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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nanoscale Three-Dimensional Imaging of Degradation in Composite Si-Containing Anodes

The use of silicon (Si) in next-generation lithium-ion battery (LIB) anodes has the potential to dramatically improve electrochemical performance over current LIB graphite (Gr) anodes, due to silicon’s higher specific capacity.1 However, widespread implementation of Si-containing anodes is inhibited by issues such as significant Si volume expansion during lithiation and an unstable solid-electrolyte interphase (SEI), resulting in unreliable performance and poor cycle life. Currently, composite anodes with both Si and graphite active materials are used to increase capacity and mitigate some of the limitations associated with Si. In composite electrodes with a heterogeneous distribution of components with varying electrical properties (including Si, Gr, conductive carbon additive, and binder), it is important to understand the local distribution of each component to correlate with electrochemical processes, particularly localized degradation and heterogeneous aging, and to optimize performance. To investigate Si-containing composite anodes in the nanoscale, we use scanning spreading resistance microscopy (SSRM), a form of scanning probe microscopy (SPM) that probes local electronic resistivity. By examining the intrinsic electronic resistivity contrast between the anode components, separate phases can be distinguished and understood within the composite structure.2 This work studies the effect of electrochemical cycling in two different electrolytes on component distribution and aging by comparing the electrical and structural evolution of composite Si-graphite electrodes and SEI before and after charge-discharge cycling. 1. W. J. Zhang. A review of the electrochemical performance of alloy anodes for lithium-ion batteries J. Power Sources 196 13–24 (2011). 2. C. Stetson, Z. Huey, A. Downard, Z. Li, B. To, A. Zakutayev, C.-S. Jiang, M. Al-Jassim, D. Finegan, S.-D. Han and S. DeCaluwe: Three-Dimensional Mapping of Resistivity and Microstructure of Composite Electrodes for Lithium-Ion Batteries. ACS Nano Letters Accepted (2020).

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Complex Dynamics in Argyrodite Solid-State Ion Conductors

Argyrodites are a compositionally diverse family of materials that exhibit remarkable ion transport properties. While the average crystal structures of argyrodites have been extensively studied, ion transport in these materials is governed by a confluence of dynamic processes spanning the cation, anion, and polyanionic sublattices. This Perspective synthesizes recent advances in understanding the role of dynamics in structural behavior and ion transport properties. We examine the compositional and structural motifs that govern order−disorder transitions within the argyrodite family and further explore how ion hopping is facilitated by lattice dynamics, from long-range phonons to local rotational dynamics of polyanionic species. Through the lens of dynamics spanning multiple time and length scales, we establish guiding principles that govern transport phenomena and highlight avenues of future study for the argyrodite family of ion conductors.

36 MATERIALS SCIENCE↗
NASA NTRS2016

An Overview of Power, Energy Storage, and Conversion Efforts for 2014 SBIR Phases I and II

Technological innovation is the overall focus of NASA's Small Business Innovation Research (SBIR) program. The program invests in the development of innovative concepts and technologies to help NASA's mission directorates address critical research and development needs for agency projects. NASA's Small Business Innovation Research (SBIR) program focuses on technological innovation by investing in development of innovative concepts and technologies to help NASA mission directorates address critical research needs for Agency programs. This report highlights 15 of the innovative SBIR 2014 Phase I and II projects that focus on one of NASA Glenn Research Center's six core competencies-Power, Energy Storage and Conversion. The technologies cover a wide spectrum of applications such as high-radiation-tolerant ceramic voltage isolators, development of hermetic sealing glasses for solid oxide fuel cells, rechargeable lithium metal cells, high-efficiency direct methane solid oxide fuel cell systems, Li metal protection for high-energy space batteries, isolated bidirectional direct current converters for distributed battery energy applications, and high-efficiency rad-hard ultrathin Si photovoltaic cell technology for space. Each article describes an innovation and technical objective and highlights NASA commercial and industrial applications. This report provides an opportunity for NASA engineers, researchers, and program managers to learn how NASA SBIR technologies could help their programs and projects, and lead to collaborations and partnerships between the small SBIR companies and NASA that would benefit both.

flywheels↗
NASA NTRS2018

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

Corbetta, M.↗
NASA NTRS2019

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

stochastic calculus↗
DOE OSTI2023

Poly(vinylferrocene) as an Ionomer and Sulfur-Confining Additive for Lithium–Sulfur Batteries

Lithium-sulfur (Li-S) batteries are promising owing to their high energy density, environmental benignity, and low cost. Most of the commonly used binders in Li-S battery cathodes are inert and have no significant effect on the challenges of sulfur as a cathode material, such as the polysulfide shuttle effect, low ionic/electronic conductivity, and a sluggish redox reaction. In this work, we demonstrate the use of poly(vinylferrocene) (PvFc) as a binder additive that can effectively increase the ionic conductivity of the cathode and act as a sulfide confining agent. Electrochemical tests performed with PvFc as part of the binder mixture used to cast the cathodes demonstrate an increase in rate capability and cycle life when compared to the baseline samples. Ionic conductivity measurements and X-ray photoelectron spectroscopy suggest that the π-cation molecular interaction between the cyclopentadienyl rings from ferrocene and Li + act like an ion couple with ferrocene acting as a static, covalently bound acceptor of Li + ions that enhances their mobility through the cathode. This coupled with the affinity between the ferrocenyl cations and the Li salt anions, which provides more distribution of counterions for Li + movement and improves accessibility to the cathode S reservoir, make PvFc a promising ionomer for Li-S batteries. In addition, the π-cation bonds between cyclopentadienyl and lithium polysulfides produce a sulfide confining effect that mitigates capacity fade through polysulfide dissolution. Furthermore, this work demonstrates an expansion in the utility of PvFc as a component in Li-ion batteries, which so far is mostly limited to use as an active material in organometallic batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

North American Lithium-Ion Battery Supply Chain Database Development - Phase II

Lithium-ion batteries (LIBs) are used in a wide range of applications, including cell phones, laptops, power tools, electric vehicles, and grid storage, and are essential for economic growth and addressing climate change. However, the significant demand for LIBs has led to supply chain issues for the United States, as China dominates the processing of battery materials and battery production. To address this concern, NAATBatt International, a trade association of North American battery companies, supported the National Renewable Energy Laboratory in developing a database of companies that mine, process, manufacture, reuse, and recycle batteries in North America. The purpose of this database was to identify strengths and gaps in the supply chain, so that private-government partnerships could develop strategies to create a competitive LIB supply chain in the US. NREL published the first version of this database in 2021 and the second version in 2022. The database includes companies that have a manufacturing facility in North America and are engaged in materials, cells, packs, end-of-life management, as well as those involved in LIB battery modeling, distribution, service and repair, and R&D. In this presentation, we will discuss our approach to collecting data and categorizing various segments and products. We will also provide a summary of the data and present various maps to illustrate the distribution of companies in the database.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗
DOE OSTI2020

Tritium Transport Phenomena in Molten-Salt Reactors

In this work, we review phenomena relevant to tritium transport in molten-salt reactors, which produce tritium from lithium and beryllium salts at significantly higher levels than other reactor types. Modeling of such phenomena began following MSRE operations, and these early models attempted to predict measured tritium distributions in the MSRE, accounting for turbulent mass-transport processes (using established heat transfer correlations), permeation through a variety of metal structures such as heat exchanger tubes, and transport to and from bubbles introduced into the salt by gas sparging. The models reasonably reproduced the MSRE data, but did so best when the permeability of structures was reduced by about a factor of 1,000. This issue does not appear to have been conclusively resolved, and all of the more recent attempts to model tritium transport in molten salts appear to make use of the same methodology. MSRE remains, however, essentially our only source of integral tritium transport data relevant to MSRs. Here, we generalize the MSRE approach to permeation in order to include potential rate-limiting effects at interfaces, as well the effects of added hydrogen. Appropriately non-dimensionalized, this system of equations identifies two dimensionless numbers whose relative values clearly delineate the conditions under which mass transport, surface effects, permeation, and hydrogen swamping are expected to become rate-limiting. We also describe the preliminary conceptual design of a forced convection FLiBe loop, into which tritium would be introduced for the purpose of providing validation data for such a model. The primary purpose of this is to investigate the coupled transport phenomena described above and identify those that are rate-limiting in MSRs. Additional test section configurations are described that would address other transport phenomena relevant to MSRs, including bubbly flows and graphite interactions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Prediction of neutron production and energy spectrum by the inverse kinematic reaction between an incident 7 Li 3+ beam and a proton target in PHITS

A neutron source using the inverse kinematic reaction between lithium and proton, p( 7 Li, n) 7 Be, achieves forward-directed neutrons, potentially enhancing neutron yield in the forward direction. Despite the advantage, no evaluated-cross-section data for this reaction can be used in Monte Carlo simulation codes, such as PHITS. To solve this problem, this study aims to evaluate the applicability of the user-defined cross-section data, Frag data, for p ( 7 Li, n) 7 Be in PHITS. The simulations reproduced collisions between 7 Li 3+ ions and polypropylene targets. The Frag data was edited based on the JENDL-5 by utilizing the two-body collision kinematics. The neutron yield and angular distribution were investigated in the simulation. As a result, the forward neutron convergence with a reasonable neutron yield and energy spectrum was observed. The expected neutron yield in the forward 1-steradian area is 2.46 × 10 10 n/s when lithium-ion energy and current are 16.45 MeV and 0.1 mA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Forecasting Battery Electrode Performance via Electrochemical Fluorescence Microscopy and Machine-Learning

Predicting lithium-ion battery performance is hindered by microscale electrode heterogeneities invisible to conventional diagnostics. Here, we combine electrochemical fluorescence microscopy (EFM), which maps electronic connectivity by visualizing an electrofluorophore reaction distribution, with a multitask ElasticNet regression to forecast discharge capacity from spatial heterogeneity. Analyzing 196 images from six pilot-scale LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathodes with varying carbon loadings, we extract 62 descriptors that capture morphology and texture. A compact five-feature model predicts capacity across eight discharge rates, achieving a per-target R 2 of up to 0.63 and an overall R 2 of 0.92, with a mean absolute percentage error of less than 2%. This performance rivals impedance-based approaches while avoiding their reliance on postformation data and incomplete electronic network information. Our facile and rapid, image-driven method may enable electrode quality control upstream of costly cell assembly to offer a transformative tool for data-driven battery research and manufacturing.

battery electrodes↗
DOE OSTI2021

Molecular Level Differences in Ionic Solvation and Transport Behavior in Ethylene Oxide-Based Homopolymer and Block Copolymer Electrolytes

Block copolymer electrolytes (BCE) such as polystyrene-block-poly(ethylene oxide) (SEO) blended with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and composed of mechanically robust insulating and rubbery conducting nanodomains are promising solid-state electrolytes for Li batteries. Here, we compare ionic solvation, association, distribution, and conductivity in SEO-LiTFSI BCEs and their homopolymer PEO-LiTFSI analogs toward a fundamental understanding of the maximum in conductivity and transport mechanisms as a function of salt concentration. Ionic conductivity measurements reveal that SEO-LiTFSI and PEO-LiTFSI exhibit similar behaviors up to a Li/EO ratio of 1/12, where roughly half of the available solvation sites in the system are filled, and conductivity is maximized. As the Li/EO ratios increase to 1/5 the conductivity, of the PEO-LiTFSI drops nearly 3-fold, while the conductivity of SEO-LiTFSI remains constant. FTIR spectroscopy reveals that additional Li cations in the homopolymer electrolyte are complexed by additional EO units when the Li/EO ratio exceeds 1/12, while in the BCE, the proportion of complexed and uncomplexed EO units remains constant; Raman spectroscopy data at the same concentrations show that Li cations in the SEO-LiTFSI samples tend to coordinate more to their counteranions. Atomistic-scale molecular dynamics simulations corroborate these results and further show that associated ions tend to segregate to the SEO-LiTFSI domain interfaces. The opportunity for "excess" salt to be sequestered at BCE interfaces results in the retention of an optimum ratio of uncompleted and complexed PEO solvation sites in the middle of the conductive nanodomains of the BCE and maximized conductivity over a broad range of salt concentrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Solar dynamic heat receiver technology

A full-size, solar dynamic heat receiver was designed to meet the requirements specified for electrical power modules on the U.S. Space Station, Freedom. The heat receiver supplies thermal energy to power a heat engine in a closed Brayton cycle using a mixture of helium-xenon gas as the working fluid. The electrical power output of the engine, 25 kW, requires a 100 kW thermal input throughout a 90 minute orbit, including when the spacecraft is eclipsed for up to 36 minutes from the sun. The heat receiver employs an integral thermal energy storage system utilizing the latent heat available through the phase change of a high-temperature salt mixture. A near eutectic mixture of lithium fluoride and calcium difluoride is used as the phase change material. The salt is contained within a felt metal matrix which enhances heat transfer and controls the salt void distribution during solidification. Fabrication of the receiver is complete and it was delivered to NASA for verification testing in a simulated low-Earth-orbit environment. This document reviews the receiver design and describes its fabrication history. The major elements required to operate the receiver during testing are also described.

Sedgwick, Leigh M.↗
DOE OSTI2023

Understanding Biases in Sample Preparation Techniques for Coupled Scanning Electron Microscopy and MAMA PuO 2 Morphological Analysis

In this project, the scanning electron microscopy (SEM) sampling method used during the statistical design study (SDS) was investigated to determine if any sampling biases were present in the analyzed data. Using standard particle size distribution powders from the National Institute of Standards and Technology (NIST 1984 standard reference material) with the origin wet dispersion method, it was determined that a bias to smaller particles was present. This was supported by theoretical calculations using Stokes’ law to determine the settling rate of spherical particles of roughly the same size and mass as those found in the SDS. Based on the theoretical calculations, it was determined that the settling rate for each of the 76 powder sets in the SDS could be unique based on specific particle shape and mass distributions, making a universal correction factor/formula not applicable. Therefore, priority shifted to developing an improved wet dispersion method that significantly reduced the particle settling rate for all particle size and shapes. This was achieved by replacing the original solvent (isopropyl alcohol) with a heavy liquid (lithium heteropolytungstates), which dramatically slowed the settling rate and allowed for the capture of a suitable homogeneous aliquot. SEM imaging and Morphological Analysis for Material Attribution (MAMA) software analysis were conducted on the NIST standard, and the SEM/MAMA data were compared to data captured by a dynamic image analysis particle size analyzer. The resulting data confirmed that the new wet dispersion method does indeed deliver an improved representative aliquot to the SEM stub. For instance, in the NIST certificate, the average particle size is ~17.1 µm ± 2.2 µm with a normal distribution. The initial wet dispersion method resulted in a drastically reduced average particle size of 6.1 µm in addition to a non-representative heavy bi-modal distribution whereas the improved LST wet dispersion method resulting in an average particle size that was much closer to the NIST certificate (12.7 µm) with a similar normal distribution. Although the improved method was still short of the NIST certificate average, atomic force microscopy analysis determined that the resulting ~20-25% reduction in size was due to particles sinking into the carbon sticky tape used for SEM imaging. It is believed that that this bias can be calibrated in a much more predicable manner than the original settling rate bias. In addition, the matching normal distribution curves between the NIST certificate and the heavy liquid method indicate a much-improved representative aliquot has been sampled and imaged. A surrogate CeO 2 powder was used to reflect PuO 2 more accurately and to aid in implementing radiological controls and shielding. The resulting data sets from the SEM/MAMA method and the particle size analyzer give almost identical average particle sizes and particle distribution statistics. Future work will re-analyze several select runs from the SDS to determine if morphological signatures can be found with the improved sampling method.

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

Predictive-Maintenance Practices: For Operational Safety of Battery Energy Storage Systems

Changes in the Demand Profile and a growing role for renewable and distributed generation are leading to rapid evolution in the electric grid. These changes are beginning to considerably strain the transmission and distribution infrastructure. Utilities are increasingly recognizing that the integration of energy storage in the grid infrastructure will help manage intermittency and improve grid reliability. This recognition, coupled with the proliferation of state-level renewable portfolio standards and rapidly declining lithium-ion (Li-ion) battery costs, has led to a surge in the deployment of battery energy storage systems (BESSs). Additionally, although BESSs represented less than 1% of grid-scale energy storage in the United States in 2019, they are the preferred technology to meet growing demand because they are modular, scalable, and easy to deploy across diverse use cases and geographic locations.

25 ENERGY STORAGE↗
DOE OSTI2026

An immersed interface method for microstructure-scale electrochemical battery models: numerical formulation and performance portable implementation

We present the numerical formulation, verification, and performance portable implementation of an immersed interface method for microstructure scale electrochemical modeling of batteries. The innovation in this approach is the resolution of chemical species and electrostatic potential discontinuities at active interfaces without the use of interface conforming unstructured grids. A unified formulation on Cartesian grids for all domains (electrodes and electrolyte) is used with interfacial flux conditions applied using volume fraction or “color” function gradients. We have developed one dimensional and two dimensional test cases with analytic solutions for electrochemical modeling using which we verified the consistency and accuracy of our scheme. Our solver is also validated against solutions from a macroscale model and an unstructured multi-subdomain solver for a full lithium ion cell. We then demonstrated the utility of our solver on an image-based complex battery electrode microstructure at high charging rate. Our technique also exhibits good scalability on distributed memory architectures using central processing units (CPU), with problem sizes up to 1.8 billion degrees of freedom and with 5400 ranks. Initial performance studies of our open-source performance portable solver showed about 70 times speed up using a graphics processing unit (GPU) compared to single compute core for a problem with 4 million cells.

25 ENERGY STORAGE↗
DOE OSTI2024

Kinetics of Radiation-induced Cr( II ) and Cr( III ) Redox Chemistry in Molten LiCl-KCl Eutectic

Chromium (Cr) is a frequent constituent of the metal alloys proposed for molten salt nuclear reactor (MSR) applications, and is typically the least noble metal ion present. Consequently, chromium is preferentially corroded into molten salt solutions. Here, the redox poise and redox cycling of chromium ions in the salt can greatly influence its corrosivity towards structural alloys, ultimately impacting the longevity of MSR systems. Radiation-induced chemistry is expected to play a significant role in determining the chromium oxidation state distribution during MSR operations. In the present research, electron pulse radiolysis techniques were employed to characterize the reactivity of Cr(II) and Cr(III) ions with primary radiolysis products in molten lithium chloride–potassium chloride (LiCl–KCl) eutectic over a temperature range of 400–600 °C. Both chromium oxidation states were found to rapidly react with the primary products of molten chloride salt radiolysis, i.e., the solvated electron (e S - ) and the dichlorine radical anion (Cl 2 ˙ - ). For reactions with the e S - , second-order rate coefficients (k) of k = (4.1 ± 0.2) and (6.1 ± 0.3) × 10 10 M -1 s -1 at 400 °C for Cr(II) and Cr(III), respectively, were determined. Temperature-dependent measurements allowed for the derivation of activation parameters for electron capture by Cr(II) and Cr(III). Both chromium ions also react with Cl 2 ˙ - , k = (7.2 ± 0.3) and (1.4 ± 0.1) × 10 9 M -1 s -1 at 400 °C for Cr(II) and Cr(III), respectively.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2023

Plating and Stripping of Lithium Metal Stabilized by a Block Copolymer Electrolyte: Local Current Density Measurement and Modeling

Here, plating and stripping of lithium protrusions in lithium metal symmetric cells containing a solid block copolymer electrolyte was studied as a function of time in 3D using time-resolved X-ray tomography. These measurements enabled determination of the spatial variation in current densities at the plating and stripping electrodes. The initial interelectrode distance was 27 μm. Correlation functions were calculated to reveal the relationships between current densities at the two electrodes and local electrolyte thickness. Current densities at opposing electrode locations during protrusion growth is uncorrelated until the local interelectrode distance decreases to less than 6 μm, just before the cell shorts. Mass balance was used to determine the area from which lithium ions that form a protrusion were stripped. Computational modeling of the plating and stripping process reveals the interplay between electrochemical and mechanical driving forces and their effect on nonuniform current distribution. Model predictions were compared with experiments without resorting to any adjustable parameters. The computed correlation functions were in qualitative agreement with experiments. Finally, the model was used to calculate contour plots of electrochemical potential within the electrolyte, shedding light on how geometry, salt concentration, interelectrode distance, and mechanical stress influence local rates of electrochemical reaction.

36 MATERIALS SCIENCE↗