Anode-Free Full Cells: A Pathway to High-Energy Density Lithium-Metal Batteries
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Chemistry↗
SEARCH · Engineering Papers
Results for “rapid decarbonization”
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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In-Situ Atomic-Scale Revelation of Amorphous Metallic Iron Formation during Hydrogen-Driven Reduction of Iron Oxides
The transition to hydrogen as a green reductant in metal production is critical for decarbonizing the metallurgical industry, yet atomic-scale mechanisms governing reduction pathways and phase evolution remain unresolved. Using in-situ environmental transmission electron microscopy, we identify a hidden pathway that reveals dynamic formation of amorphous metallic iron (Fe) during the hydrogen-driven reduction of ferrous oxides of Fe 3 O 4 and FeO. Real-time imaging uncovers three coexisting transformation routes: (i) Fe 3 O 4 → FeO, (ii) Fe 3 O 4 → amorphous Fe, and (iii) FeO → amorphous Fe. The resulting amorphous Fe exhibits fluid-like mobility, enabling its rapid aggregation and crystallization into core-shell nanostructures, with a crystalline core enveloped by an amorphous shell. Complementary ab initio molecular dynamics simulations trace the amorphous Fe formation to interfacial strain at the metal/oxide interfaces, where large lattice mismatches destabilize the metal lattice during initial metallization. This interplay between thermodynamics and kinetics governs phase evolution: thermodynamics favors a self-limiting amorphous Fe overlayer, while rapid oxide reduction kinetics drives amorphous overgrowth. Our findings demonstrate that amorphous intermediates bypass rate-limiting crystalline steps, providing mechanistic insights to optimize H 2 -based processes for sustainable steelmaking. In conclusion, these insights bridge the gap between macroscopic process engineering and atomic-scale dynamics, with broader implications for catalysis and nanostructured material synthesis, where oxide reduction pathways critically shape functional phases and microstructures.
36 MATERIALS SCIENCE↗
Innovating the next generation of commercial smart building software
Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.
Casillas, Armando↗
Development of a web-based screening tool for ground source heat pump applications
Ground source heat pump (GSHP) technology has great potential to help the nation meet its energy and decarbonization goals, but several barriers hinder the wide application of GSHP. Important barriers include the lack of a coherent toolset for analyzing the technical feasibility and economic viability of the GSHP application. The current design and analysis methods are ineffective and require significant expertise to apply. Although building energy modeling is increasingly important in designing buildings, the tools for GSHP modeling and simulation are lacking. A web-based free-to-use tool is being developed for quick techno-economic analysis of GSHP applications in nearly any building in the United States. This tool is enabled by improvements in the calculation methodology to allow rapid sizing of borehole configurations that provide significant cost savings. The screening tool currently uses US Department of Energy (DOE) prototype building models and an extended g-function library to size ground heat exchangers and simulate the performance of GSHP systems. The team is integrating with DOE's Oak Ridge National Laboratory's AutoBEM program to automatically create a building model based on user inputs. This paper introduces the structure, components, features, and results of the web-based screening tool for GSHP applications. Future directions for further developing the tool are also discussed.
Liu, Xiaobing↗
Computational framework for behind-the-meter DER techno-economic modeling and optimization: REopt Lite
The energy system is undergoing a major transformation with the global emphasis on decarbonization. Distributed generation is projected to play a significant role in the new energy system, and energy models are informing how distributed generation can be integrated reliably and economically. In this work, we present an end-to-end computational framework for distributed energy resource (DER) modeling, REopt Lite™, which captures the interface of technology, economics, and policy in the energy modeling process. We describe the problem space, the building blocks of the model, the scaling capabilities of the design, the optimization formulation, and the extensibility of the model. We present a framework for accelerating the techno-economic analysis of behind-the-meter distributed energy resources to enable rapid planning and decision-making, thereby enabling greater renewable energy deployment. This computation framework is open-sourced to facilitate transparency, flexibility, and wider collaboration opportunities within the worldwide energy modeling community.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Hierarchically Structured Catalysts Toward Sustainable Hydrogen Economy: Electro‐ and Thermo‐Chemical Pathways
Abstract Hydrogen, as an important clean energy source, plays a more and more crucial role in decarbonizing the planet and meeting the global climate challenge due to its high energy density and zero‐emission. The demand for sustainable hydrogen is increasing drastically worldwide as driven by the global shift towards low‐carbon energy solutions. Thermochemical catalysis process dominates hydrogen production at scale given its relatively mature technology and commercialization status, as well as the established manufacturing infrastructure. While due to its environmentally friendly nature and growing abundant sources of renewable electricity, the electrochemical path for hydrogen production is rising as a major alternative to the thermochemical means. Nevertheless, hierarchically structured catalysts and devices have gradually taken the center stage toward replacing the traditional counterparts, especially with the rapid advancement of the design and manufacture of such ordered nanostructure assemblies toward high activity, efficient mass transport, and superb stability. In this review, the latest progress of the hierarchically structured catalysts for hydrogen production have been surveyed on electro‐ and thermo‐ chemical pathways comparatively. It covers the structure designs of atomic dispersion, nanoscale surfaces and interfaces for achieving highly active and durable catalysts, components, and devices. Both electrochemical and thermochemical approaches are reviewed in terms of the vast design details, engineered benefits, and understandings of various Pt‐group metal (PGM) and non‐PGM based transition metal catalysts for hydrogen production. As the growing trend, brief discussions are also presented toward the high‐level assembly and manufacture of complexly structured components and devices at scale in the electrochemical and thermochemical energy systems.
Deng, Chenxin↗
Large-Amplitude Motion Platform: A New Ocean Simulator Can Help Technologies Succeed
Offshore renewable energy technologies - like wave energy devices, wind turbines, floating solar panels, and hybrid systems - can help decarbonize our power grids as well as offshore activities like international shipping and seafood farming. But it's not always easy to build technologies hearty enough to operate in a powerful ocean environment. And subjecting promising prototypes to real ocean waves can be an expensive, time-consuming, and risky way to get these technologies ready for the high seas. Now, with the National Renewable Energy Laboratory's (NREL's) new testing platform, called the large-amplitude motion platform (or LAMP for short), our experts can replicate powerful ocean waves in a low-risk laboratory setting. The LAMP, coupled with NREL's diverse array of testing instrumentation, can help technology developers rapidly hone their prototypes before embarking on a potentially costly and time-consuming ocean trial.
marine energy↗
Generative AI for Power Grid Operations
Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Future-proofing photovoltaics module reliability through a unifying predictive modeling framework
Solar energy, especially photovoltaics (PV), plays a significant role in the global energy transition required for decarbonization. Technological advancements in increasing efficiencies coupled with cost reductions through economies of scale made PV a cost-competitive energy source set to exceed the milestone of 1 TW globally deployed capacity in 2022. However, ongoing downward price pressure coupled with increasing service life expectations creates tremendous challenges for reliability engineers in ensuring the safe and reliable operation of PV modules and systems over the anticipated service life. Today's reliability research efforts aim for module lifetimes of up to 50 years. Still, our current tools fall short in accurately assessing degradation mechanisms and failure modes over such extended periods. We argue that the well-established PV reliability learning cycle needs to be accelerated to keep up with the rapid technological advancements and high expectations that are put on PV and its role in the global energy transition. In this article, we explore the evolution of the PV reliability learning cycle and highlight the significance that predictive modeling capabilities will have on future PV module reliability. We propose creating a unifying modeling framework - which once established will enable the holistic assessment of PV module reliability, accelerate the PV reliability learning cycle, and bring us closer to quantitative service life predictions of PV modules.
14 SOLAR ENERGY↗
Catalyzing deep decarbonization with federated battery diagnosis and prognosis for better data management in energy storage systems
Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified transportation and renewable electricity generation. However, significant challenges hinder the large-scale deployment of batteries. Conventional methods rely on centralized collection and processing of fleet-level data, leading to database size issues and privacy concerns due to potential data breaches. To enable scalable deployment of battery management systems, this article proposes a federated battery diagnosis and prognosis model, which distributes the processing of battery standard current-voltage-time-usage data in a privacy-preserving manner. Instead of transferring the raw data, this approach communicates only the locally processed parameters, thus reducing communication load and preserving data confidentiality. The federated model offers a paradigm shift in battery health management through privacy-preserving distributed methods for battery data processing and lifetime prediction, ensuring the reliable and sustainable deployment of lithium-ion batteries in a rapidly evolving world.
asset health management↗
Precious metal oxygen-evolving anodes for electrolytic reduction of metal oxides in molten LiCl-Li 2 O electrolyte
Understanding the electrochemical stability of oxygen-evolving anode materials in molten salt electrolytes is essential to enable decarbonized electrolytic reduction of metal oxides (e.g., used nuclear oxide fuels). Here, this work investigated three precious metals (Ir, Ru, and Pt) as oxygen-evolving anodes in molten LiCl-Li 2 O (99.0-1.0 wt%) at 650 °C. For consistent measurements, this work employed a three-electrode cell comprised of a two-phase Li-Bi (65-35 at%) reference electrode and a NiO counter electrode. Anodic polarization behavior of each anode was investigated via cyclic voltammetry (CV) and chronoamperometry. The onset potential for oxygen evolution was observed at E > 2.9 V (vs. Li/Li + ) for the Ir and Ru anodes and anodic current density was as high as 1.0 A cm -2 at 3.23 V. The dimensional stability of each anode was evaluated from long-term electrolysis experiments (10.0-32.1 h) at 3.23 V. Rapid consumption of the Pt anode was observed after the application of 26,453 C cm -2 with a reduction in diameter of about 15.8% due to the formation of a non-protective Li 2 PtO 3 compound. The formation of this compound was also observed during CV measurements as additional anodic waves at potentials more negative than that of oxygen evolution. In contrast, both the Ir and Ru anodes exhibited excellent dimensional stability with a reduction in diameter or thickness of less than 1.5% even after applying greater charge density of ~41,100 C cm -2 , demonstrating superior stability during oxygen evolution in the LiCl-Li 2 O electrolyte.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Opportunities for green hydrogen production with land-based wind in the United States
Hydrogen (H 2 ) is an efficient energy carrier and storage mechanism that can supply both stationary and transport energy demand. Rapidly declining renewable energy generation costs; technology innovations in wind, solar, battery storage, and electrolysis; and a global push for more sustainable and secure energy have driven increased interest in green H 2 production. In this study, we develop an H 2 scenario analysis tool to assist in rapid, high-resolution insights into future, green H 2 pathways to achieve policy goals and market competitiveness. Using this tool, we estimate H 2 production and costs for U.S., off-grid scenarios given varying policy and cost scenarios from 2025–2035. Results indicate that achieving economically competitive green H 2 production (below $\$$2/kg) is possible in 2030 with no policy incentives (one site achieves this target), while increasing policy support to include wind and green H 2 production tax credits enables widespread economic viability sooner, with sub-$\$$2/kg LCOH targets achieved by 2025 and 51.7% of sites achieving this target by 2035. Maximizing policy support through prevailing wage and apprenticeship credit multipliers enable widespread economic viability, including sub-$\$$2/kg of green H 2 by 2025 and even negative pricing by 2035. Regions with lowest LCOH values correspond to high wind resource areas and capacity factors. Achieving decarbonization goals with green H 2 depends on technology cost reductions and policy support, with a maximum average LCOH reduction of $\$$23.10 between no and maximum policy support scenarios, and a maximum average LCOH reduction of $\$$25.86 between current, conservative technology costs and 2035 projected technology cost assumptions.
08 HYDROGEN↗
Finite-time correlations boost large voltage angle fluctuations in electric power grids
Abstract Decarbonization in the energy sector has been accompanied by an increased penetration of new renewable energy sources in electric power systems. Such sources differ from traditional productions in that, first, they induce larger, undispatchable fluctuations in power generation and second, they lack inertia. Recent measurements have indeed reported long, non-Gaussian tails in the distribution of local voltage frequency data. Large frequency deviations may induce grid instabilities, leading in worst-case scenarios to cascading failures and large-scale blackouts. In this article, we investigate how correlated noise disturbances, characterized by the cumulants of their distribution, propagate through meshed, high-voltage power grids. For a single source of fluctuations, we show that long noise correlation times boost non-Gaussian voltage angle fluctuations so that they propagate similarly to Gaussian fluctuations over the entire network. However, they vanish faster, over short distances if the noise fluctuates rapidly. We furthermore demonstrate that a Berry–Esseen theorem leads to the vanishing of non-Gaussianities as the number of uncorrelated noise sources increases. Our predictions are corroborated by numerical simulations on realistic models of power grids.
24 POWER TRANSMISSION AND DISTRIBUTION↗
The Impact of Sound Ordinances on the Land-Based Wind Technical Potential of the United States
The rapid rise of sound ordinances has affected wind energy siting across state, county and local jurisdictions. Quantifying this impact on wind energy potential is required for effective energy planning. However, complex turbine sound modelling combined with evolving policies have contributed to limited understanding of these policies' impact on national wind technical potential. Here we develop an approach to evaluate wind turbine sound profiles across the United States and calculate setback distances from residential structures to translate sound-related policies into spatial turbine siting criteria. Compared to a baseline scenario that ignores sound, we find an 8% reduction in wind energy capacity when accounting for existing sound ordinances. Further, extrapolating a 45-A-weighted decibel (dBA) limit nationwide shows a 29% decline, disproportionately taken from high-quality and low-cost wind capacity. This reveals sound ordinances as a major factor in determining wind technical potential that could challenge US decarbonization goals reliant on wind energy.
17 WIND ENERGY↗
Offshore reanalysis wind speed assessment across the wind turbine rotor layer off the United States Pacific coast
Abstract. The California Pacific coast is characterized by considerable wind resource and areas of dense population, propelling interest in offshore wind energy as the United States moves toward a sustainable and decarbonized energy future. Reanalysis models continue to serve the wind energy community in a multitude of ways, and the need for validation in locations where observations have been historically limited, such as offshore environments, is strong. The U.S. Department of Energy (DOE) owns two lidar buoys that collect wind speed observations across the wind turbine rotor layer along with meteorological and oceanographic data near the surface to characterize the wind resource. Lidar buoy data collected from recent deployments off the northern California coast near Humboldt County and the central California coast near Morro Bay allow for validation of commonly used reanalysis products. In this article, wind speeds from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), the Climate Forecast System version 2 (CFSv2), the North American Regional Reanalysis (NARR), the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), and the analysis system of the Rapid Refresh (RAP) are validated at heights within the wind turbine rotor layer ranging from 50 to 100 m. The validation results offer guidance on the performance and uncertainty associated with utilizing reanalyses for offshore wind resource characterization, providing the offshore wind energy community with information on the conditions that lead to reanalysis error. At both California coast locations, the reanalyses tend to underestimate the observed rotor-level wind resource. Occasions of large reanalysis error occur in conjunction with stable atmospheric conditions, wind speeds associated with peak turbine power production (> 10 m s−1), and mischaracterization of the diurnal wind speed cycle in summer months.
17 WIND ENERGY↗
Abstract for CRADA between National Energy Technology Laboratory and Mattiq, Inc.
To decarbonize the chemicals and fuels industry, we require new and innovative technologies that can leverage renewable feedstocks including renewable electricity and renewable carbon sources, such as CO 2 . State-of-the-art (SOTA) CO 2 utilization technologies that can produce renewable chemicals and fuels, such as the electrochemical reduction of CO 2 , are still significantly lacking in efficiency, and are therefore not cost-competitive with existing infrastructure. The key bottleneck to cost-competitive chemicals and fuels sourced from CO 2 and renewable electricity is the lack of any efficient catalyst material. The National Energy Technology Laboratory (NETL) and Mattiq will collaborate in the development of an efficient catalyst material that can effectively convert CO 2 into products of interest. Specifically, NETL will utilize high-performance computing to greatly reduce the number of potential materials to be investigated by Mattiq ultrahigh-throughput experimental catalyst discovery framework. This work is poised to rapidly accelerate the development of novel and efficient CO 2 reduction electrocatalysts that can bring CO 2 utilization closer to commercial viability.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Examining Supply-Side Options to Achieve 100% Clean Electricity by 2035
The growing climate emergency requires a dramatic and rapid reduction of greenhouse gas emissions in the United States and internationally. This study evaluates a variety of 100% clean electricity system scenarios in 2035 that could put the United States on a path to economy-wide net-zero emissions by 2050, specifically focusing on technical requirements, challenges, and cost implications. The results highlight there are multiple approaches to cost-effectively achieve a net-zero carbon grid in 2035.
100% clean electricity↗
Co-Location of Cellulosic Bioethanol and Alcohol-to-Jet (ATJ) Production Facilities for Targeted Scale-Up of Sustainable Aviation Fuel (SAF) Production
Achieving aerospace industry net-zero emissions by 2050 requires rapid scaling of sustainable aviation fuel (SAF) production. Leveraging existing infrastructure, proven technologies like Alcohol-to-Jet (ATJ), and low carbon intensity (CI) feedstocks (e.g., switchgrass and miscanthus) can support this transition and help achieve near-term emissions reduction targets. This study evaluates the implications of lignocellulosic ethanol biorefinery siting and integration with petroleum refineries to produce SAF across 1000 sites randomly sampled from areas suitable for perennial grasses in the U.S. rainfed region. To better understand the logistics of material transport and handoffs, we integrated models of biomass harvest, transport, ethanol, and ATJ production in a stochastic framework based on Monte Carlo simulations to characterize SAF minimum selling price (MSP) and carbon intensity (CI), considering site-specific parameters (e.g., feedstock production, transportation, taxes, incentives). The results indicate trade-offs between MSP and CI across locations, with median MSP ranging from 7.9 to 12.8 USD·gal −1 and CI from −9.7 to 39.4 gCO 2 e·MJ −1 . Despite high estimated decarbonization costs (580 USD·tonCO 2 e −1 ), our results indicate that site-specific deployment of ATJ with low-CI feedstocks can improve sustainability outcomes. The framework provides a systematic approach to assess cost and sustainability trade-offs across locations, considering the end-to-end supply chain and supporting an informed investment in SAF production.
09 BIOMASS FUELS↗