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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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The Xcel-NLR Wind Electrolysis R&D Project is designed to gain knowledge and insight about producing hydrogen from electricity for use as a vehicle fuel and as a "stored wind". The project will analyze producing hydrogen directly from wind as well as from the electric grid. In addition, it will look at storing hydrogen and then using it to put electricity back onto the grid.
Optimal operation of lithium-ion batteries requires robust battery models for advanced battery management systems (ABMS). A nonlinear model predictive control strategy is proposed that directly employs the pseudo-two-dimensional (P2D) model for making predictions. Using robust and efficient model simulation algorithms developed previously, the computational time of the nonlinear model predictive control algorithm is quantified, and the ability to use such models for nonlinear model predictive control for ABMS is established.
New electrolytes are critical for high‐energy lithium (Li)–sulfur (S) batteries (LSBs) to ensure their stability against Li metal anode and polysulfides (PSs) shuttling which hinder the large‐scale application of LSBs. In this study, the design principle of moderately solvating electrolytes (MSEs) for LSBs is demonstrated by using a multiple‐solvent system comprising of a highly solvating solvent, a weakly solvating solvent, and a non‐solvating solvent to create a well‐balanced electrolyte system. This resulting electrolyte significantly improves the cycle life of LSBs, achieving 300 cycles, which is twice as long as that of similar cells with the conventional electrolyte and it also ensures stable calendar life for at least seven months. The optimal MSE forms robust passivation layers enhancing the structural integrity of both S and Li metal electrodes after cycling. These virtues effectively hinder parasitic side reactions and self‐discharge behavior of LSBs. This electrolyte design principle is versatile and can be applied to other battery chemistries, providing a potential path toward the development of a more efficient and stable battery system. By addressing key challenges such as the instability of electrodes and shuttling of polysulfides, this electrolyte approach offers promising solutions for advancing LSB technology.
This report considers the technological and market pathways that will enable better use of photovoltaic (PV) electricity as fuel for future transportation demand. Most of the pathways identified will require collaborative research and development (R&D) efforts to improve the capabilities of multiple technologies, including PV, energy storage, vehicles, electrolyzers, electrofuels, and infrastructure. For plug-in electric vehicles (PEVs), technologies that enable wide-scale managed and coordinated charging are among the highest priorities for continued research, development, and deployment in the near term. Furthermore, managed and coordinated charging capabilities are foundational for future vehicle-to-grid (V2G) functionality in the long term. For hydrogen fuel cell electric vehicles (FCEVs), the use of PV electricity for electrolysis provides an opportunity to increase PV deployment. For rail, air, and maritime transportation, the feasibility of increased PV use varies in the near term; opportunities for synergies with solar include the electrification of rail, increased reliability from airport microgrids, and switching from heavy fuel oil to clean maritime electrofuels made from PV-based hydrogen. Over the longer term, battery swap stations for electric airplanes and the co-location of solar with hydrogen fueling stations at shipping ports may enable greater synergies between PV and transportation.
Energy storage is becoming the chief barrier to the utilization of more renewable energy sources on the grid. With independent service operators aiming to acquire gigawatts in the next 10–20 years, there is a large need to develop a suite of new storage technologies. Redox flow batteries (RFB) may be part of the solution if certain key barriers are overcome. This review focuses on a particular kind of RFB based on nonaqueous media that promises to meet the challenge through higher voltages than the organic and aqueous variants. This class of RFB is divided into three groups: molecular, macromolecular, and redox-targeted systems. The growing field of theoretical modeling is also reviewed and discussed.
National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.
Lithium-ion batteries with silicon anodes promise high energy density but are limited by calendar lifetime. Reducing the long iteration time to obtain experimental results requires predicting calendar lifetime early in a cell's life. In this study, we demonstrate that lightweight machine learning models with feature engineering can provide calendar lifetime estimates from early electrochemical signals. After 1 month of electrochemical aging, the best models achieve 10% error in calendar-life prediction and can separate "bad" from "good" lifetime cells with a mean F1 score of 0.857. As battery systems exhibit inherent variability, four methods for uncertainty quantification are compared, and confidence intervals are demonstrated with an uncertainty of +-3.6 months in lifetime prediction. A feature importance analysis indicates that early patterns in voltage decay are the strongest indicators of calendar lifetime. Finally, this modeling approach has high error when generalizing to new electrode chemistries or testing conditions but with appropriately low confidence.
A pseudo-2d model using COMSOL Multiphysics® software is developed to simulate performance and performance degradation of Li-ion batteries consisting of layered and olivine cathodes with graphite anode when subjected to peak shaving grid service. Multiple degradation pathways are considered, including solid electrolyte interphase (SEI) formation and breakdown at the anode, cathode dissolution and its synergistic effect on SEI formation at the anode. The model is validated by simulating commercial cylindrical cell performance. A global model is developed to simulate performance across all chemistries, along with individual chemistry models using global model parameters as initial values. There is good agreement between these models for various optimization parameters such as SEI equilibrium potential, cathode dissolution exchange current density, solvent diffusivity in the SEI and SEI ionic conductivity. To circumvent time constraints related to the COMSOL model, a 0d global model is developed which fits data well and provides more clarity on differences in cathode dissolution exchange current density. Again, good agreement for various optimization parameters is obtained among the COMSOL global & individual chemistry models and the 0-d model. The lessons learned from the physics-based model is used to develop a top down statistics-based model using current, voltage and anode volumetric change per mole lithium intercalated, along with their interactions as degradation predictors. This model predicts out of sample degradation for multiple grid services and electric vehicle drive cycle with high accuracy and provides the pathway to develop an efficient battery management system combining machine learning and findings from physics-based computationally intensive algorithms.
Li-ion batteries are crucial for the global energy transition to renewables; however, their scalability is limited by the supply of key elements used in commercial cathodes (e.g., Ni, Mn, Co, P). Therefore, there is an urgent need for next-generation cathodes composed of widely available and industrially scalable elements. Here, we introduce a Li-rich cathode based on the known material Li 2 FeS 2 , composed of low-cost elements (Al, Fe, S) that are globally mined and refined at an industrial scale. The substitution of redox-inactive Al 3+ for Fe 2+ achieves remarkably high degrees of anion redox, which, in turn, yields high gravimetric capacity (≈450 mAh·g –1 ) and energy density (≳1000 Wh·kg –1 ). We show that Al 3+ enables high degrees of delithiation by stabilizing the delithiated state, suppressing phase transformations that would otherwise prevent deep delithiation and extensive anion redox. This mechanistic insight offers new possibilities for developing scalable, next-generation Li-ion battery cathodes to meet pressing societal needs.
The Distribution System Operator with Transactive (DSO+T) study conducted a large-scale simulation of over 60,000 customers in a region the size of Texas to demonstrate the effective coordination of distributed energy resources (DERs) in commercial and residential buildings. The integrated simulation included both the bulk (wholesale generation and transmission) and distribution systems. The DERs (including batteries, electric vehicles, air conditioning, and water heaters) participated in a transactive energy retail market that was integrated into an existing competitive wholesale market. The engineering and economic performance of the resulting demand flexibility was evaluated over annual simulations for both moderate and high renewable generation scenarios. A detailed parametric cost model was developed to enable detailed economic analysis of key stakeholders. In addition, fixed and dynamic customer tariffs were designed and applied to the customer population. This allowed the impact on annual customer bills to be analyzed for various building types (residential versus commercial; single- versus multi-family). This paper presents results showing the relative flexibility of batteries, electric vehicles, and building loads throughout the year and under different renewable scenarios. This feeds a detailed breakdown of the impact this flexibility has on the operating costs of the grid and the resulting net economic benefit. Finally, the study showed that practically all customer classes (including non-participating customers) save money under the proposed demand flexibility scheme. The study found overall net annual economic savings of $3.3-5.0B for a region the size of Texas equating to average customer bill savings of 10-16%.
We report in laser-produced high-energy-density plasmas, large-scale strong magnetic fields are spontaneously generated by the Biermann battery effects when temperature and density gradients are misaligned. Saturation of the magnetic field takes place when convection and dissipation balance field generation. While theoretical and numerical modeling provide useful insight into the saturation mechanisms, experimental demonstration remains elusive. In this letter, we report an experiment on the saturation dynamics and scaling of Biermann battery magnetic field in the regime where plasma convection dominates. With time-gated charged-particle radiography and time-resolved Thomson scattering, the field structure and evolution as well as corresponding plasma conditions are measured. In these conditions, the spatially resolved magnetic fields are reconstructed, leading to a picture of field saturation with a scaling of $B ~ 1/L_T$ for a convectively dominated plasma, a regime where the temperature gradient scale ($L_T$) exceeds the ion skin depth.
There has been significant recent interest in studying multiscale characteristics of current and next-generation batteries, including lithium-metal and lithium-sulfur batteries. Advances in computing power make researchers believe that the detailed multiscale models can be efficiently simulated to arrive at the insights for the degradation and performance loss; however, this is not true and special attention needs to be paid to local singularities, boundary layers, moving boundaries, etc. This article presents 2D examples that illustrate the importance of grid convergence studies, provides well-defined detailed models to test the efficiency of numerical schemes, and discusses the associated simulation challenges.
Abstract The dependence on lithium-ion batteries leads to a pressing demand for advanced cathode materials. We demonstrate a new concept of layered-rocksalt intergrown structure that harnesses the combined figures of merit from each phase, including high capacity of layered and rocksalt phases, good kinetics of layered oxide and structural advantage of rocksalt. Based on this concept, lithium nickel ruthenium oxide of a main layered structure ( R $$\bar{3}$$ 3 ¯ m ) with intergrown rocksalt ( Fm $$\bar{3}$$ 3 ¯ m ) is developed, which delivers a high capacity with good rate performance. The interwoven rocksalt structure successfully prevents the anisotropic structural change that is typical for layered oxide, enabling a nearly zero-strain operation upon high-capacity cycling. Furthermore, a design principle is successfully extrapolated and experimentally verified in a series of compositions. Here, we show the success of such layered-rocksalt intergrown structure exemplifies a new battery electrode design concept and opens up a vast space of compositions to develop high-performance intergrown cathode materials.
LiNi x Co y MnzO 2 (x+y+z=1)||graphite lithium-ion battery (LIB) chemistry promises practical applications. However, its low-temperature (≤ –20°C) performance is poor because the increased resistance encountered by Li + transport in and across the bulk electrolytes and the electrolyte/electrode interphases induces capacity loss and battery failures. Though tremendous efforts have been made, there is still no effective way to reduce the charge transfer resistance (R ct ) which dominates low-temperature LIBs performance. In this work, we propose a strategy of using low-polarity-solvent electrolytes which have weak interactions between the solvents and the Li + to reduce R ct , achieving facile Li + transport at sub-zero temperatures. The exemplary electrolyte enables LiNi 0.8 Mn 0.1 Co 0.1 O 2 ||graphite cells to deliver a capacity of ≈113 mAh g –1 (98% full-cell capacity) at 25°C and to remain 82% of their room-temperature capacity at –20°C without lithium plating at 1/3C. They also retain 84% of their capacity at –30°C and 78% of their capacity at –40°C and show stable cycling at 50°C.
The phase separation dynamics in graphitic anodes significantly affects lithium plating propensity, which is the major degradation mechanism that impairs the safety and fast charge capabilities of automotive lithium-ion batteries. In this study, we present comprehensive investigation employing operando high-resolution optical microscopy combined with non-equilibrium thermodynamics implemented in a multi-dimensional (1D+1D to 3D) phase-field modeling framework to reveal the rate-dependent spatial dynamics of phase separation and plating in graphite electrodes. Here we visualize and provide mechanistic understanding of the multistage phase separation, plating, inter/intra-particle lithium exchange and plated lithium back-intercalation phenomena. A strong dependence of intra-particle lithiation heterogeneity on the particle size, shape, orientation, surface condition and C-rate at the particle level is observed, which leads to early onset of plating spatially resolved by a 3D image-based phase-field model. Moreover, we highlight the distinct relaxation processes at different state-of-charges (SOCs), wherein thermodynamically unstable graphite particles undergo a drastic intra-particle lithium redistribution and inter-particle lithium exchange at intermediate SOCs, whereas the electrode equilibrates much slower at low and high SOCs. These physics-based insights into the distinct SOC-dependent relaxation efficiency provide new perspective towards developing advanced fast charge protocols to suppress plating and shorten the constant voltage regime.
Hydrogen fuel cell-powered off-road vehicles can replace hydrocarbon-powered off-road vehicles to reduce carbon dioxide and criteria pollutant emissions in the agriculture, construction, and mining industries. Vehicle manufacturers and customers recognize health and environmental benefits of emissions reductions but are ultimately compelled by the total cost of ownership of their vehicles. In this study, we conduct a technoeconomic evaluation for three hallmark off-road vehicles, tractors, wheel loaders, and excavators, comparing vehicles with hydrogen fuel cell + battery hybrid powertrains to traditional diesel powertrains. Stakeholder-valued performance metrics include fuel cell engine power, engine durability, hydrogen consumption rate, hydrogen storage system volume, and energy-regenerative drivetrain efficiency. The total cost of ownership includes capital, operating and maintenance, fuel, and fuel storage costs. State-of-the-art fuel cell powered wheel loaders and excavators are currently cost competitive with diesel platforms. If targeted improvements to cost, performance, and durability improvements of fuel cell stacks and storage systems are achieved, fuel cell systems would be cost competitive for tractors and significantly lower total cost of ownership options for wheel loaders and excavators.
A primary barrier preventing repetitive fast charging of Li-ion batteries is lithium metal plating at the graphite anode. One approach toward mitigating Li metal deposition is the deliberate modification of the graphite anode surface with materials demonstrating high overpotentials unfavorable for Li metal nucleation, such as Ni or Cu nanoscale films. This research explores Ni and Cu surface coatings at different areal loadings (3 or 11 μg cm -2 ) on the electrochemistry of graphite/LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) type Li-ion batteries. Extended galvanostatic cycling of control and metal-coated electrodes in graphite/NMC622 pouch cells are conducted under high rate conditions. Based on the overpotential of Li deposition on metal foil, both Ni and Cu treatments were anticipated to result in reduced lithium deposition. The higher metal film loadings of 11 μg cm -2 Ni- or Cu-coated electrodes exhibit the highest capacity retention after 500 cycles, with mean improvements of 8% and 9%, respectively, over uncoated graphite electrodes. Li plating quantified by X-ray diffraction indicates that the metal films effectively reduce the quantity of plated Li compared to untreated electrodes, with 11 μg cm -2 Cu providing the greatest benefit.
This study presents the design, construction, and simulation of a mobile muon detector tailored for geological overburden characterization. The detector employs plastic scintillator paddles with silicon photomultipliers (SiPMs) and a QuarkNet data acquisition system, offering a portable solution suitable for remote field deployment. The simulator’s modular aluminum frame allows for adjustable geometry and directional sensitivity, while its battery system supports over a week of autonomous operation. Preliminary experimental tests confirmed that its muon flux measurements were consistent with theoretical expectations. A comprehensive simulation framework using Geant4 and CORSIKA was developed to model detector response and overburden effects. Analytical and Monte Carlo methods were used to assess quadrant resolution and infer muon directionality. This work lays the foundation for future overburden mapping and supports the development of reconstruction algorithms for geological applications.