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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 217 records · Page 12

Accomplishments and challenges of metrics for sustainable energy, population, and economics as illustrated through three countries

The global Sustainable Development Goals require meeting multiple objectives on energy, population, economics, and ecosystems. Development and economic growth as defined by current metrics requires energy inputs, yet energy growth can also increase negative impacts on natural systems. To achieve sustainable development goals, policymakers and technologists will need energy system solutions that consider not only cost and efficiency but also population, quality of life, natural ecosystems, and culture that accommodates different starting points and transition timelines of various countries. To explore possible approaches, this perspectives paper summarizes energy in the context of economic growth and population, illustrating concepts through the diverse status and direction of three countries--Japan, the United States, and Bangladesh--as potential views into a post-growth sustainable future. Four fundamental questions on long-term energy development are identified, related to optimal energy use per capita, sustainable global energy demand, managing an energy transition with stable population, and the need for generalizable approaches across countries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Pathways to a Sustainable Aviation Ecosystem: Electrified Aviation Demand Modeling

With leading energy experts, high-performance computing, and powerful analysis and modeling capabilities, the National Renewable Energy Laboratory (NREL) empowers aviation stakeholders with tools and data to project future energy demand and explore supply options. As a result, NREL can help electric utilities and airport operations identify aviation electrification opportunities and prepare for future electricity needs.

aerial vehicles↗

Policy impact on economic and environmental sustainability of anaerobic digestion: Industrial case study Insights

This paper thoroughly examines how policy incentives impact the economic and environmental sustainability of anaerobic digestion (AD) systems. It uses techno-economic and life cycle analyses, along with real industry data, to explore the entire AD process—from feedstock acceptance to digestate disposal. It evaluates the effects of various U.S. policy crediting programs on the economic viability of different AD pathways for treating sewage sludge and food waste. Furthermore, tipping fees are identified as the primary driver of profitability, while policy credits play a crucial role in enhancing economic feasibility, particularly for renewable natural gas production. However, future regulatory changes could reshape this economic landscape. All AD pathways are found to significantly reduce greenhouse gas emissions, though economic outcomes are highly sensitive to digestate disposal costs and feedstock tipping fees. Co-digestion with food waste is proposed as a strategy to reduce dependence on policy credits and improve long-term economic stability.

Anaerobic Digestion↗

Process design and techno-economic analysis for bio-based graphite and liquid hydrocarbons production from lignocellulosic biomass

The worldwide demand for graphite, as the main anode material for Li-ion batteries, is expected to double by 2028 since it supports the use of electricity, including transient renewable sources, for energy storage, sustainable mobility, and automation. However, the dependence on non-renewable and external resources jeopardizes the world supply chain. This study explores the technical and economic performance of transforming lignocellulosic biomass into biographite and fuel-grade hydrocarbons through pyrolysis bio-oil upgrading. According to simulation results, the total power demand for the biorefinery reached 10,784 kWh per tonne of biographite, of which 36 % can be supplied by the heat integration network and power plant. Sensitivity and risk analyses were conducted to evaluate the economics, with process yields identified as the most relevant indicators to the minimum selling price (MSP). The analysis revealed a promising cost-competitive range for biographite MSP against fossil-based graphite (medium quality synthetic graphite Chinese market price ~$\$$4.2/kg). Case D, which includes biofuels as a byproduct, presents the best metrics, reaching a MSP of $\$$3.3/kg of anode-grade biographite with a profit margin of 27 %. While including biofuels in the product slate provides the best economic performance, the uncertainty associated with the big capital investment makes its risk 13 % higher to attain an IRR >20 % than the case in which biographite is produced as a standalone product. Overall, this study demonstrates that integrated biorefineries can produce a cost-competitive bio-based anode material for Li-ion batteries.

09 BIOMASS FUELS↗

Exploring the Structural, Biochemical, and Functional Diversity of Glycoside Hydrolase Family 12 from Penicillium subrubescens

Glycoside hydrolases (GHs) play an essential role in plant biomass degradation and modification for the sustainable production of biochemicals. The filamentous Ascomycete fungus Penicillium subrubescens contains a higher number of GH12 candidates compared to related species. Therefore, we aimed to compare P. subrubescens GH12s for their ability and substrate specificity for plant cell wall polysaccharide degradation and species’ potential as a source of novel enzymes for plant biomass valorization. Our re-evaluated phylogenetic analysis of fungal GH12 members showed that the P. subrubescens GH12s were located in different (new) clades. Biochemical characterization marked PsEglA as an endoglucanase and four other P. subrubescens GH12s (i.e., PsXegA–D) as xyloglucanases. Interestingly, structural features of PsXegD and PsXegE were more comparable to those of Basidiomycete GH12 xyloglucanases with a unique open substrate-binding cleft. PsUegA displayed dual xyloglucanase and endoglucanase activity and also showed distinct structural features. Comparative transcriptome analysis supported the functional diversity of P. subrubescens GH12s in plant biomass degradation. The gene encoding PsUegA was expressed under diverse conditions, suggesting a scouting role for this enzyme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transforming Energy Through Computational Excellence: A View From NREL

At the National Renewable Energy Laboratory (NREL)—a U.S. Department of Energy laboratory—computational science, high-performance computing, applied mathematics, advanced computer science, visualization, and data play a pivotal role in advancing energy abundance, affordability, security, and reliability. From fundamental scientifc discovery to systems engineering and analysis, NREL researchers tackle market-relevant challenges to develop solutions for an independent energy system that is reliable, resilient and secure. Collaborative partnerships with industry, government, and academia ensure that our research remains cutting edge, impactful, applicable, and aligned with real-world energy needs. This special issue of Computing in Science & Engineering highlights exemplary NREL projects where computational tools and methodologies drive discovery and accelerate innovation in scalable and integrated energy systems. The featured articles explore the role of computational modeling, high-performance computing, generative AI, and adaptive computing in advancing independent energy solutions, optimizing sustainability research, and enhancing decision-making for energy solutions using a broad mix of energy technologies. Here, these contributions demonstrate how NREL’s computational research bridges the gap between theoretical advancements and practical implementation, emphasizing interdisciplinary collaboration and a commitment to innovation, with a focus on translating computational excellence into real-world impact, thus accelerate progress toward national energy goals. By showcasing cutting-edge research at the intersection of computational science and energy systems, this issue aims to inspire and inform researchers, practitioners, and policymakers dedicated to shaping a more reliable energy future.

97 MATHEMATICS AND COMPUTING↗

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗

Environmental, Economic, and Scalability Consideration of Selected Biomass-Derived Blendstocks for Mixing-Controlled Compression Ignition (MCCI) Engines

Co-Optimization of Fuels & Engines (Co-Optima) explores how simultaneous innovations in fuels and engines can boost fuel economy and vehicle performance while reducing emissions. The Analysis of Sustainability, Scale, Economics, Risk and Trade (ASSERT) team supports Co-Optima goals by evaluating environmental and economic drivers and the potential of bioblendstock candidates. The team assesses potential benefits or drawbacks of deploying co-optimized fuels and engines in the transportation sector. This presentation provides guidance into which Co-Optima bioblendstocks may be most economically and environmentally viable when scaled up.

biomass↗

Developing Metrics to Assess Justice and Equity Implications of Early-Stage Research

Physics is a central component of early-stage research and development of virtually all technologies. But as much as scientific breakthroughs often hold the key to high efficiencies, long lifetimes, and high stability in devices for countless applications, early-stage choices research choices, such as those around materials or processing, can also serve to lock in long-term social and equity impacts of deployed technologies. This talk will explore how scientists can start to consider these impacts, with a focus on the energy sector and achieving a just and sustainable energy transition. We discuss development of the Justice Underpinning Science and Technology Research (JUST-R) metrics framework - a suite of metrics targeted at early-stage researchers to assess justice considerations in their work. The framework is evaluated for its appeal to researchers and effectiveness at promoting integration of justice considerations into research through case studies, which reveal its ability to broaden researcher perspectives and key avenues for future improvement.

energy equity↗

U.S. Airport Infrastructure and Sustainable Aviation Fuel

Worldwide, aviation accounts for 2% of all manmade carbon dioxide emissions and 12% of all transportation CO 2 emissions In 2018, the U.S. accounted for 25% of the world jet fuel consumption and 21% of global enplanements. Airports and airlines are considering alternative fuel to meet environmental and sustainability goals and mandates. Sustainable aviation fuel (SAF), made from non-petroleum feedstocks, has the potential to significantly reduce emissions from air transportation. SAF must be blended with petroleum based jet fuel prior to its use in aircraft. This report explores background information on jet fuel use, quality standards and best practices, airport infrastructure, and options for delivering SAF to airports.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2,5‐Dimercapto‐1,3,4‐Thiadiazole (DMCT)‐Based Polymers for Rechargeable Metal–Sulfur Batteries

Organosulfur materials are a sustainable alternative to the present-day layered oxide cathodes in lithium-based batteries. One such organosulfur material that was intensely explored from the 1990s to early 2010s is 2,5-dimercapto-1,3,4-thiadiazole (DMCT). However, research interest declined as the electrode reactions with DMCT were assumed to be too sluggish to be practical. Armed with the advances in metal–sulfur batteries, we revisit DMCT-based materials in the form of poly[tetrathio-2,5-(1,3,4-thiadiazole)], referred to as pDMCT-S. With an appropriate choice of electrode design and electrolyte, pDMCT-S cathode paired with a Li-metal anode shows a capacity of 715 mA h g −1 and a Coulombic efficiency of 97.7% at a C/10 rate, thus quelling the concerns of sluggish reactions. Surprisingly, pDMCT-S shows significantly improved long-term cyclability compared to a sulfur cathode. Investigations into the origin of the stability reveals that the discharge product Li-DMCT in its mesomeric form can strongly bind to polysulfides, preventing their dissolution into the electrolyte and shuttling. This unique mechanism solves a critical problem faced by sulfur cathodes. Encouragingly, this mechanism results in a stable performance of pDMCT-S with Na-metal cells as well. In conclusion, this study opens the potential for exploring other organic materials that have inherent polysulfide sequestering capabilities, enabling long-life metal–sulfur batteries.

2,5-dimercapto-1,3,4-thiadiazole↗

A remarkable CHF of 345W/cm 2 is achieved in a wicked-microchannel using HFE-7100

Boiling heat transfer of dielectric fluids is a promising cooling technique for thermal management of microelectronic systems. However, the critical heat flux achievable is generally low, because of the poor thermophysical properties of these fluids. Here, to address this dilemma, we propose a new cooling concept to substantially enhance global liquid supply during phase-change process using enhanced capillary-driven force. Additionally, dedicated vapor pathways are designed among a bank of micro-pillars to facilitate vapor removal. In this work, new wicks comprised of silicon micro-pinfin arrays are explored to significantly enhance the flow boiling heat transfer performance. To examine the functionalities of this wick, experiments on HFE-7100 were carried out with mass velocities varying from 247 to 3,465 kg/m 2 s. To explore the enhancement mechanisms and to analyze the capillary-assisted flow boiling process, visualization studies were conducted. The results indicate that sustainable evaporation induced by wick microstructures and efficient liquid supply are the enhancement mechanisms compared to parallel microchannels with solid walls. It is found that the overall heat transfer coefficient is substantially increased up to 75%. Remarkably, a high critical heat flux (CHF) of approximately 345 W/cm 2 is recorded at G = 3,465 kg/m 2 s at coolant inlet temperature of ~20 °C. Equally importantly, this noticeable enhancement of CHF value is associated with drastically decreased pressure drops compared to microchannels decorated with μ-pinfin fences.

36 MATERIALS SCIENCE↗

Experimental and theoretical study of weakly coherent mode in I-mode edge plasmas in the EAST tokamak

The I-mode is a promising operation mode for fusion in the future, featuring high-temperature and low-density confinement, but the reason why the temperature and density are decoupled remains an important aspect to be explored. The experimental results from the experimental advanced superconducting tokamak (EAST) showed that the weakly coherent mode (WCM) is directly related to sustaining the I-mode and that the peak amplitude of the WCM is proportional to the temperature in the pedestal. Here, simulating the experimental data from EAST with the six-field model of BOUT++, we find a density perturbation close to the frequency of the WCM observed in the experiment. By testing all the physical terms in this model, we find that the density perturbation and particle transport are directly related to the drift Alfvén wave (DAW) mode. Additionally we use the SymPIC program (Xiao et al Plasma Sci. Technol. 20 110501; Phys. Plasmas 22 112504; Plasma Sci. Technol. 23 055102) to simulate the same experimental data and find that the frequency range of the WCM is close to both experimental and BOUT++ results. Therefore, the WCM of the I-mode can be considered to be driven by the DAW, which helps improve the transport of the I-mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

GDSA - Modeling and Integration – ORNL: PFLOTRAN modeling

This report summarizes work done at Oak Ridge National Laboratory (ORNL) related to post-closure criticality consequence analysis of dual-purpose canister (DPC) direct disposal in unsaturated alluvium. PFLOTRAN software was used to model the behavior of a breached DPC with low water infiltration rates and unsaturated conditions in alluvial deposits such that a low-power criticality event occurs with a focus on thermal hydrological constraints on criticality timing and power output. This summary describes initial exploration of those thermal hydrological processes and of the long-term average power output from a criticality event that could be sustained without driving water out of the DPC package and thereby terminating the criticality event. The objectives are (1) to identify, for different groundwater infiltration rates, the time at which the DPC fills with water sufficiently to potentially initiate criticality; (2) to bound the power output that could be produced by a criticality event that would thermally drive water out of the package at various percolation rates; and (3) provide an estimate of how the size of a package breach affects the water infiltration and therefore the possibility timing of criticality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Biofuels Induced Land Use Change Emissions: The Role of Implemented Land Use Emission Factors

Biofuels’ induced land-use change (ILUC) emissions have been widely studied over the past 15 years. Many studies have addressed uncertainties associated with these estimates. These studies have broadly examined uncertainties associated with the choice of economic models, their assumptions and parameters, and a few bio-physical variables. However, uncertainties in land-use emission factors that represent the soil and vegetation carbon contents of various land types across the world and are used to estimate carbon fluxes due to land conversions are mostly overlooked. This paper calls attention to this important omission. It highlights some important sources of uncertainty in land-use emissions factors, explores the range in these factors from established data sources, and compares the influence of their variability on ILUC emissions for several sustainable aviation fuel (SAF) pathways. The estimated land-use changes for each pathway are taken from a well-known computable general equilibrium model, GTAP-BIO. Two well-known carbon calculator models (CCLUB and AEZ-EF) that represent two different sets of emissions factors are used to convert the GTAP-BIO estimated land-use changes to ILUC emissions. The results show that the calculated ILUC emissions obtained from these carbon calculators for each examined SAF pathway are largely different, even for the same amortization time horizon. For example, the ILUC emissions values obtained from the AEZ-EF and CCLUB models for producing jet fuel from corn ethanol for a 25-year amortization period are 24.9 gCO 2 e/MJ and 15.96 gCO 2 e/MJ, respectively. This represents a 60% difference between the results of these two carbon calculators for the same set of land-use changes. The results show larger differences for other pathways as well.

09 BIOMASS FUELS↗

BETO 2021 Peer Review - WBS 4.1.2.32: Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis project uses systems thinking and analysis to assess current and/or prospective techno-economics, research and development, deployment strategies, policy, and market conditions and their impact on the potential development trajectories of the bioenergy industry over time. Results from this project include identification of opportunities and constraints to industrial development, quantification of multiple metrics (energy, economic, environmental) and informing researchers, decision makers, and industry of the steps needed for a sustainable, nationwide biofuels industry. Analyses from this project enable the creation of a bioenergy industry by (1) inciting policy-makers to explore scenarios for nationwide biofuels production, identifying policy actions consistent with pathways for growth; (2) improving industry’s understanding of industry growth potential under different technology and investment conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with tools and analyses that can be adapted to meet research and teaching objectives, connecting students with careers that build the industry. One of the many modeling tools used in this project, the Biomass Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. We use models like the BSM to examine the implications of policies and incentives as well as their potential side-effects. The BSM uses a system-dynamics simulation to model dynamic interactions and transitions across the supply chain; it tracks the deployment of biofuels given industrial learning and the reaction of the investment community in the context of land availability, projected oil markets, consumer demand for biofuels, and government policies over time. Under expected market conditions, analyses using the BSM suggest that the biofuels industry may require significant external actions in the early years to thrive. Interventions that accelerate the industrial learning process (e.g. operation of pre-commercial and commercial facilities) have been identified as having strong influence in starting the growth of a commercial biofuel industry. Policies which are coordinated across the whole supply chain in BSM foster the growth of the biofuels industry and production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Combining CO2 Electrolysis with Biological Upgrading to Fuels and Chemicals: Turning Waste into Fuels

The utilization of flue gas-derived CO2 presents an opportunity to enhance carbon utilization in the bioethanol industry, contributing to the production of valuable products. In the context of a 90 million-gallon-per-year corn ethanol plant generating approximately 30 tons per hour of 99% pure CO2, a collaborative effort involving six national laboratories has been established. This initiative, known as the CO2 Reduction and Upgrading for e-Fuels (CO2RUe) Consortium, is funded by the Department of Energy's BioEnergy Technologies Office (BETO). The primary objective of the CO2RUe Consortium is to explore innovative approaches to harness CO2 as a valuable feedstock. This interdisciplinary consortium integrates electrochemistry with biological upgrading techniques, aiming to yield sustainable, value-added products and aviation fuels. The presentation will delve into the recent advancements in the realms of electrochemistry and biological upgrading, with a specific focus on formic acid and CO. Additionally, the talk will include an analysis of future electricity grid scenarios, technoeconomic evaluations, and life-cycle assessments. These assessments aim to provide a comprehensive understanding of the impacts of various conversion pathways on both cost and carbon intensity. The CO2RUe Consortium is at the forefront of steering the development of economically favorable and sustainable processes for CO2 utilization. The presentation will showcase the consortium's progress in driving the advancement of technology and processes, emphasizing the economic viability and sustainability of CO2 utilization within the broader context of the bioethanol industry.

biological upgrading↗