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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Framework for Evaluating the Resilience Contribution of Solar PV and Battery Storage on the Grid

Motivated by decreased cost and climate change concerns, penetration of solar photovoltaic (PV) and battery energy storage has been continually increasing. The variability in solar generation assets has led to many challenges for utilities and researchers. Therefore, there is increasing interest in the area of resilience of the grid and contribution from its assets. This paper describes a proposed framework for evaluating the resilience contribution of solar generation and battery storage. The metric provides a quantifiable adaptive capacity measure with uncertainty for the contribution assets proved to the bulk grid. A case study using long and short-term solar generation, with and without battery storage, demonstrates the framework and provides useful insight to the resilience solar and battery storage assets contribute.

14 SOLAR ENERGY↗
DOE OSTI2020

Supercooled liquid sulfur maintained in three-dimensional current collector for high-performance Li-S batteries

In lithium-sulfur (Li-S) chemistry, the electrically/ionically insulating nature of sulfur and Li 2 S leads to sluggish electron/ion transfer kinetics for sulfur species conversion. Sulfur and Li 2 S are recognized as solid at room temperature, and solid-liquid phase transitions are the limiting steps in Li-S batteries. Here, we visualize the distinct sulfur growth behaviors on Al, carbon, Ni current collectors and demonstrate that (i) liquid sulfur generated on Ni provides higher reversible capacity, faster kinetics, and better cycling life compared to solid sulfur; and (ii) Ni facilitates the phase transition (e.g., Li 2 S decomposition). Accordingly, light-weight, 3D Ni-based current collector is designed to control the deposition and catalytic conversion of sulfur species toward high-performance Li-S batteries. This work provides insights on the critical role of the current collector in determining the physical state of sulfur and elucidates the correlation between sulfur state and battery performance, which will advance electrode designs in high-energy Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Designing interphases for practical aqueous zinc flow batteries with high power density and high areal capacity

Aqueous zinc flow batteries (AZFBs) with high power density and high areal capacity are attractive, both in terms of cost and safety. A number of fundamental challenges associated with out-of-plane growth and undesirable side reactions on the anode side, as well as sluggish reaction kinetics and active material loss on the cathode side, limit practical deployment of these batteries. We investigated artificial interphases created using a simple electrospray methodology as a strategy for addressing each of these challenges. The effectiveness of the electrospray interphases in full cell zinc-iodine flow batteries was evaluated and reported; it is possible to simultaneously achieve high power density [115 milliwatts per square centimeter (mW/cm 2 )] and high areal capacity [25 milliampere hour per square centimeter (mA·hour/cm 2 )]. Last, we extended it to aqueous zinc-bromine and zinc-vanadium flow batteries of contemporary interest. It is again found that high power density (255 and 260 mW/cm 2 , respectively) and high areal capacity (20 mA·hour/cm 2 ) can be simultaneously achieved in AZFBs.

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

Lithium-compatible and air-stable vacancy-rich Li 9 N 2 Cl 3 for high–areal capacity, long-cycling all–solid-state lithium metal batteries

Attaining substantial areal capacity (>3 mAh/cm 2 ) and extended cycle longevity in all–solid-state lithium metal batteries necessitates the implementation of solid-state electrolytes (SSEs) capable of withstanding elevated critical current densities and capacities. In this study, we report a high-performing vacancy-rich Li 9 N 2 Cl 3 SSE demonstrating excellent lithium compatibility and atmospheric stability and enabling high–areal capacity, long-lasting all–solid-state lithium metal batteries. The Li 9 N 2 Cl 3 facilitates efficient lithium-ion transport due to its disordered lattice structure and presence of vacancies. Notably, it resists dendrite formation at 10 mA/cm 2 and 10 mAh/cm 2 due to its intrinsic lithium metal stability. Furthermore, it exhibits robust dry-air stability. Incorporating this SSE in Ni-rich LiNi 0.83 Co 0.11 Mn 0.06 O 2 cathode-based all–solid-state batteries, we achieve substantial cycling stability (90.35% capacity retention over 1500 cycles at 0.5 C) and high areal capacity (4.8 mAh/cm 2 in pouch cells). These findings pave the way for lithium metal batteries to meet electric vehicle performance demands.

25 ENERGY STORAGE↗
DOE OSTI2025

High-voltage water-scarce hydrogel electrolytes enable mechanically safe stretchable Li-ion batteries

Soft Li-ion batteries, based on conventional organic electrolytes, face performance degradation challenges due to moisture penetration and safety concerns due to possible leakage of toxic fluorine compounds and flammable solvents under mechanical damage. We design a water-scarce hydrogel electrolyte with fluorine-free lithium salt to achieve wide electrochemical stability window (up to 3.11 volts) in ambient air without hermetic packaging while balancing high stretchability (1348%), ion conductivity (41 millisiemens per centimeter), and self-healing capabilities for mechanically and chemically safe stretchable Li-ion batteries. Molecular synergy between hydrophilicity and lithiophilicity of zwitterionic polymer backbone is revealed by molecular dynamics simulations. The battery exhibits capacity retention under harsh mechanical stresses—enduring stretching, twisting, folding, and multiple through-punctures by a needle—while self-healing from repeated through cuts by a razor blade. Stable ambient operation for 1 month over 500 charge-discharge cycles (average coulomb efficiency, 95%) is achieved. A prototype self-healing electronic system with embedded soft batteries demonstrates practical application as a durable embodied energy source.

Science & Technology - Other Topics↗
DOE OSTI2021

A rechargeable zinc-air battery based on zinc peroxide chemistry

When two is better than four Batteries based on the reaction of zinc and oxygen have been used for more than a century, but these have been primary (that is, nonrechargeable) cells. These batteries use an alkaline electrolyte and require a four-electron reduction of oxygen to water, which is a slow process. Sun et al. show that with the right choice of nonalkaline electrolyte, the battery can operate using a two-electron zinc-oxygen/zinc peroxide chemistry that is far more reversible. By making the electrolyte hydrophobic, water is excluded from the near surface of the cathode, thus preventing the four-electron reduction. These batteries also show higher energy density and better cycling stability. Science , this issue p. 46

Science & Technology - Other Topics↗
DOE OSTI2025

Cracking the failure of lithium batteries

Lithium batteries that use a solid electrolyte have the potential to improve safety and increase the amount of stored energy . This makes solid-state electrochemical cells a promising option for electric vehicles and wearable devices. However, nonuniform plating or stripping of lithium at the interface between an anode (negative electrode) and the electrolyte during charging and discharging leads to growth of detrimental lithium filaments (dendrites) that short-circuit the battery cell. This problem even occurs when the battery operates at small currents. The underlying mechanism of this failure is not well understood. On page 311 of this issue, Wang et al. (1) report that structural defects accumulate in the lithium metal anode under repeated charging and discharging at a small current. This is similar to mechanical fatigue that is observed over longer periods of intermittent straining of a material. Here, the observation could guide the design of lithium batteries with increased life span.

25 ENERGY STORAGE↗
DOE OSTI2020

A Low-Cost Iron-Based Current Collector for Alkaline Battery Electrodes

The use of three-dimensional porous nickel foam as the current collector of the nickel hydroxide electrode adds significantly to the cost of the nickel-based alkaline rechargeable batteries. Although iron is considerably less expensive than nickel, iron corrodes at the operating potential of the nickel hydroxide electrode. We have found that a 70–100 nm thick thermal coating of cobalt ferrite spinel protects the iron from corrosion. Such a coated iron substrate was found to be stable against corrosion even when polarized anodically at 10 mA cm -2 in 30% potassium hydroxide electrolyte for 1000 h. While the thermal coating of cobalt ferrite protected iron against corrosion, incorporation of lithium ions into the coating was found to enhance the electrical conductivity of the coating. XPS and EXAFS studies confirmed that the enhanced conductivity resulted from an increase in the population of Co 3+ in the ferrite spinel lattice. An inexpensive iron (steel) substrate protected by such a coating when used as a nickel hydroxide battery electrode exhibited a specific capacity of 0.25 Ah g -1 at C/5 discharge rate, comparable to a nickel hydroxide electrode based on a relatively expensive nickel foam substrate. The steel-based electrode also exhibited no noticeable degradation over 150 cycles at C/2 rate. This demonstration of a robust and economical steel substrate presents a unique opportunity for reducing the cost of the nickel hydroxide battery electrode in alkaline batteries

25 ENERGY STORAGE↗
DOE OSTI2020

An Efficient Electrochemical Tanks-in-Series Model for Lithium Sulfur Batteries

This article applies and efficiently implements the Tanks-in-Series methodology ( J. Electrochem. Soc. , 167 , 013534 (2020)) to generate a computationally efficient electrochemical model for Lithium-Sulfur batteries. The original Tank model approach for Lithium-ion batteries is modified to account for porosity changes with time. In addition, an exponential scaling method is introduced that enables efficient simulation of the model equations to address the wide range of time constants present for different reactions in the Lithium-Sulfur system. The Tank Model achieves acceptable voltage error even for transport-limited discharged conditions. Predictions of internal electrochemical variables are examined, and electrochemical implications of the approximations discussed. This suggests significant potential for real-time applications such as optimal charging, cell-balancing, and estimation, and represents a step forward in efforts to incorporate detailed electrochemical models in advanced Battery Management Systems for Lithium-Sulfur batteries.

Parke, Caitlin D. (ORCID:0000000177324044)↗
DOE OSTI2022

Topology Optimization of 3D Flow Fields for Flow Batteries

We report as power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.

25 ENERGY STORAGE↗
DOE OSTI2022

The Role of Functionalized Conducting Polymer Binders in Improving Power Density and Cycle Life of Lithium-Sulfur Batteries

Lithium-Sulfur batteries are promising as the next-generation of low-cost, high-energy rechargeable batteries. However, the commercialization of this battery has been limited by poor rate capability and cycle life. To improve the performance of Li-S cells, we have investigated the role of two n-dopable conducting polymers, N2200 and N2200-OE, as binders for the sulfur cathode. The electron and ion transport properties of these polymer binders, along with their strong affinity for polysulfides, results in significantly enhanced performance compared to cells with the traditional insulating PVDF binder. The role of these conducting polymer binders in enhancing the performance of the cells is analyzed using impedance spectroscopy, shuttle current measurements, conductivity measurements, UV–vis spectroscopy, GIWAXS studies and post-cycling analysis of the anodes. The conducting polymer binders reduce the cell impedance by a factor of four leading to a marked improvement in rate capability. The shuttling of the polysulfides and the formation of insoluble sulfides at the anode is curtailed by the interaction of the polysulfides with the backbone of the polymer binders, leading to an impressive capacity retention of 82% after 500 cycles. These studies demonstrate the benefit of tailored polymer binders at the sulfur electrode in addressing the limitations of lithium-sulfur batteries.

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

Quantifying the Entropy and Enthalpy of Insertion Materials for Battery Applications Via the Multi-Species, Multi-Reaction Model

The entropy coefficient of a battery cell is the property that governs the amount of reversible heat that is generated during operation. In this work, we propose an extension of the Multi-Species, Multi-Reaction (MSMR) model to capture the entropy coefficient of a large format lithium-ion battery cell. We utilize the hybridized time-frequency domain analysis (HTFDA) method using a multi-functional calorimeter to probe the entropy coefficient of a large format pouch type lithium-ion battery with a NMC 811 cathode and a graphite anode. The measured entropy coefficient profile of the battery cell is deconvoluted into an entropy coefficient for each active material, which is then estimated using an extension of the MSMR model. Finally, we extend the entropy of a material to individual entropy for each gallery as treated by the model.

Electrochemistry↗
DOE OSTI2024

Application of the Multi-Species, Multi-Reaction Model to Coal-Derived Graphite for Lithium-Ion Batteries

Graphite is a critical material used as the negative electrode in lithium-ion batteries. Both natural and synthetic graphites are utilized, with the latter obtained from a range of carbon raw materials. In this paper, efforts to synthesize graphite from coal as a domestic feedstock for synthetic graphite are reported. Domestic coal-derived graphite could address national security and energy issues by standing up domestic supply chains for battery critical materials. The performance in lithium-ion coin cells of this coal derived graphite is compared to a commercial battery-grade graphite. For the first time, a multi-species, multi-reaction (MSMR) modeling technique is applied to synthetic graphite derived from coal. Key thermodynamic, transport, and kinetic parameters are obtained for the coal derived graphite and compared to the same parameters for commercial battery-grade graphite. Modeling of synthetic graphites will allow for virtual evaluation of these materials toward production of domestically sourced graphite.

Paul, Abigail (ORCID:0000000172892069)↗
DOE OSTI2024

Leveraging Temperature-Dependent (Electro)Chemical Kinetics for High-Throughput Flow Battery Characterization

The library of redox-active organics that are potential candidates for electrochemical energy storage in flow batteries is exceedingly vast, necessitating high-throughput characterization of molecular lifetimes. Demonstrated extremely stable chemistries require accurate yet rapid cell cycling tests, a demand often frustrated by time-denominated capacity fade mechanisms. We have developed a high-throughput setup for elevated temperature cycling of redox flow batteries, providing a new dimension in characterization parameter space to explore. We utilize it to evaluate capacity fade rates of aqueous redox-active organic molecules, as functions of temperature. We demonstrate Arrhenius-like behavior in the temporal capacity fade rates of multiple flow battery electrolytes, permitting extrapolation to lower operating temperatures. Collectively, these results highlight the importance of accelerated decomposition protocols to expedite the screening process of candidate molecules for long lifetime flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Modeling Structured Electrodes and Graded Porosity for Improving Discharge Rate Capability in Ultra-Thick Graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 Batteries

Long-range electric vehicles (EVs) require high-energy-density batteries that also meet the power demands of high current charge and discharge. Ultra-thick (>100 μm) Lithium-ion battery electrodes are critical to enable this need, but slow ion transport in conventional uniform electrodes (UEs) reduces battery capacity at increasing charge/discharge rates. We present a 3D computational analysis on the impact of structured electrode (SE) and graded electrode (GE) geometries on the discharge rate capability of ultra-thick graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-622) battery cells based on the footprint of a commercial EV pouch cell. SE cathodes with either a “grid” or “line” geometry and GEs with two layers of porosity were modeled. Based on the results of 230 models, we found that the electrolyte volume fraction is a key parameter that impacts capacity improvements in UEs, GEs, and SEs at 2 C–6 C discharge rates. SEs have the greatest discharge rate capability, outperforming GEs and UEs due to reduced Lithium-ion concentration gradients across the electrode thickness, which mitigates electrolyte depletion at high rates. The best SE model has a “grid” geometry with gravimetric and volumetric energy density improvements of 0.9%–4% at C/2–2 C and 18%–24% at 4 C–6 C relative to UEs.

25 ENERGY STORAGE↗
DOE OSTI2025

Electrochemical-Mechanical Coupling Strongly Affects the Performance of Nanopore, Thin-Film, and Solid-State Batteries

Here, the present study focuses on the electrochemical-mechanical (ECM) coupling effects of a thin-film, solid-state battery with only stiff, ceramic materials, in contrast to prior investigations that focus on individual active material particles or aggregations of particles. We model the impacts of ECM couplings including stress-transport and stress-equilibrium potential on the full-cell performance and potential mechanical failure modes of a thin-film battery conformally deposited in a nanopore scaffold, which is an experimentally achievable device. Model results indicate electrode volume changes due to lithium insertion or removal, along with mechanical boundary conditions, result in stress gradients that alter the lithium-ion flux, reduce lithium concentration gradients, and improve cell rate capability. However, the high stress levels in the cell can also lead to mechanics-related failure such as the separation of cell layers. For the parameter set in this work, stress-transport coupling has a much greater influence on rate capability than stress-potential coupling. Optimization of thin-film batteries to harness the benefits of ECM coupling effects requires leveraging geometric design and material selection. The current work underscores the need for further theoretical and experimental investigation into ECM coupling effects in thin-film batteries to enhance their understanding and design optimization.

25 ENERGY STORAGE↗
DOE OSTI2020

Shell Predictive Battery Life Models (SPBLM) [SWR-20-35]

Battery life models to predict the capacity fade and resistance growth of lithium-ion batteries from various manufacturers with different chemistries. The battery life model is trained on experimental test data, and accounts for calendar and cycling aging mechanisms as functions of cell environmental conditions and use. The battery life model is then used to predict capacity fade and resistance growth under any arbitrary aging scenario.

Smith, Kandler↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗