PROPULSION SYSTEMS↗

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗

Advances in high-pressure and high-temperature heat exchangers: Innovations via additive manufacturing and their applications

This paper provides a comprehensive overview of technological developments and applications for high-pressure and high-temperature (HPHT) heat exchangers produced through additive manufacturing (AM) techniques. As the demand for high-efficiency energy systems has been rising, the role of heat exchangers for thermal management and transport is becoming increasingly crucial. In this context, AM has emerged as a promising manufacturing solution to address the challenges posed by higher operating temperatures and/or pressures. This paper delves into three primary areas: the exploration of HPHT regimes supported by conventional heat exchangers, the impact of AM processes on thermal transport devices, and the discussion focused on HPHT heat exchangers produced via AM. The study examines the traditional manufacturing processes, materials, structures and geometries, and limitations of the commonly used heat exchangers for HPHT applications. Furthermore, it highlights the potential of AM in optimizing HPHT heat exchanger design, by reviewing studies that enable uniform flow distribution, minimization of fouling, and thermo-hydraulic performance augmentation without compromising structural stability. While addressing the limitations of cost, size, and other constraints, this study offers insights into the possibilities of AM in revolutionizing HPHT heat exchanger technology. The goal has been to fill the gap in literature by summarizing key studies, findings, and limitations, presenting a detailed examination, and proposing new areas for research. In conclusion, this review contributes to a deeper understanding of AM’s role in advancing HPHT heat exchangers for future energy systems.

36 MATERIALS SCIENCE↗

Nontraditional Approaches To Enable High-Energy and Long-Life Lithium–Sulfur Batteries

In this study, lithium-sulfur (Li-S) batteries are promising for automotive applications due to their high theoretical energy density (2600 Wh/kg). In addition, the natural abundance of sulfur could mitigate the global raw material supply chain challenge of commercial lithium-ion batteries that use critical elements, such as nickel and cobalt. However, due to persistent polysulfide shuttling and uncontrolled lithium dendrite growth, Li-S batteries using nonencapsulated sulfur cathodes and conventional ether-based electrolytes suffer from rapid cell degradation upon cycling. Despite significant improvements in recent decades, there is still a big gap between lab research and commercialization of the technology. To date, the reported cell energy densities and cycling life of practical Li-S pouch cells remain largely unsatisfactory. Traditional approaches to improving Li-S performance are primarily focused on confining polysulfides using electronically conductive hosts. However, these micro- and mesoporous hosts suffer from limited pore volume to accommodate high sulfur loading and the associated volume change during cycling. Moreover, they fail to balance adsorption-conversion of polysulfides during charge-discharge, leading to the formation of massive dead sulfur. Such hosts are themselves electrochemically inactive, which decreases the practical energy density. In contrast, a series of nontraditional approaches, paired with advances in multiscale mechanistic understanding, have recently demonstrated exciting performance outcomes not only in conventional coin cells but also in practical pouch cells. In this Account, we first introduce our novel cathode design strategies to overcome polysulfide shuttling and sluggish redox kinetics in thick S cathodes via selenium-sulfur chemistry and cathode host engineering. Next, we gain a mechanistic understanding of Li-S batteries in various types of electrolytes via a series of spectroscopic, nuclear magnetic resonance, and electrochemical methods. Meanwhile, a novel cathode solid electrolyte interphase encapsulation strategy via nonviscous highly fluorinated ether-based electrolyte is introduced. The established selection rule by investigating how solvating power retards the shuttle effect and induces robust cathode/solid-electrolyte interphase formation is also included. We then discuss how the synergistic interactions between rational cathode structures and electrolytes can be exploited to tailor the reaction pathways and kinetics of S cathodes under high mass loading and lean electrolyte conditions. In addition, a novel interlayer design to simultaneously overcome degradation processes (polysulfide shuttling and lithium dendrite formation) and accelerate redox reaction kinetics is presented. Finally, this Account concludes with an overview of the challenges and strategies to develop Li-S pouch cells with high practical energy density, long cycle life, and fast-charging capability.

25 ENERGY STORAGE↗

Nondestructive Analysis of Commercial Batteries

Electrochemical batteries play a crucial role for powering portable electronics, electric vehicles, large-scale electric grids, and future electric aircraft. However, key performance metrics such as energy density, charging speed, lifespan, and safety raise significant consumer concerns. Enhancing battery performance hinges on a deep understanding of their operational and degradation mechanisms, from material composition and electrode structure to large-scale pack integration, necessitating advanced characterization methods. These methods not only enable improved battery performance but also facilitate early detection of substandard or potentially hazardous batteries before they cause serious incidents. Here, this review comprehensively examines the operational principles, applications, challenges, and prospects of cutting-edge characterization techniques for commercial batteries, with a specific focus on in situ and operando methodologies. Furthermore, it explores how these powerful tools have elucidated the operational and degradation mechanisms of commercial batteries. By bridging the gap between advanced characterization techniques and commercial battery technologies, this review aims to guide the design of more sophisticated experiments and models for studying battery degradation and enhancement.

36 MATERIALS SCIENCE↗

Isolation of Single Donors in ZnO

The shallow donor in zinc oxide (ZnO) is a promising semiconductor spin qubit with optical access. Single indium donors are isolated in a commercial ZnO substrate using plasma focused ion beam (PFIB) milling. Quantum emitters are identified optically by spatial and frequency filtering. The indium donor assignment is based on the optical bound exciton transition energy and magnetic dependence. The emission stability of these single donors in terms of both intensity and frequency, alongside their transition linewidths less than twice the lifetime limit, highlight the promise of single In donors as optically accessible spin qubits. Here, the optical stability of single donors after FIB fabrication is promising for optical device integration required for scalable quantum technologies based on single donors in direct band gap semiconductors.

42 ENGINEERING↗

Manufacturing Valuable Coal-Derived Products in Southern Appalachia

This project’s objective is to develop and deploy new technologies for manufacturing rare earth elements (REE), critical minerals (CM), and valuable non-fuel, carbon-based products (CBP) from coal and/or coal waste in the SoApp Basin, thus revitalizing distressed SoApp coal communities and reducing reliance on foreign imports of REE and CM. Resource availability and technological advances alone will not ensure this objective is met. The right mix of business climate, market forces, and policy will also be needed. This report identifies the critical technologies, infrastructure, supply chains, human capital, and policy gaps that must be addressed to manufacture REE, CM, and CBP from coal resources and wastes in SoApp The primary goal of the project is to characterize the resource base in the SoApp Basin.

01 COAL, LIGNITE, AND PEAT↗

Integrating HPC, AI, and Workflows for Scientific Data Analysis: Report from Dagstuhl Seminar 23352

The Dagstuhl Seminar 23352, titled “Integrating HPC, AI, and Workflows for Scientific Data Analysis,” held from August 27 to September 1, 2023, was a significant event focusing on the synergy between High-Performance Computing (HPC), Artificial Intelligence (AI), and scientific workflow technologies. The seminar recognized that modern Big Data analysis in science rests on three pillars: workflow technologies for reproducibility and steering, AI and Machine Learning (ML) for versatile analysis, and HPC for handling large data sets. These elements, while crucial, have traditionally been researched separately, leading to gaps in their integration. The seminar aimed to bridge these gaps, acknowledging the challenges and opportunities at the intersection of these technologies. The event highlighted the complex interplay between HPC, workflows, and ML, noting how ML has increasingly been integrated into scientific workflows, thereby enhancing resource demands and bringing new requirements to HPC architectures, like support for GPUs and iterative computations. The seminar also addressed the challenges in adapting HPC for large-scale ML tasks, including in areas like deep learning, and the need for workflow systems to evolve to leverage ML in data analysis fully. Moreover, the seminar explored how ML could optimize scientific workflow systems and HPC operations, such as through improved scheduling and fault tolerance. A key focus was on identifying prestigious use cases of ML in HPC and understanding their unique, unmet requirements. The stochastic nature of ML and its impact on the reproducibility of data analysis on HPC systems was also a topic of discussion.

97 MATHEMATICS AND COMPUTING↗

Navigating United States Standards and Regulation for Digital Energy Systems

This report provides an analysis of the U.S. standards and regulatory landscape for digital energy systems, focusing on cybersecurity, safety, and reliability requirements. It examines the interplay between federal mandates, state regulations, voluntary industry standards, and utility-specific policies, highlighting critical gaps between compliance and real-world risk mitigation. While NERC CIP standards enforce cybersecurity for Bulk Electric System assets, distribution-level infrastructure and emerging technologies often fall outside mandatory oversight, creating vulnerabilities. The report identifies systemic challenges such as reliance on self-attestation, uneven state adoption of safety codes, and lagging standards for advanced technologies like battery energy storage and inverter-based resources. Through a detailed gap analysis, it underscores the urgency of proactive risk-based approaches, independent verification, and strategic engagement with state and federal entities. Recommendations include adopting tiered security frameworks, strengthening procurement practices, and addressing emerging technology risks to ensure resilient and secure digital energy infrastructure. This guidance is intended for utilities, regulators, and stakeholders navigating compliance obligations and seeking to enhance cybersecurity and safety beyond minimum standards.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Ducted Fuel Injection and Cooled Spray Technologies for Particulate Control in Heavy-Duty Diesel Engines

Heavy-duty diesel engine manufacturers are continually seeking simple, low-cost technologies to reduce emissions. Ducted Fuel Injection (DFI) and Cooled Spray (CS) technologies have emerged as promising solutions, offering the potential for nearly sootless operation. These innovations could significantly decrease harmful Particulate Matter (PM) emissions while enabling further optimization to reduce Nitrogen Oxides (NOx) and increase efficiency. While initial experiments across various engine types have shown promise, uncertainties remain regarding the ideal geometry, scaling properties, and effectiveness of these technologies across different operating conditions. This project aims to address these knowledge gaps through experiments in both optical and metal single-cylinder engines.

33 ADVANCED PROPULSION SYSTEMS↗

Development of thin-gap GEM- μ RWELL hybrid detectors

Micro Pattern Gaseous Detectors (MPGDs) are used for tracking in High Energy Physics and Nuclear Physics because of their large area, excellent spatial resolution capabilities and low cost. However, for high energy charged particles impacting at a large angle with respect to the axis perpendicular to detector plane, the spatial resolution degrades significantly because of the long trail of ionization charges produced in clusters all along the track in the drift region of the detector. The long ionization charge trail results in registering hits from large number of strips in the readout plane which makes it challenging to precisely reconstruct the particle’s position using simple center of gravity algorithm. As a result, the larger the drift gap, the more severe the deterioration of spatial resolution for inclined tracks. For the same reason, the position resolution is also severely degraded in a large magnetic field, where the Lorentz E x B effect causes the ionization charges to follow a curved and longer path in the detector gas volume. In this paper, we report on the development of thin-gap MPGDs as a way to maintain excellent spatial resolution capabilities of MPGD detectors over a wide angular range of incoming particles. In a thin-gap MPGD, the thickness of the gas volume in the drift region is reduced from typically 3 mm to 1 mm or less. We present preliminary test beam results demonstrating the improvement in spatial resolution from 400 m with a standard 3 mm gap μ RWELL prototype to ~140 μ m with a double amplification GEM- μ RWELL thin-gap hybrid detector. Here, we also discuss the impact of a thin-gap drift volume on other aspects of the performance of MPGD technologies such as the efficiency and detector stability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Toward the application of the Risk-Based Maintenance approach to a hydrogen-fueled manufacturing plant

Safety, reliability, and maintenance of hydrogen-based equipment, including Risk-Based Maintenance (RBM), have recently gained increasing attention, as hydrogen, while key to decarbonizing hard-to-abate sectors, raises safety concerns. However, two literature gaps limit the development of risk-based strategies for hydrogen technologies. First, existing RBM methodologies do not account for hydrogen-specific components, such as electrolyzers, which differ from conventional equipment. Second, available studies on electrolyzer reliability remain largely qualitative or laboratory-scale. This study addresses these gaps by proposing an adapted RBM methodology tailored to hydrogen-fueled manufacturing facilities. Integrating qualitative tools (e.g., FMEA) with probabilistic models (e.g., Bayesian Networks) enables comprehensive hazardous scenarios identification and likelihood estimation. A conceptual layout of a glass furnace supplied by a 3 MW PEM electrolyzer is considered as a case study to demonstrate the feasibility of the adapted RBM framework in identifying high-risk components and enabling maintenance prioritization, potentially improving plant safety.

08 HYDROGEN↗

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

14 SOLAR ENERGY↗

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services: Preprint

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗

Evaluating energy justice metrics in early-stage science and technology research using the JUST-R metrics framework

Embedding principles of energy justice throughout all aspects of clean energy technology research and development (R&D) can facilitate a more just energy transition; yet gaps remain in our understanding of how to best integrate energy justice from the earliest R&D stages. The Justice Underpinning Science and Technology Research (JUST-R) metrics framework has been developed to enable early-stage energy researchers to assess and address justice considerations associated with their research, but the impacts of the framework, and others like it, have yet to be evaluated. This study seeks to evaluate the JUST-R metrics framework in terms of its effectiveness and appeal to researchers engaged in early-stage technical R&D using qualitative analyses of documents and workshop transcripts. We find that the metrics framework helps researchers identify problems and potential solutions surrounding the energy justice implications of their work and spurs a change in perspective for researchers, but, simultaneously, there is no evidence of solution follow-through within the evaluation timeframe. Greater institutional support, specialization to research areas, knowledge of energy justice fundamentals, and earlier incorporation of energy justice considerations in research projects arise as factors needed to aid continued use of the framework and pursuit of identified solutions. This evaluation protocol and these findings can serve as a guide for improving other frameworks with similar goals of encouraging sociotechnical engagement in early-stage energy R&D.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comparison of effectiveness and energy use of airborne pathogen mitigation measures to meet clean air targets in a prototypical office building

Organizations such as ASHRAE and the Centers for Disease Control and Prevention (CDC) have proposed guidelines for controlling infectious aerosols in buildings, which can be met through measures such as modified operation of the heating, ventilation, and air-conditioning (HVAC) system or incorporating air-cleaning technologies. However, more research is needed to understand the trade-offs between health, energy, and comfort aspects when designing measures for these guidelines. To address this gap, this paper presents an analysis using new models for air-cleaning technologies, including in-duct and in-room germicidal ultraviolet (GUV) systems and portable air cleaners (PACs). These models are incorporated into an existing prototypical office building model and six measures are designed to meet ASHRAE Standard 241 and CDC clean air targets: MERV 13 HVAC filtration, maximum outdoor air supplied to the building, PACs, and in-duct, upper-room, and whole-room GUV. The measures are simulated for an office building in a cool and humid climate compared against a baseline simulation using MERV 8 filtration. The results show that all measures, except for the maximum outdoor air case, can meet the ASHRAE 241 standard without significant impacts on energy or comfort. The HVAC system measures were not able to meet the CDC target with the default system sizing and lead to significant energy increases, while the in-room measures were able to meet the CDC target with small impacts on energy consumption. Finally, this paper consolidates the simulation findings and provides practical guidance for building operators to meet clean air targets while limiting energy and comfort impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗