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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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We highlight the status of, and propose future approaches for, rheological, electrochemical, and spectroscopic characterization of concentrated redoxmer electrolytes for energy storage, with an emphasis on nonaqueous redox flow batteries.
Secondary alkaline batteries, such as nickel-cadmium and silver-zinc, are commonly used for aerospace applications. The uniform evaluation and comparison of separator properties for these systems is dependent upon the measurement techniques. This manual presents a series of standard test procedures that can be used to evaluate, compare, and select separator materials for use in alkaline batteries. Detailed test procedures evaluating the following characteristics are included in this manual: physical measurements of thickness and area weight, dimensional stability measurements, electrolyte retention, resistivity, permeability as measured via bubble pressure, surface evaluation via SEM, chemical stability, and tensile strength.
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The dynamic information of lithium-ion battery active materials obtained from coin cell-based in-situ characterizations might not represent the properties of the active material itself because many other factors in the cell could have impacts on the cell performance. To address this problem, a single particle cell was developed to perform the in-situ characterization without the interference of inactive materials in the battery electrode as well as the X-ray-induced damage. In this study, the dynamic morphological and phase changes of selenium-doped germanium (Ge 0.9 Se 0.1 ) at the single particle level were investigated via synchrotron-based in-situ transmission X-ray microscopy. The results demonstrate the good reversibility of Ge 0.9 Se 0.1 at high cycling rate that helps understand its good cycling performance and rate capability. This in-situ and operando technique based on a single particle battery cell provides an approach to understanding the dynamic electrochemical processes of battery materials during charging and discharging at the particle level.
The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.
Testing of absorbent plate separation materials and propellant formulations to characterize battery components ability to withstand dry heat sterilization
Preparation, characterization, and an electrochemical study of Mg 0.1 V 2 O 5 prepared by a novel sol-gel method with no high-temperature post-processing are disclosed. Cyclic voltammetry showed the material to be quasi-reversible, with improved kinetics in an acetonitrile-, relative to a carbonate-, based electrolyte. Galvanostatic test data under a C/10 discharge showed a delivered capacity >250 mAh/g over several cycles. Based on these results, a magnesium anode battery, as disclosed, would yield an average operating voltage ˜3.2 Volts with an energy density ˜800 mWh/g for the cathode material, making the newly synthesized material a viable cathode material for secondary magnesium batteries.
Forge Nano has recently developed an innovative strategy based on atomic layer deposition(ALD) of oxide coatings on battery separators and electrode materials. ORNL team worked with Forge Nano under this CRADA to construct larger format cells, validate battery and separator performance, and perform advanced materials characterization. It was observed that oxide coatings improve the battery cell performance in terms of both rate capability and long-term cyclic stability. ORNL team performed the research under this CRADA at DOE’s Battery Manufacturing Facility (BMF) at ORNL.
Forge Nano has recently developed an innovative strategy based on atomic layer deposition (ALD) of oxide coatings on battery separators and electrode materials. ORNL team worked with Forge Nano under this CRADA to construct larger format cells, validate battery and separator performance, and perform advanced materials characterization. It was observed that oxide coatings improve the battery cell performance in terms of both rate capability and long-term cyclic stability. ORNL team performed the research under this CRADA at DOE’s Battery Manufacturing Facility (BMF) at ORNL.
The lithium–sulfur (Li–S) battery is a promising next-generation energy storage technology because of its high theoretical energy and low cost. Extensive research efforts have been made on new materials and advanced characterization techniques for mechanistic studies. However, it is uncertain how discoveries made on the material level apply to realistic batteries due to limited analysis and characterization of real high-energy cells, such as pouch cells. Evaluation of pouch cells (>1 A h) (instead of coin cells) that are scalable to practical cells provides a critical understanding of current limitations which enables the proposal of strategies and solutions for further performance improvement. Herein, we design and fabricate pouch cells over 300 W h kg -1 , compare the cell parameters required for high-energy pouch cells, and investigate the reaction processes and their correlation to cell cycling behavior and failure mechanisms. Spatially resolved characterization techniques and fluid-flow simulation reveal the impacts of the liquid electrolyte diffusion within the pouch cells. We found that catastrophic failure of high-energy Li–S pouch cells results from uneven sulfur/polysulfide reactions and electrolyte depletion for the first tens of cycles, rather than sulfur dissolution as commonly reported in the literature. The uneven reaction stems from limited electrolyte diffusion through the porous channels into the central part of thick cathodes during cycling, which is amplified both across the sulfur electrodes and within the same electrode plane. A combination of strategies is suggested to increase sulfur utilization, improve nanoarchitectures for electrolyte diffusion and reduce consumption of the electrolytes and additives.
The emergence of high-entropy materials has inspired the exploration of novel materials in diverse technologies. In electrochemical energy storage, high-entropy design has shown advantageous impacts on battery materials such as suppressing undesired short-range order, frustrating energy landscape, decreasing volumetric change and reducing the reliance on critical metals. This comment addresses the definition and potential improper use of the term “high entropy” in the context of battery materials design, highlights the unique properties of high-entropy materials in battery applications, and outlines the remaining challenges in the synthesis, characterization, and computational modeling of high-entropy battery materials.
Lithium-ion batteries are recognized as an important electrochemical energy storage technology due to their superior volumetric and gravimetric energy densities. Graphite is widely used as the negative electrode, and its adoption enabled much of the modern portable electronics technology landscape. However, developing markets, such as electric vehicles and grid-scale storage, have increased demands, including higher energy content and a diverse materials supply chain. Alternatives that provide the opportunity to increase capacity and address supply chain concerns are of interest. Understanding the fundamental mechanisms that govern battery function is crucial to driving further improvements in the field. Advanced characterization techniques, such as those enabled by synchrotron light sources and high-resolution electron microscopes, that can uncover these mechanisms have become a necessity for elucidating structural evolution upon electrochemical conversion at the nano- to mesoscales. Performing these experiments with relevant electrochemistry using in situ and operando experiments imparts the ability to identify critical reaction pathways and capture intermediate (dis)charge products not discernible by traditional experiments.
The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.
Flame processes are the most economic ones to produce fine powders and have been used to produce pigment titanium oxide and fused silica in large volumes. In this work a flame spray pyrolysis (FSP) process is used to make positive electrode materials for Li-ion battery, which is made of complex metal oxide powders, such as Li(Ni1/3Mn1/3Co1/3)O2. In particular, the work was focused on making the NMC materials with stoichiometric compositions and desired morphologies. During the pyrolysis process different morphologies can be formed, involving often powders with primary nanoparticles. Such nanostructures were found to have affected the battery performance. Detailed results of the synthesis, characterization, and battery testing of the NMC powder materials will be presented.
Here, using a thick NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ) electrode as an example, we present a macro- to nanoscale 2D and 3D imaging analysis approach coupled with 4D (space + time) computational modeling to probe its degradation mechanism in a lithium-ion battery cell. Particle cracking increases and contact loss between particles and carbon-binder domain are observed to correlate with the cell degradation. This study unravels that the reaction heterogeneity within the thick cathode caused by the unbalanced electron conduction is the main cause of the battery degradation over cycling. The increased heterogeneity in the system will entail more cathode regions where the degree of active material utilization is uneven, leading to higher probabilities of particle cracking. These findings shed light on the crucial role of the electronic and ionic transportation networks in the performance deterioration of the thick cathode. They also provide guidance for cathode architecture optimization and performance improvement.
Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries and electrocatalysts. Experimental characterizations of such materials by operando microscopy produce rich image datasets, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.
Improved performance of lithium-ion batteries (LIBs) plays a critical role in the future of next- generation battery applications. Nickel-rich layered oxides such as LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC 811), are popular cathodes due to their high energy densities. However, they suffer from high surface reactivity, which results in the formation of Li 2 CO 3 passive layer. Herein, we show the role of nanosecond pulsed laser annealing (PLA) in improving the current capacity and cycling stability of LIBs by reducing the carbonate layer, in addition to forming a protective LiF layer and manipulating the NMC 811 microstructures. We use high-power nanosecond laser pulses in a controlled way to create nanostructured surface topography which has a positive impact on the capacity retention and current capacity by providing an increased active surface area, which influences the diffusion kinetics of lithium-ions in the electrode materials during the battery cycling process. Advanced characterizations show that the PLA treatment results in the thinning of the passive Li 2 CO 3 layer, which is formed on as-received NMC811 samples, along with the decomposition of excess polyvinylidene fluoride (PVDF) binder. The high-power laser interacts with the decomposed binder and surface Li + to form LiF phase, which acts as a protective layer to prevent surface reactive sites from initiating parasitic reactions. As a result, the laser treated cathodes show relative increase of the current capacity of up to 50%, which is consistent with electrochemical measurements of LiB cells.
In Phase 1, the University of Texas at Austin explored many methods of cathode design, synthesis, and modification, while also developing an understanding of the relationships among the cathode, anode, and electrolyte. Some of the major accomplishments are highlighted in this report.