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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Beyond Price-Taker: Multiscale Optimization of Wind and Battery Integrated Energy Systems

Integrating renewable energy into the electric grid is challenging due to the intermittency and variability of wind and other non-dispatchable resources. Integrated energy systems (IESs) combine multiple energy technologies (e.g., fossil, nuclear, renewables, storage) to reduce costs and improve flexibility and reliability. However, standard techno-economic analysis (TEA) methods often overestimate the benefits of IESs because they fail to account for energy market adjustments. This paper systematically studies the limitations of the prevailing price-taker assumption for TEA and optimization of hybrid energy systems. As an illustrative case study, we retrofit an existing wind farm in the RTS-GMLC test system (which loosely mimics the Southwest U.S.) with battery energy storage to form an IES. We show that the standard price-taker model overestimates the electricity revenue and the net present value (NPV) of the IES up to 178% and 30.4%, respectively, compared to our more rigorous multiscale optimization. These differences arise because introducing storage creates a more flexible resource that impacts the larger wholesale electricity market. Moreover, this work highlights the impact of the IES has on the market via various strategic bidding, and underscores the importance of moving beyond price-taker for optimal storage sizing and TEA of IESs. We conclude by discussing opportunities to generalize the proposed framework to other IESs, and highlight emerging research questions regarding the complex interactions between IESs and markets.

25 ENERGY STORAGE↗
DOE OSTI2023

High-Entropy Surface Complex Stabilized LiCoO 2 Cathode

In this study, elevating the charge voltage of LiCoO 2 increases the energy density of batteries, which is highly enticing in energy storage implementation ranging from portable electronics to e-vehicles. However, hybrid redox reactions at high voltages facilitate oxygen evolution, electrolyte decomposition and irreversible phase change, and accordingly lead to rapid battery capacity decay. Here significantly improved high-voltage cycling stability of Mg-Al-Eu co-doped LiCoO 2 is demonstrated. It is found that element co-doping induces a near-surface high-entropy zone, including an innately thin disordered rock-salt shell and a dopant segregation surface. The high-entropy complex can effectively suppress oxygen evolution and near-surface structure deconstruction. The phase change reversibility between O3 and H1-3 and thermal stability of the cathode are greatly enhanced as well. As a result, the co-doped LiCoO 2 exhibits a remarkable cycling performance, retaining 86.3% and 72.0% of initial capacity over 800 and 2000 cycles, respectively, with a high cut-off voltage of 4.6 V. The feasible co-doping approach broadens the perspective for the development of stable lithium-ion batteries with high operating voltages.

25 ENERGY STORAGE↗
DOE OSTI2023

Envisioning the Future Renewable and Resilient Energy Grids—A Power Grid Revolution Enabled by Renewables, Energy Storage, and Energy Electronics

Today’s power grids are facing tremendous challenges because of the ever-increasing power demand, system complexity, infrastructure cost, knowledge base, and policy and regulatory issues to achieve supply–demand power balance and resiliency with respect to more frequent extreme weather events and cyberattacks. It is particularly challenging when the transition toward 100% intermittent renewable energy sources is considered. Many countries are calling for building up more transmission and distribution lines to increase power delivery capacities. This article is an attempt to answer two urgent questions: Is more transmission and distribution infrastructure really needed to meet the increasing power demand? What kind of future grid infrastructure should we envision and build? This article attempts to answer these questions and proposes the concept of community-centric asynchronous renewable and resilient energy grids. By clearly differentiating the concepts of grid resilience and reliability, the importance of building resilient power electronics’ devices and robust system-level control algorithms to achieve 100% renewable energy integrated resilient grids is presented. To identify the shortcomings and propose advancements, power electronics’ technologies are categorized using the proposed concepts of natural source frequencies (NSf), energy storage, direct energy conversion/control and fault protection (DeCaFp), and high-efficiency energy consumption and buffering (heECaB) technology. The ability of networked microgrids to greatly reduce power outages and power system restoration time is demonstrated by leveraging robust decentralized and centralized control algorithms, identified through a comprehensive literature review. Future research areas are proposed to further enhance grid stability, controllability, cybersecurity, and protection against faults in the presence of 100% renewable sources by leveraging the advanced capabilities of NSf, DeCaFp, and heECaB devices and system-level control algorithms.

14 SOLAR ENERGY↗
DOE OSTI2022

Design and implementation of dynamic I/O control scheme for large scale distributed file systems

In this paper, we have analyzed the input/output (I/O) activities of Cori, which is a high-performance computing system at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. Our analysis results indicate that most users do not adjust storage configurations but rather use the default settings. In addition, owing to the interference from many applications running simultaneously, the performance varies based on the system status. To configure file systems autonomously in complex environments, we developed DCA-IO, a dynamic distributed file system configuration adjustment algorithm that utilizes the system log information to adjust storage configurations automatically. Our scheme aims to improve the application performance and avoid interference from other applications without user intervention. Moreover, DCA-IO uses the existing system logs and does not require code modifications, an additional library, or user intervention. To demonstrate the effectiveness of DCA-IO, we performed experiments using I/O kernels of real applications in both an isolated small-sized Lustre environment and Cori. Our experimental results shows that our scheme can improve the performance of HPC applications by up to 263% with the default Lustre configuration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
DOE OSTI2023

Comparative Density Functional Theory Study of Magnetic Exchange Couplings in Dinuclear Transition-Metal Complexes

Multicenter transition-metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information-processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular, the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory is the only practical electronic structure method for evaluating the J coupling. Here, we assess the accuracy of different density functional approximations for predicting the magnetic couplings of eight dinuclear transition-metal complexes, including five dimanganese, two dicopper, and one divanadium with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r 2 SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids tested in this work have a tendency to over-correct the error in magnetic coupling parameters from the Perdew–Burke–Ernzerhof (PBE) GGA as seen for manganese complexes. The performance of local hybrid density functionals shows no improvement in terms of bias and is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r 2 SCAN meta-GGAs are found to perform as well as benchmark global hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error or delocalization error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Role of inner solvation sheath within salt–solvent complexes in tailoring electrode/electrolyte interphases for lithium metal batteries

Functional electrolyte is the key to stabilizing the highly reductive lithium (Li) metal anode (LMA) and high voltage cathode for long life, high energy-density rechargeable Li metal batteries (LMBs). However, fundamental knowledge of the interaction principles between reactive electrodes and electrolytes is still limited. Recently localized high-concentration electrolytes (LHCEs) are emerging as promising electrolyte design strategies for LMBs. They can also serve as an ideal platform for understanding the reactivity characteristics of the inner solvation sheath on electrode surfaces due to their unique solvation structures. Here, we study the effects of a series of LHCEs with model electrolyte solvents (carbonate, sulfone, phosphate and ether) in high voltage LMBs. Varied electrode stabilities exhibited in different LHCEs indicate the intricate synergies between the salt and the solvent on electrode surfaces. Experimental and theoretical analyses reveal an intriguing general rule that the strong interactions between the salt and the solvent in the inner solvation sheath promote their intermolecular proton/charge transfer reactions, which dictates the properties of the electrode/electrolyte interphases and thus the battery performances.

Solvation sheath, salt-solvent complex, electrode/↗
DOE OSTI2022

Elucidating Instabilities Contributing to Capacity Fade in Bipyridine‐Based Materials for Non‐aqueous Flow Batteries

Abstract Metal‐based non‐aqueous redox flow batteries have the potential for long‐term energy storage if stability requirements can be achieved. One such stability issue in metal coordination complexes arises from ligand shedding in the anolyte upon reduction. Recognizing that the free ligands are relatively more stable than the metal coordination complex under highly reducing conditions, we evaluated a family of metal‐free bipyridinium materials as flow battery anolytes with the corresponding iron coordination complex as the catholyte. Bipyridinium compounds were functionalized for increased electrochemical stability, cycled in flow cells to understand efficiencies, and analyzed for degradation products. Methylation of the bipyridine nitrogens increased electrochemical stability yet left the reduced molecule susceptible to radical‐induced bond cleavage. Subsequent functionalization of bipyridine with carbomethoxy groups resulted in good battery performance with 96 % Coulombic and 90 % voltage efficiency, and improved cycling stability over a methoxy‐substituted anolyte with 14 % vs 36 % capacity fade in the first charge‐discharge cycle.

Kolesnichenko, Claudina X.↗
DOE OSTI2020

Influence of physical and chemical hydrology on bioremediation of a U-contaminated aquifer informed by reactive transport modeling incorporating 238 U/ 235 U ratios

Microbially-catalyzed reductive immobilization of aqueous uranium (U) as a solid phase has been proposed as a U remediation technique. Both laboratory and field experiments have demonstrated that this reduction reaction alters the 238 U/ 235 U ratio, producing a 238 U-enriched U(IV) solid. In contrast, other major U reactive transport processes fractionate these isotopes much less. This suggests the potential to quantify the extent of bioreduction occurring in groundwater containing U using the 238 U/ 235 U ratio, which would substantially improve upon current practices largely relying on U concentration measurements alone. Current reactive transport models for uranium dynamics include only concentration measurements, which are strongly influenced by highly coupled reactive transformation and aqueous transport processes. The complex physical and chemical behavior of U potentially compromises such quantitative analysis of U storage and release. Here we report the first numerical reactive transport model which explicitly incorporates variations in the 238 U/ 235 U ratio of U and demonstrates improved interpretation of the principal chemical reactions and groundwater transport processes affecting the subsurface mobility and distribution of this widespread contaminant. Recent U bioreduction studies performed in a contaminated aquifer in Rifle, Colorado, USA applied Rayleigh distillation models to interpret U stable isotope fractionation observed as a result of acetate amendment. These simplified models were unable to resolve the spatiotemporal pattern of U isotope fractionation recorded in the aqueous solutes. Here, we employ the multi-component, isotope-enabled CrunchTope reactive transport software to interpret these measured U isotope ratios, and demonstrate accurate reproduction of observed trends in both geochemistry and 238 U/ 235 U ratios for two consecutive years of field experiments. Overall, our results indicate that accurately modeling both the U concentration and isotope ratio distributions greatly constrains the parameter space of the model. We find that the transport properties of U in the Rifle aquifer are governed by the presence of low-permeability regions, which the isotopes are uniquely sensitive to. When U reduction is spatially constrained by these low-permeability regions, the shift in the 238 U/ 235 U ratio becomes more muted. Accurate modeling of observed U isotope ratios thus provides a powerful means to better understand bioremediation, and the current study serves to advance the application of this novel method.

238U/235U↗
DOE OSTI2025

Quantifying the Reactivity of Isolated Li x Si Domains in Si Anodes Using Operando NMR

The use of Si anodes can greatly improve the energy density of Li-ion batteries. However, understanding and mitigation of calendar aging remains a barrier to commercialization. Here, in this short report, we utilize operando Nuclear Magnetic Resonance (NMR) spectroscopy to detect and quantify lithium silicides (Li x Si) as they form and react within Si anodes in pouch cells during calendar aging. We provide direct experimental evidence of complex aging phenomena in the Si anodes, including both SEI growth and dissolution during storage. Formation of electrochemically isolated Li x Si is also observed, as indicated by the partial persistence of highly lithiated phases after the cell is discharged. Remarkably, we show that these isolated domains can themselves self-discharge over time, suggesting that their detection can be challenging in post-mortem studies. Finally, we show that aging outcomes depend heavily on the type of silicon particles contained within the electrode, and that certain surface coatings can help decrease the reactivity between lithium silicides and the electrolyte.

Li-ion battery↗
DOE OSTI2022

Beyond Local Solvation Structure: Nanometric Aggregates in Battery Electrolytes and their Effect on Electrolyte Properties

Electrolytes are an essential component of all electrochemical storage and conversion devices, such as batteries. In the history of battery development, the complex nature of electrolytes has often been a bottleneck. Fundamental knowledge of electrolyte systems encompasses elucidation of structure-property relationships of the solution species. Recently, nanometric aggregates have been observed in several classes of electrolytes, including super-concentrated, redox-flow, multivalent, polymer, and ionic liquid-based electrolytes. Compared with the well-studied local solvation structures such as contact ion pairs and solvent-separated ions, these aggregates impose unique effects on the ion distribution and transport both within bulk electrolytes and at electrode/electrolyte interfaces. This Perspective highlights the discovery of the aggregates in various battery electrolytes and their impact on electrolyte properties. We also present an outlook for future studies of this emerging field of nanometric aggregates and the need for the development of new experimental and computational tools to study their properties.

Yu, Zhou↗
DOE OSTI2025

Unravelling electro-chemo-mechanical interplay in layered oxide cathode degradation in solid-state batteries

Solid-state batteries (SSBs) hold notable promise for advancing energy storage technologies. However, their commercial viability is limited by the poor cycle stability and complex degradation mechanism. This study underscores the pivotal role of electro-chemo-mechanical interactions in driving the failure of SSBs. Leveraging advanced x-ray imaging and spectroscopy techniques, we analyzed LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes from cycled Li x In||Li 6 PS 5 Cl (LPSC)||NMC811 SSBs, uncovering the interplay between microstructure, chemical heterogeneity, mechanical characteristics, and electrochemical performance. Our results show that revealing electro-chemo-mechanical interactions is essential to develop strategies to suppress the degradation of SSBs. Particularly, we revisit a LiNbO 3 (LNO) coating layer to mitigate electrochemical degradation. The LNO@NMC811 cathode retains 116 milliampere-hours per gram after 200 cycles, showing excellent stability, while the uncoated NMC811 cathode keeps degrading over time, with suppressed chemical heterogeneity and mechanical failure. This work highlights the importance of synergizing advanced material design with coating techniques, ensuring uniform lithium flux and improving mechanical properties to achieve stable, high-performance SSBs.

Zheng, Xueli [SLAC National Accelerator Laboratory↗
DOE OSTI2021

RF Harmonic Kicker R&D Demonstration and Its Application to the RCS Injection of the EIC

The Rapid Cycling Synchrotron (RCS) of the Electron-Ion Collider (EIC) at Brookhaven National Laboratory (BNL) is an accelerating component of the electron injection complex, which provides polarized electrons in electron-ion collisions in the main Electron Storage Ring (ESR). We present the injection scheme into the RCS based on an ultra-fast harmonic kicker, whose "five odd-harmonic modes" prototype was developed in the context of the Jefferson Lab EIC (JLEIC) conceptual design. In its early stage of R&D, the sharp (~3 ns width) waveform construction, beam dynamics, and pulsed power operation with short ramping time (~10 us) will be discussed together with the fabrication work of the JLEIC prototype.

Park, G. -T.↗
DOE OSTI2023

A Deep Learning-Based Workflow for Fast Prediction of 3D State Variables in Geological Carbon Storage: A Dimension Reduction Approach

In this study, we used deep learning techniques, which are a form of artificial intelligence, to create fast and effective models for predicting how fluids flow in underground geological formations. This is important for managing geological carbon storage, a method used to fight climate change by storing carbon dioxide underground. The challenge lies in the complex nature of these underground spaces and the large amount of data needed to accurately simulate them. To overcome these issues, we developed a new workflow that reduces the data’s complexity before training the deep learning model and then reconstructs the predicted results in their original form. We also proposed a unique approach to handle the specific complexities found in 3D saturation fields, a crucial aspect of fluid flow prediction. We tested our method using real-world data from the Gulf of Mexico. Our results show that our approach not only accurately predicts fluid behavior but also significantly reduces computation time. This will greatly improve real-time decision-making and risk assessment in large-scale geological carbon storage operations.

Wang, Hongsheng↗
DOE OSTI2022

Optimizing DER Deployment for Climate, Health, Resilience, and Energy Bill Benefits Using the REopt Model

Climate change, public health, and resilience to power outages are of critical concern to local governments, federal agencies, and the private sector, and are increasingly motivating investments in distributed energy resources (DERs). However, designing a solar-plus-storage system to co-optimize for climate, health, resilience, and energy bill benefits requires complex trade-offs. To address this need, the National Renewable Energy Laboratory has integrated climate and health impacts of grid-purchased electricity and on-site fuel consumption into the publicly-available REopt web tool and API - a techno-economic model that determines the cost-optimal DER system sizes and dispatch strategy. This presentation will provide an overview of the tool's methodology, datasets, and capabilities, including costing emissions into system sizing and dispatch and setting emissions reductions targets. Results of previous work will demonstrate the use of new emissions accounting capabilities by quantifying the impact of including climate and health costs on the optimal resilient microgrid configurations for a hospital, school, and warehouse across 14 U.S. cities.

climate↗
DOE OSTI2024

Effect of K + Force Fields on Ionic Conductivity and Charge Dynamics of KOH in Ethylene Glycol

Predicting ionic conductivity is crucial for developing efficient electrolytes for energy storage and conversion and other electrochemical applications. An accurate estimate of ionic conductivity requires understanding complex ion–ion and ion–solvent interactions governing the charge transport at the molecular level. Molecular simulations can provide key insights into the spatial and temporal behavior of electrolyte constituents. However, such insights depend on the ability of force fields to describe the underlying phenomena. In this work, molecular dynamics simulations were leveraged to delineate the impact of force field parameters on ionic conductivity predictions of potassium hydroxide (KOH) in ethylene glycol (EG). Four different force fields were used to represent the K + ion. Diffusion-based Nernst–Einstein and correlation-based Einstein approaches were implemented to estimate the ionic conductivity, and the predicted values were compared with experimental measurements. The physical aspects, including ion-aggregation, charge distribution, cluster correlation, and cluster dynamics, were also examined. A force field was identified that provides reasonably accurate Einstein conductivity values and a physically coherent representation of the electrolyte at the molecular level.

25 ENERGY STORAGE↗
DOE OSTI2024

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗
DOE OSTI2020

Groundwater characterization and monitoring at a complex industrial waste site using electrical resistivity imaging

A contaminated industrial waste site in Washington State (USA) containing buried, metallic-waste storage tanks, pipes, and wells, was evaluated to determine the feasibility of monitoring groundwater remediation activities associated with an underlying perched aquifer system using electrical resistivity tomography. The perched aquifer, located ~65 m below ground surface and ~10 m above the regional water table, contains high concentrations of nitrate, uranium, and other contaminants of concern from past tank leaks and intentional releases of wastes to surface disposal sites. The extent of the perched water aquifer is not well known, and the effectiveness of groundwater extraction for contaminant removal is uncertain, so supplemental characterization and monitoring technologies are being evaluated. Numerical simulations of subsurface flow and contaminant transport were performed with a highly resolved model of the hydrogeologic system and waste site infrastructure, and these simulations were used as the physical basis for electrical resistivity tomography modeling. The modeling explicitly accounted for metallic infrastructure at the site. The effectiveness of using surface electrodes versus surface and horizontal subsurface electrodes, for imaging groundwater extraction from the perched water aquifer, was investigated. Although directional drilling is a mature technology, its use for electrode emplacement in the deep subsurface under a complex industrial waste site via horizontal wells has not yet been demonstrated. Results from this study indicate that using horizontal subsurface electrode arrays could significantly improve the ability of electrical resistivity tomography to image deep subsurface features and monitor remediation activities under complex industrial waste sites.

54 ENVIRONMENTAL SCIENCES↗