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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

In-situ construction of ceria-metal/titanate heterostructure with controllable architectures for efficient fuel electrochemical conversion

Construction of ceria-metal/titanate heterostructure via exsolution is a promising strategy to improve the catalytic activity of titanate perovskites and broaden their applications in various energy conversion scenarios. However, the species exsolved after reduction are limited to reducible metal cations, such as Ni, Co, Fe, and precious metals. Herein, we report a modified exsolution approach for co-exsolving active oxides and metal nanoparticles from a titanate perovskite, La 0.8 Ce 0.1 Ni 0.4 Ti 0.6 O 3-δ (LCeNT). We highlight strained facet-specific CeO 2 cubes can be grown on the support after an air-annealing process with their morphology tunable by varying annealing temperature, whilst exsolution of Ni nanoparticles form subsequently following chemical/electrical reduction. An electrolyte-supported SOFC utilizing CeO 2 -Ni@LCeNT anode achieves maximum power density of 642 mW cm -2 at 900 °C in H 2 (~3% H 2 O). Exceptional robustness of the heterostructure is illustrated after running the cell in CH 4 (~3% H 2 O) for 20 h. Here this work demonstrates an intriguing pathway to constructing stable and active ceria-metal/titanate heterostructure for energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of Soluble Corrosion Products on Electrical Double Layer in LiCl-KCl Molten Salts

Corrosion in molten salts greatly hampers the application for renewable energy applications like molten salt reactors. To develop effective strategies for corrosion mitigation, understanding the interfacial structures and properties such as specific ion adsorption and electrical double layer capacitance are crucial. Using cyclic voltammetry and electrochemical impedance spectroscopy, we systematically studied the interfaces on various model electrodes including W (solid), Bi (liquid), and the stainless steel 316 in LiCl-KCl eutectic molten salts with the addition of corrosion species CrCl 2 and FeCl 2 . Both Cr 2+ and Fe 2+ ions increased electrical double layer capacitance, with Cr 2+ showing specific adsorption behavior and shifting the potential of zero charge, while Fe 2+ had minimal effect on point of zero charge. Two-working electrode measurements revealed increasing open-circuit potential and electrical double layer capacitance during the exposure of stainless steel 316, indicating its progressive corrosion and ion accumulation at the interface. X-ray photoelectron spectroscopy and Raman confirmed Cr enrichment at the interface. This work highlights the strong correlation between electrical double layer behavior and corrosion dynamics in molten salts and suggests electrical double layer capacitance as a sensitive, in situ indicator for corrosion monitoring.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Advanced Research Directions on AI for Energy

This AI for Energy report further details grand challenges that provide significant opportunities for energy applications across nuclear energy, the power grid, carbon management, energy storage, and energy materials over the next decade. The main conclusions and opportunities from this study are available in the Key Findings section of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Lithium Metal as an Anode in Electrochemical Energy Storage

The drastic environmental and economic costs of global warming have driven the necessity to reduce, if not eliminate, a dependency on oil and gas for energy applications. Alternative clean energy reliance has been initiated as a global investment for a more sustainable future. Part of this transitional effort is focused on energy storage via a rechargeable battery. High energy density storage is necessary for utilizing non-dispatchable green energy technologies, as well in the electric transition of our vehicle fleet. Further, understanding methods of extracting, manufacturing, and recycling lithium is necessary to lessen environmental impact. Lithium metal is often considered the “Holy Grail” of battery technology, due to its high theoretical capacity (3,860 mAh/g) and low electrochemical potential (-3.04 V vs. SHE). However, parasitic reactions lead to rapid and dangerous battery failure. Therefore, determining methods of stabilizing lithium metal is paramount for the transition to a greener future.

25 ENERGY STORAGE↗
DOE OSTI2024

Potential–Dependent BDAC Adsorption on Zinc Enabling Selective Suppression of Zinc Corrosion for Energy Storage Applications

Utility-scale zinc (Zn) batteries are a promising solution to address the problem of intermittency of renewable energy sources; however, Zn-metal anodes in these batteries suffer from capacity loss due to spontaneous corrosion of the Zn especially when high-surface area anode configurations are employed. Additionally, Zn dendrites are known to form during battery charging limiting the cycle-life of these batteries. Electrolyte additives have been explored that prevent aforementioned issues, but these too come at a cost, i.e., surface-blocking additives polarize the electrode surface leading to loss in the voltaic and energy efficiencies of the battery. In this contribution, a novel electrolyte additive, benzyldimethylhexadecylammonium chloride (BDAC), is investigated for its ability to suppresses corrosion of Zn in an acidic (pH = 3) electrolyte. An attribute of BDAC distinct from previously studied additives is that it selectively suppresses electrochemical activity when the Zn electrode is at its corrosion potential; however, during high-rate Zn deposition (charging) or stripping (discharging), BDAC is essentially deactivated and thus it does not appreciably polarize the electrode surface, thus minimizing voltaic efficiency losses. This selective corrosion suppression behavior is explored using slow-scan voltammetry, which reveals hysteresis implying a potential- or current-dependent BDAC adsorption mechanism in which BDAC reaches higher surface coverages when the partial currents at the Zn surface are low (e.g., at or near the corrosion potential), but BDAC coverage is reduced considerably when the Zn deposition or stripping rates are increased. Numerical simulations of the BDAC diffusion-adsorption process corroborate this mechanism. Ramifications of our approach to the selective suppression of Zn dendrites are discussed.

25 ENERGY STORAGE↗
DOE OSTI2021

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Bioinspired Supercharging of Photoredox Catalysis for Applications in Energy and Chemical Manufacturing

For more than a decade, photoredox catalysis has been demonstrating that when photoactive catalysts are irradiated with visible light, reactions occur under milder, cheaper, and environmentally friendlier conditions. Furthermore, this methodology allows for the activation of abundant chemicals into valuable products through novel mechanisms that are otherwise inaccessible. The photoredox approach, however, has been primarily used for pharmaceutical applications, where its implementation has been highly effective, but typically with a more rudimentary understanding of the mechanisms involved in these transformations. From a global perspective, the manufacture of everyday chemicals by the chemical industry as a whole currently accounts for 10% of total global energy consumption, and generates 7% of the world's greenhouse gases annually. In this context, the Bio-Inspired Light-Escalated Chemistry (BioLEC) Energy Frontier Research Center (EFRC) was founded to supercharge the photoredox approach for applications in chemical manufacturing aimed at reducing its energy consumption and emissions burden, by using bio-inspired schemes to harvest multiple electrons to drive endothermically uphill chemical reactions. The Center comprises a diverse group of researchers with expertise that includes synthetic chemistry, biophysics, physical chemistry, and engineering. Here the team works together to gain a deeper understanding of the mechanistic details of photoredox reactions while amplifying the applications of these light-driven methodologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗
DOE OSTI2025

Upcycling Polyethylene Waste Into Advanced Carbon Materials Used for Energy Storage Applications

Upcycling plastic into advanced carbons, such as graphite and graphene, offers attractive options to manage waste streams by converting the plastic into carbon electrode materials for energy storage devices. However, polyethylene (PE) is notoriously difficult to upcycle because it decomposes into light gases at approximately 350-400 °C which prevents processing it at higher temperatures to convert it into advanced carbons. This work addresses this challenge by oxidatively functionalizing PE between 300-330 C which stabilizes it for higher temperature processing into graphite & graphene. In addition, the graphite & graphene are tested as lithium-ion battery or supercapacitor electrodes where their electrochemical performances outperform commercial materials.

graphene↗
DOE OSTI2025

Upcycling Polyethylene Waste Into Advanced Carbon Materials Used for Energy Storage Applications

Upcycling plastic into advanced carbons, such as graphite and graphene, offers attractive options to manage waste streams by converting the plastic into carbon electrode materials for energy storage devices. However, polyethylene (PE) is notoriously difficult to upcycle because it decomposes into light gases at approximately 350-400 °C which prevents processing it at higher temperatures to convert it into advanced carbons. This work addresses this challenge by oxidatively functionalizing PE between 300-330 C which stabilizes it for higher temperature processing into graphite & graphene. In addition, the graphite & graphene are tested as lithium-ion battery or supercapacitor electrodes where their electrochemical performances outperform commercial materials.

graphene↗
DOE OSTI2022

Chemical compatibility of hollow ceramic cenospheres as thermal insulation for high-temperature thermal energy storage applications with molten nitrate salt

An effective insulation material that is both thermally and chemically stable in molten salts could transform the design of molten-salt-based thermal energy storage (TES) tanks. Most current molten salt TES tanks hold the metallic tank structure in direct contact with hot salt inventory, a design which leads to thermal expansion of the tank and triggers stresses that can lead to thermomechanical failures. With an internal insulation to lower the temperature at the tank structure, the extent of thermal expansion can be reduced, thereby reducing expansion-induced stresses and allowing for consideration of lower-cost tank structure materials. Conventional insulation materials are either 1) too porous and allow molten salts to permeate into the matrix, which significantly increases the thermal conductivity or 2) too dense and have a thermal conductivity that cannot provide sufficient thermal insulation. This paper presents an alternative thermal insulation concept using cenospheres which have an alumino-silicate structure. The cost analysis suggests that the low-density cenospheres can be one of the cheapest materials to provide cost-effective thermal insulation. The chemical compatibility of cenospheres is investigated in molten 60 wt% NaNO3/40 wt% KNO3 salt which is close to industrial-grade Solar Salt. This paper shows that diffusion of the sodium and potassium cations from the salt into the cenospheres occurs based on weight analysis, energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy. The cation diffusion breaks the bridging oxygen bonds and causes volume expansion of the microstructure which is responsible for the failure of the cenosphere particles. The chemical composition of the cenospheres is found to affect their compatibility with molten nitrate salt. A cenosphere product with low iron content showed the best compatibility with an average survival rate of 77.9% +/- 9.8% after 7 days of immersion in the molten nitrate salt. While even the low-iron cenospheres appear to require protection from direct molten salt contact, their slow degradation rate, closed-cell porosity, and low cost hold potential for effective use as internal tank insulation.

14 SOLAR ENERGY↗
DOE OSTI2021

Biomass-Derived Polymeric Binders in Silicon Anodes for Battery Energy Storage Applications

The demand for portable electronic devices has increased rapidly during the past decade, and has driven a concordant growth in battery production. Since their development as a commercial energy storage solution in the 1990s, lithium-ion batteries (LIBs) have attracted significant attention in both science and industry due to their long cycle life, high energy density, low self-discharge rate, and high working voltage. Production of LIBs requires large amounts of a polymeric binder – commonly polyvinylidene difluoride (PVDF) – for processing and performance purposes. However, since this material is petrochemically-derived, it is far from “green” or sustainable. On the other hand, polymers and their building blocks are found widely throughout nature and can be renewably sourced from biomass at low cost; therefore, replacing PVDF with biomass-derived binders is a promising approach to reduce the environmental footprint of LIBs. Additionally, polymer binders play a critical role in next-generation battery performance. For instance, silicon (Si) is a promising high-capacity anode material for LIBs because of its high theoretical capacity (4200 mA h g –1 ), low working potential, and high abundance in Earth's crust. However, its huge volume change during charge/discharge tends to result in a shortened cycle life, since conventional binders interact only weakly with silicon's native surface and cannot maintain long-term integrity of the electrode. Naturally derived polymers have found better success in this role due to their high structural advantages. In this review, we summarize recent developments in silicon anode binders derived from various biomass sources, with a focus on polymer properties and their effect on battery performance. Further, we propose various perspectives based on our own assessment of these works, and provide a brief commentary on the future outlook of the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

Digital twin is often viewed as a technology that can assist engineers and researchers make data-driven system and network-level decisions. Across the scientific literature, digital twins have been consistently theorized as a strong solution to facilitate proactive discovery of system failures, system and network efficiency improvement, system and network operation optimization, among others. With their strong affinity to the industrial metaverse concept, digital twins have the potential to offer high-value propositions that are unique to the energy sector stakeholders to realize the true potential of physical and digital convergence and pertinent sustainability goals. Although the technology has been known for a long time in theory, its practical real-world applications have been so far limited, nevertheless with tremendous growth projections. In the energy sector, there have been theoretical and lab-level experimental analysis of digital twins but few of those experiments resulted in real-world deployments. There may be many contributing factors to any friction associated with real-world scalable deployment in the energy sector such as cost, regulatory, and compliance requirements, and measurable and comparable methods to evaluate performance and return on investment. Those factors can be potentially addressed if the digital twin applications are built on the foundations of a scalable and interoperable framework that can drive a digital twin application across the project lifecycle: from ideation to theoretical deep dive to proof of concept to large-scale experiment to real-world deployment at scale. This paper is an attempt to define a digital twin open architecture framework that comprises a digital twin technology stack (D-Arc) coupled with information flow, sequence, and object diagrams. Those artifacts can be used by energy sector engineers and researchers to use any digital twin platform to drive research and engineering. This paper also provides critical details related to cybersecurity aspects, data management processes, and relevant energy sector use cases.

Gourisetti, Sri, Nikhil Gupta (ORCID:0000000188778↗
DOE OSTI2024

Improved Methods for Modeling Functional Transition Metal Compounds in Complex Environments: Ground States, Excited States, and Spectroscopies

Rapid advances in energy applications require new theory and computational models to provide guidance for interpretation of experimental results and mechanistic understanding. New theory development is necessary to treat systems of increasing complexity, size, and relevance to real applications. Functional transition metal compounds, including molecules, clusters, nanoparticles, surfaces, and solids, provide particular promise for magnetic, optical, and catalytic applications. However, such systems can be exceptionally challenging to model. To make progress in understanding and designing transition metal compounds for energy applications, theory must be able to simulate such systems in complex environments, as well as simulate the spectra of such complex systems to provide direct connections with experiment. Leveraging the independent expertise of the team’s members, this project aimed to make inroads to the theoretical and computational challenges associated with studying transition metal compounds, their reaction chemistry, photophysics and photochemistry, and response to spectroscopic interrogation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Modulating Operational Conditions to Mitigate Deactivation in Formate Dehydrogenation on Pd Phases

In heterogeneous catalysis, poisoning by surface-bound intermediates poses a major barrier to sustained catalyst performance in (de)hydrogenation reactions. Formate/bicarbonate systems, as liquid organic hydrogen carriers (LOHCs), offer a CO 2 -integrated, low-temperature pathway for hydrogen storage and release, making them attractive for circular energy applications. However, their lower hydrogen density and susceptibility to catalyst deactivation limit their competitiveness compared to conventional LOHCs like methylcyclohexane. Here, this study investigates the mechanistic origins of formate (HCOO – ) dehydrogenation and associated deactivation on Pd interfaces. Using density functional theory (DFT) simulations, we show that under thermocatalytic conditions, strongly bound formate accumulates on the catalyst surface (Pd(111)), blocking active sites, raising activation barriers, and leading to progressive performance loss. Because formate adsorption involves charge transfer, we exploit its sensitivity to electronic structure by modulating the electrochemical potential of the catalyst. Our results reveal that hydrogen transfer from water and formate exhibits opposing potential dependencies, providing insights into the opposing driving forces behind both catalytic activity and poisoning. To further probe this phenomenon, we examine electrochemically induced phase transitions in Pd, focusing on PdO(100) and PdH(110), which are stable under oxidizing and reducing potentials, respectively, and demonstrate enhanced dehydrogenation activity between −0.4 and 0.2 V vs standard hydrogen electrode (SHE). Complementary thermal treatments help decouple kinetic and thermodynamic contributions to intermediate binding. These findings underscore the critical role of the catalyst phase and external stimuli in dictating poison-active site interactions and highlight phase engineering as a promising strategy to mitigate deactivation. This work offers mechanistic insights and design principles for developing more resilient and efficient catalysts for LOHC applications under realistic operating conditions.

Pd phase↗