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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Advancing Ethanol-to-Jet cost Effectiveness via direct conversion to n -Butene-Rich olefins and Co-Product Valorization

Ethanol is a promising feedstock for sustainable aviation fuel production; however, conventional routes face significant energy and cost challenges, particularly due to the ethanol dehydration step to ethylene. Here, this study leverages breakthrough experimental data to perform comprehensive techno-economic and life-cycle assessments of an innovative ethanol-to-jet process. The process employs a single-step catalytic conversion, enabled by multifunctional Cu-ZrO 2 /SBA-16 catalyst, to directly upgrade ethanol into a mixed olefin stream rich in n-butene. The single-step conversion eliminates the costly ethanol dehydration step in the conventional process. High selectivity toward n-butene offers key advantages: it simplifies downstream oligomerization into jet-range hydrocarbons and enables the co-production of renewable n-butene alongside sustainable aviation fuel. The analysis estimates a minimum fuel selling price as low as $\$$2.50 per gallon, whether using corn ethanol or cellulosic ethanol from corn stover. Life cycle CO 2 equivalent emissions are projected to be as low as 10.6 g CO 2 eq/MJ sustainable aviation fuel, representing over 70% reduction compared to conventional petroleum-based jet fuel. This one-step ethanol upgrading approach not only facilitates SAF and n-butene co-production but also provides operational flexibility. The ability to tailor product outputs allows the ethanol-to-jet process to adapt to varying feedstocks, incentive programs, and market dynamics, ultimately enhancing the economic viability of sustainable aviation fuel production.

Xu, Yiling [Pacific Northwest National Laboratory ↗
DOE OSTI2025

The Staged, Pressurized Oxy-Combustion Technology: Status and Application to Boiler Retrofits to Yield Carbon-Negative Power via Biomass

Recognizing the benefits of pressurization and fuel staging on the efficiency of oxy-combustion, the staged, pressurized oxy-combustion (SPOC) process was introduced in 2012. The combination of fuel staging and pressurized oxy-combustion results in a more compact plant, a higher plant efficiency and reduced costs for pollutant and greenhouse gas removal compared with plants equipped with conventional carbon capture. This approach to power generation enables a modular boiler design and optimizes the plant for flexible operation, which is essential to meet the demands of the modern grid when it contains intermittent power sources. Originally designed to burn coal, the SPOC process is well-suited for biomass because the combustion of biomass leads to a high moisture content in the flue gas and the SPOC process is able to recover the latent heat of this moisture, enhancing system performance over that of traditional biomass combustion at atmospheric pressure. The present work is focused on evaluating the potential for utilizing the SPOC process in retrofit applications wherein the boilers of an existing plant are replaced with the SPOC process, and woody biomass is used as the fuel to yield carbon-negative power. Two applications are considered: power generation and cogeneration (heat and power). Modeling these systems in Aspen Plus demonstrates that the SPOC process surpasses the performance of baseline plants with post-combustion capture (PCC) for both power generation and cogeneration. Specifically, compared to a PCC equipped plant, the SPOC power plant has 33% higher efficiency, and the SPOC cogeneration plant reaches 42% higher net energy. Experimentally, the existing SPOC facility was fired for the first time with 100% biomass and after minor improvements were made to the feeding system, the facility demonstrated excellent performance during startup, steady-state operation and turndown.

Carbon capture and storage↗
DOE OSTI2025

Probing Surface/Bulk Structural Chemistry of Key Components of Solid Oxide Electrochemical Cells with In Situ / Operando Raman Spectroscopy

The remarkable attributes of solid oxide electrochemical cell technology (e.g., energy efficiency, low cost, scalability, low emissions, and operational flexibility, etc.) drive the wider adoption of electrochemical conversion routes for sustainability. It is critical for the codevelopment of solid oxide cell materials and processes to establish the mechanistic understanding of the underlying chemical phenomena at the molecular level. Herein, we summarize the advancements in Raman spectroscopy that provide structural/molecular information on electrode/electrolyte materials typically used in solid oxide cells for energy conversion. In particular, we discuss the multifactorial environment induced chemical processes that govern the performance and longevity of solid oxide electrochemical devices. The in situ/operando Raman spectroscopic investigations on the electrode/electrolyte materials reported in the literature are summarized with the emphasis on identification of key material properties that control the functional aspects of the solid oxide cells. The molecular level understanding of the electrochemical processes will allow advancement of the rational design of electrochemical materials for process level deployment of solid oxide cell technology.

Electrodes↗
DOE OSTI2025

Equilibrium-gated pattern formation: How molecular dissociation thermodynamics drive emergent behavior in dissipative polymeric systems

Emergent patterns in biological systems arise through dissipative processes that balance reaction and transport phenomena, producing highly functional properties from self-regulating mechanisms. Synthetic fabrication, by contrast, often relies on user-controlled, multistep methods that lack the self-organizing capabilities of natural systems. Inspired by nature, we sought chemical systems that integrate strongly coupled reaction and transport phenomena, identifying frontal ring-opening metathesis polymerization (FROMP) as a method capable of creating diverse forms and functions through reactive processing. By employing discrete molecular initiators, FROMP allows precise control of key reaction steps—inhibition, initiation, and propagation. Using an integrated computational and experimental framework, we uncover how near-equilibrium inhibition dynamics, coupled with far-from-equilibrium reaction kinetics, drive pattern formation in frontally polymerized synthetic materials. We propose the concept of equilibrium-gated pattern formation, demonstrating how initiator chemistry can be tuned to achieve programmable macroscale properties. Our study reveals a surprising insight: Emergent behavior in FROMP systems arises from the inhibition-dominated regime of resin composition, expanding prior observations that such behavior is confined to a narrow compositional space near the boundary between front quenching and uniform front propagation. We identify a broader compositional window, far from the quenching regime, where emergent behavior reliably manifests. This expanded design space significantly enhances the operational flexibility of reactive systems and their capacity for self-organization. Furthermore, these insights provide a roadmap for designing bioinspired materials with self-organizing capabilities, unlocking possibilities in synthetic manufacturing.

Architected Polymers↗
DOE OSTI2025

Feasibility of Recycling Discharged Microreactor Heavy Metal in Light Water and Sodium-Cooled Fast Reactors: A Neutronics Analysis

Nuclear microreactors (MRs) offer unique advantages, such as rapid deployment, potability, low maintenance requirements, and operational flexibility. Their compact size makes them a promising solution for decentralized power generation, particularly in remote areas, military bases, and disaster-stricken regions. However, MRs face challenges, including unutilized fissile material at the end of life, economic inefficiency, increased heavy metal (HM) waste complicating disposal, and the accumulation of plutonium (Pu) with high 239 Pu concentrations raising proliferation risks. Here, this study investigated the neutronics feasibility of a novel three-stage fuel cycle where discharged HM from MRs is recycled and burned in light water reactors and sodium-cooled fast reactors. This approach converts discharged HM into valuable fuel, enhancing the efficiency of MR deployments while improving the safeguardability of their final waste products. Neutronics analysis demonstrated that the safety characteristics of reactor designs in each stage were minimally impacted by the proposed cycle. For two representative MR designs, a fast-spectrum MR with solid pellet fuel and a thermal-spectrum MR with TRISO (TRi-structural-ISOtropic) fuel compacts, the proposed fuel cycle reduced the uranium disposal mass flow rate by ~60%, decreased the 235 U enrichment of the discharge fuel to ~1 wt%, eliminated plutonium disposal, and increased the cumulative fuel burnup to ~580 gigawatt-day per metric ton of initial heavy metal (GWd/t-iHM) or 60% fissions per initial metal atom. Despite the significant differences between the two MR designs, the performance and infrastructure requirements of the developed fuel cycles were remarkably similar, indicating its generalizability to a broader class of MRs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Primary Heat Transport System Design Considerations for Xcimer Energy’s Athena Fusion Pilot Plant

Fusion energy promises a reliable, carbon-free source of power; however, significant challenges remain before it can be deployed as an economical energy source. In addition to achieving fusion conditions, power plants must operate under extreme temperatures, radiation, and mechanical loads while maintaining high efficiency and availability. These requirements place strong demands on engineering design and plant operation. This work focuses on the engineering challenges associated with balance of plant analysis for inertial fusion energy systems. In particular, this paper examines the design considerations for primary heat transfer systems in fusion pilot plants employing molten fluoride salt coolants, with particular emphasis on system layout optimization and the balance between competing design objectives using the Xcimer Energy Athena inertial pilot plant design as a case study. Through systematic analysis of candidate system configurations and parametric sensitivity studies, we identify key engineering trade-offs governing salt inventory, pumping power requirements, and operational flexibility. The analysis employs system-level modeling tools to explore the design space and establish relationships between geometric parameters and system performance metrics.

Greenwood, Scott [ORNL] (ORCID:0000000333480736)↗
DOE OSTI2024

A Networked Microgrid Framework and Testbed for Communication, Controls, and Optimization Testing

This paper presents the development and experimental results of a networked AC microgrid testbed located at Oak Ridge National Laboratory. The testbed comprises two, 480V three-phase, four wire microgrids designed to operate standalone, grid-tied, or as a network of microgrids. This testbed represents both the state of the industry, by incorporating grid-assets commonly found in real microgrids, and the state of the art, as it is a platform to evaluate advanced controllers. The main elements of this networked microgrid testbed are presented in this paper including a Scenario Manager, local microgrid controls, and a networked microgrid control. The Scenario Manager has the objective of emulating real-world conditions. The local microgrid controller oversees standalone, grid-tied, or islanded operation. The microgrid control is a higher-level control that coordinates interaction between islanded microgrids. This paper delves into these controllers and validates their operation in the networked microgrid testbed showcasing the operational flexibility and advance control capabilities.

Ferrari Maglia, Max↗
DOE OSTI2026

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
DOE OSTI2024

Case study of UAS ignition of prescribed fire in a mixedwood on the William B. Bankhead National Forest, Alabama

Abstract Background For at least four decades, practitioners have recognized advantages of aerial versus ground ignition for maximizing the effectiveness of prescribed fires. For example, larger areas can be ignited in less time, or ignition energy may be variously targeted over an area in accordance with the uneven distribution of fuels. The maturation of wireless communication, geopositioning systems, and unmanned aerial systems (UAS) has enhanced those advantages, and UAS approaches also provide further advantages relative to helicopter ignitions, such as reduced risk to human safety, lower operating costs, and higher operational flexibility. In a long running study at the Bankhead National Forest in northcentral Alabama, prescribed fire has been used for nearly 20 years. Most of the burns have been hand-ignited via drip torches, while some have been aerially ignited via helicopter. In March 2022, for the first time, a UAS was used to ignite prescribed fires across a landscape that included a long-term research stand. This field note relates comparisons of both fire behavior and fuel consumption metrics for the UAS-ignited burn versus previous burns on the same stand, and versus burns of other research stands in the same year. Results The UAS-ignited prescribed fire experienced burn effects similar to those from ground-ignited prescribed fires on the same stand in previous years, as well as those from ground-ignited prescribed fires on other stands in the same year. Conclusion This post hoc analysis suggests that UAS ignition approaches may be sufficient for achieving prescribed burn goals, thereby enabling practitioners to realize the advantages offered by that ignition mode.

Environmental Sciences & Ecology↗
DOE OSTI2024

Transactive Energy Practices Survey

For nearly two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach encourage transactive energy designs have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Membrane-based Carbon Capture Process Optimization using CFD Modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.

Pedrozo, Hector A.↗
DOE OSTI2024

Treatment and Mineral Recovery from Combustion Residual Leachate and Produced Water

This talk presents the design of operationally flexible diafiltration membrane systems for Li/Co recovery, and applies robust optimization methodologies using these flexible systems to generate optimal designs immune to membrane manufacturing variability and uncertain process inlet conditions. The results highlight the use of robust optimization to find design strategies and insights that may reduce technical risks arising from model uncertainties.

Able, Chad↗
DOE OSTI2025

Evaluating Thermostats' Deadbands Using HVAC Hardware-In-the-Loop Experiment for Advanced Control Strategies

Smart thermostats have gained significant popularity due to their potential for optimizing energy consumption and enhanced user control while ensuring occupants' comfort. The deadband, also referred to as temperature differential, is defined as the temperature difference between the desired setpoint and upper threshold or lower threshold for the HVAC equipment to turn on. It is a key factor influencing energy efficiency and user satisfaction. This paper presents a comparative analysis of the deadbands of five different smart thermostats, tested with a heat pump, aiming to identify variations in their deadband settings and implications for energy management. The experimental study was conducted using a HVAC hardware-in-theloop (HIL) system that integrates smart thermostats with physical HVAC equipment in a simulated house environment. The study explores the trade-offs between energy efficiency and occupant comfort and highlights how different thermostats participating in demand response event cycle differently based on their deadband settings. The findings offer valuable insights into how selecting the right thermostat or configuring smart thermostat with appropriate deadband settings can be leveraged to enhance demand response capabilities, shift loads effectively and improve operational flexibility in HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Post-2026 Environmental Impact Statement Rate Analysis for the Colorado River Storage Project

The Glen Canyon Dam (GCD) is a principal power-generating asset within the Colorado River Storage Project (CRSP), accounting for approximately 70–80% of CRSP power production over the past two decades. In June 2023, the U.S. Bureau of Reclamation (Reclamation) issued a Notice of Intent to prepare an Environmental Impact Statement (EIS) outlining operational guidelines and strategies for Colorado River Basin reservoirs after 2026 (Reclamation, 2023). Power generation is among CRSP’s statutory purposes under the Colorado River Storage Project Act of 1956 (U.S. Congress, 1956). Assessing how alternative policy frameworks affect CRSP power production and the resulting electricity rates for U.S. customers is therefore essential to inform decision-making. This report evaluates projected electricity rates and the market value of electricity from the Western Area Power Administration (WAPA) CRSP GCD under multiple post-2026 policy scenarios to support Reclamation’s EIS development. Results from advanced econometric and machine learning models indicate that the Enhanced Coordination alternative (EnhanCoor), Maximum Operational Flexibility alternative (CCA), and Supply Driven - 55 alternative (SD55) alternatives yield more favorable hydropower generation and capacity outcomes, which are objectives outlined in Reclamation’s documentations (Reclamation, 2007; Reclamation, 2016). Specifically, these scenarios are associated with higher electricity production, lower projected rate trajectories, and greater economic value to the U.S. power system from CRSP generation. The remaining five scenarios generally produce lower generation, higher rate trajectories, and reduced long-term market values.

13 HYDRO ENERGY↗
DOE OSTI2026

Machine Learning Based Metamodel for Faster Life Cycle Assessment of Large Portfolio of Buildings

Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Update on Model Specification Development of Ternary Pumped Storage Technologies [Slides]

T-PSH is an innovative structure of C-PSH that features two turbines, one for pumping and one for generation, replacing the single turbine in C-PSH. These turbines are housed in separate chambers, with an additional set of penstocks connecting the pump turbine to the hydraulic system. This structure enables T-PSH to operate in an HSC mode, allowing for simultaneous pumping and generation, which provides greater operational flexibility compared to C-PSH. To model T-PSH's HSC mode, a user defined turbine and governor system model is required, including the shared penstock model and additional pump turbine model. This specification will focus on the details of the user-defined turbine and governor model, which leverages the HYGOV model.

16 TIDAL AND WAVE POWER↗