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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 OSTI2025

Cycling Performance and Structure Evolution of Co-Free Lithium- and Manganese-Rich Layered Oxides in Lithium-Ion Batteries

Lithium- and manganese-rich (LMR) layered oxides are high-capacity cathode materials that are being considered for electric vehicle (EV) lithium-ion batteries (LIBs). Here, we investigate the electrochemical cycling behavior of cells containing a cobalt-free LMR oxide, 0.3Li 2 MnO 3 ·0.7LiMn 0.5 Ni 0.5 O 2 , paired with either Li or graphite anodes. Two- and three-electrode cells are cycled under varying conditions to examine the effects of oxide activation, upper cutoff voltage, separator type, and electrolyte composition. Post-cycling characterization of harvested electrodes, with electrochemical, X-ray absorption spectroscopy, and solid-state 6 Li nuclear magnetic resonance spectroscopy techniques, are used to correlate cell performance changes with redox state evolution in the oxide and Li inventory shifts in the cell. Our results show that capacity fade and impedance rise primarily originate at the graphite anode and LMR cathode, respectively. Notably, while Ni undergoes reversible redox, Mn shows no evidence of bulk redox activity even in highly-aged electrodes: only relithiated LMR electrodes show some reduction of Mn. Graphite electrodes degrade due to particle isolation and SEI growth, exacerbated by Mn dissolution and deposition on graphite anodes. These findings highlight the coupled structural and electrochemical degradation mechanisms in LMR/graphite cells and underscore lithium inventory retention and electrode interfacial stability as critical factors for enhancing long-term performance.

Badami, Pavan P. [Argonne National Laboratory (ANL↗
DOE OSTI2025

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Front-End Engineering Design (FEED) Study for a Carbon Capture Plant Retrofit to a Natural Gas-Fired Gas Turbine Combined Cycle Power Plant (2x2x1 Duct-Fired 758-MWe Facility with F Class Turbines)

A comprehensive front-end engineering design (FEED) study has been undertaken by Bechtel National Inc. (Bechtel) for locating a post-combustion capture and compression (PCC) unit at Panda’s Sherman natural gas–combined cycle (NGCC) power plant in Sherman, Texas. This is described in the unredacted FEED Study report (Attachment 1) with all supporting documents, numbering over 150. The Study Report is publicly available. Sizing of the PCC plant is based on treating an amount of flue gas equivalent to that produced when generating 420 MW, which is approximately 68% of the total flue gas emitted by the NGCC power plant operating at guarantee condition with duct burners off. A reduced power plant capacity factor was used for sizing the PCC plant because the gas turbines at the site often operate at reduced load due to the high penetration of renewable power in the ERCOT region. The cost of carbon capture is primarily driven by capital cost (and therefore is highly sensitive to capacity factor). Sizing the capture unit so that when used it is nearly always operating at full capacity is critical to the economic viability of the proposed investment.

03 NATURAL GAS↗
DOE OSTI2020

Hydrogen-Bonding Interactions in Hybrid Aqueous/Nonaqueous Electrolytes Enable Low-Cost and Long-Lifespan Sodium-Ion Storage

Although “water-in-salt” electrolytes have opened a new pathway to expand the electrochemical stability window of aqueous electrolytes, the electrode instability and irreversible proton co-insertion caused by aqueous media still hinder the practical application, even when using exotic fluorinated salts. In this study, an accessible hybrid electrolyte class based on common sodium salts is proposed, and crucially an ethanol-rich media is introduced to achieve highly stable Na-ion electrochemistry. Here, ethanol exerts a strong hydrogen-bonding effect on water, simultaneously expanding the electrochemical stability window of the hybridized electrolyte to 2.5 V, restricting degradation activities, reducing transition metal dissolution from the cathode material, and improving electrolyte–electrode wettability. The binary ethanol–water solvent enables the impressive cycling of sodium-ion batteries based on perchlorate, chloride, and acetate electrolyte salts. Notably, a Na 0.44 MnO 2 electrode exhibits both high capacity (81 mAh g –1 ) and a remarkably long cycle life >1000 cycles at 100 mA g –1 (a capacity decay rate per cycle of 0.024%) in a 1 M sodium acetate system. The Na 0.44 MnO 2 /Zn full cells also show excellent cycling stability and rate capability in a wide temperature range. The gained understanding of the hydrogen-bonding interactions in the hybridized electrolyte can provide new battery chemistry guidelines in designing promising candidates for developing low-cost and long-lifespan batteries based on other (Li + , K + , Zn 2+ , Mg 2+ , and Al 3+ ) systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Stabilized Co-Free Li-Rich Oxide Cathode Particles with An Artificial Surface Prereconstruction

Li-rich metal oxide (LXMO) cathodes have attracted intense interest for rechargeable batteries because of their high capacity above 250 mAh g –1 . However, the side effects of hybrid anion and cation redox (HACR) reactions, such as oxygen release and phase collapse that result from global oxygen migration (GOM), have prohibited the commercialization of LXMO. GOM not only destabilizes the oxygen sublattice in cycling, aggravating the well-known voltage fading, but also intensifies electrolyte decomposition and Mn dissolution, causing severe full-cell performance degradation. In this study, an artificial surface prereconstruction (ASR) for Li 1.2 Mn 0.6 Ni 0.2 O 2 particles with a molten-molybdate leaching is conducted, which creates a crystal-dense anion-redox-free LiMn 1.5 Ni 0.5 O 4 shell that completely encloses the LXMO lattice (ASR-LXMO). Differential electrochemical mass spectroscopy and soft X-ray absorption spectroscopy analyses demonstrate that GOM is shut down in cycling, which not only stabilizes HACR in ASR-LXMO, but also mitigates the electrolyte decomposition and Mn dissolution. ASR-LXMO displays greatly stabilized cycling performance as it retains 237.4 mAh g –1 with an average discharge voltage of 3.30 V after 200 cycles. More crucially, while the pristine LXMO cycling cannot survive 90 cycles in a pouch full-cell matched with a commercial graphite anode and lean (2 g A –1 h –1 ) electrolyte, ASR-LXMO shows high capacity retention of 76% after 125 cycles in full-cell cycling.

25 ENERGY STORAGE↗
DOE OSTI2024

Co-optimization of nuclear reactor flexible power operation and maintenance scheduling

As flexible power operation of nuclear power plants becomes more attractive due to the reduction in fossil-fueled dispatchable generation on energy grids, finding optimal power production strategies that balance revenue generation with operational concerns becomes more complex. This article presents a general framework to aid operators in designing economically optimal long term dispatch strategies for nuclear power plants. The principal novelty is the linking of estimated system remaining useable life (RUL) to strategic operational decisions. It is shown that, depending on the relationship between the fixed costs from maintenance and the associated lost revenue from an outage, it can be economically optimal in the long term to delay a maintenance outage and not perform this alongside refueling. For a given relationship between power ramping and degradation, optimal strategies were found that discouraged load following in some situations while minimizing unnecessary maintenance. It is shown that heavy load following can cause maintenance and refueling outages to diverge due to their inverse relationships with respect to load following, potentially leading to a significant loss in capacity factor. As a result, this general framework can be applied to specific reactor dispatch allowing operators to adapt operational strategies as future grid conditions change.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Development of an Extreme Fast Charging Battery

The objective of the project is to research, develop, design, fabricate, and demonstrate extreme fast charging (XFC) Li-ion cells capable of a 10 min charge to deliver 180Wh/kg at the beginning of life (BoL) and sustain >500 XFC cycles with less than 20% capacity loss. The PI developed an asymmetric temperature modulation (ATM) charging strategy that charges a Li-ion cell at an elevated temperature of ~60oC and discharges at the ambient temperature. The elevated charging temperature eliminates Li plating, while the limited exposure time to 60oC effectively controls materials degradation, thereby enabling XFC with remarkable battery life. We developed and demonstrated 209 and 271 Wh/kg cells, both of which exceed the afore-mentioned target of delivering 180Wh/kg at BoL and sustaining 500+ XFC cycles with less than 20% loss.

25 ENERGY STORAGE↗
DOE OSTI2020

In Operando XANES Imaging of High Capacity Intermetallic Anodes for Lithium Ion Batteries

In operando 2D X-ray absorption near edge structure (XANES) imaging was performed near the Cu K-edge during cycling of Cu 6 Sn 5 composite anodes for lithium ion batteries. Galvanostatic lithiation and delithiation with intermittent constant voltage holds near reaction plateaus show evolution of absorption spectra for active material particles. XANES spectra obtained from images taken during cycling were compared to standard spectra for Cu, Cu 6 Sn 5 , and Li 2 CuSn. Chemical composition was assessed for Cu-containing phases. Distinct Cu, Cu 6 Sn 5 , and Li 2 CuSn regions were identified for each voltage plateau. Mechanical degradation, electrode particle fracture and expansion were observed during delithiation. Furthermore, movement of particles during cycling suggests that expansion also impacts the supporting secondary phases and the transport networks therein. These results demonstrate that spectroscopic X-ray imaging methods can clearly distinguish chemically distinct phases in alloy electrodes and have the versatility to observe the evolution of these phases during lithiation and delithiation.

25 ENERGY STORAGE↗
DOE OSTI2021

In–Depth Analysis of the Degradation Mechanisms of High–Nickel, Low/No–Cobalt Layered Oxide Cathodes for Lithium–Ion Batteries

A rational compositional design of high-nickel, cobalt-free layered oxide materials for high-energy and low-cost lithium-ion batteries would be expected to further propel the widespread adoption of electric vehicles (EVs), yet a composition with satisfactory electrochemical properties has yet to emerge. The previous work has demonstrated a promising LiNi 0.883 Mn 0.056 Al 0.061 O 2 (NMA-89) composition that outperformed high-nickel, cobalt-containing analogs in cycling stability and maintained a comparable rate performance and thermal stability. Herein, the capacity fading mechanism of NMA-89 in a pouch full cell with a 4.2 V cutoff is compared to that of its cobalt-containing analogs. The results reveal that particle cracking in LiNi 0.89 Mn 0.055 Co 0.055 O 2 (NMC-89) and LiNi 0.883 Co 0.053 Al 0.064 O 2 (NCA-89) leads to a loss of active material and an increase in surface area, thereby exacerbating structural and surface instabilities, accelerating impedance and polarization growth, and ultimately reducing their capacity retentions. LiNi 0.89 Mn 0.044 Co 0.042 Al 0.013 Mg 0.011 O 2 (NMCAM-89) and NMA-89 experience subdued surface reactions and maintain spherical particle structures, both of which are conducive to their capacity retentions during long-term cycling. Furthermore, this investigation offers insights into how specific transition-metal ions dictate the electrochemical stability of high-Ni layered oxide cathode materials, highlights the benefit of Mn-Al combination in NMA-89, and presents potential strategies to further enhance the performance of this novel class of cathode materials.

degradation mechanisms↗
DOE OSTI2020

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Copper carbon composite wire with a uniform carbon dispersion made by friction extrusion

Copper-carbon composites are a group of materials with excellent mechanical, electrical, thermal, and tribological properties. However, bulk size copper-carbon composites made by the traditional manufacturing processes, like rolling or extrusion, fall short of reaching some of these properties predicted by theory or demonstrated only by samples at centimeter scale or smaller. The two main challenges to the successful scaling-up are: 1) to uniformly disperse carbon in the metal matrix; 2) to avoid degradation due to oxidation or reaction from overheating. In this work, we first demonstrate friction extrusion as a new method to make bulk-size void-free copper-carbon composite wires with homogenized carbon dispersion. Three different carbon varieties, graphite powder, graphene nanopowder, and carbon nanotubes, were added to the copper matrix with the concentration ranging from 0.5 wt% to 15 wt%. Special tooling, processing parameters, and procedures were developed, especially for high carbon content samples. Ten-fold reductions of both copper grain size and carbon particle size were achieved and attributed to the high shear deformation. Energy dispersive X-ray spectrometry indicates the carbon powder was refined to a sub-micron level and uniformly dispersed in the copper matrix. Compared with that of pure copper, the thermal capacity of the composite wire increases by 30 % while density reduces by 29 %.

Friction extrusion, Metal matrix composite, Graphe↗
DOE OSTI2022

Predicting battery capacity from impedance at varying temperature and state of charge using machine learning

Prediction of battery health from electrochemical impedance spectroscopy (EIS) data can enable rapid measurement of battery state in real-world applications without using additional sensors or time-consuming performance measurements. However, deconvoluting the effect of capacity, state of charge, and temperature on EIS response is complicated analytically. Here, various machine-learning models, such as linear, Gaussian process, random forest, and artificial neural network regression, are utilized to predict capacity from EIS using hundreds of capacity, direct current (DC) resistance, and EIS measurements recorded under varying conditions of health, temperature, and state of charge (SOC). Several feature extraction and selection methods from traditional electrochemical analysis and statistical modeling are explored using machine-learning pipelines. EIS data from just two frequencies can accurately predict capacity, and interrogation shows that the optimal set of frequencies is not usually intuitive. Best results are achieved with an ensemble model, which predicts battery capacity with a mean absolute error of 1.9% on data from unobserved cells.

25 ENERGY STORAGE↗
DOE OSTI2025

Minimizing Inter‐Lattice Strain to Stabilize Li‐Rich Cathode by Order–Disorder Control

Li-rich Mn-based layered (LMR) cathodes with anionic redox chemistry show great potential for next-generation sustainable Li-ion battery (LIB) applications due to the low cost and high energy density. However, the asynchronous structural evolutions with cycling in the heterogeneous composite structure of LMR lead to serious lattice strain and thus fast electrochemical decay, which hinders the commercialization of LMR cathodes. Here, in this study, an order–disorder coherent LMR cathode is demonstrated that exhibits a higher average voltage (by 0.25 V), negligible voltage decay (97.6% voltage retention after 100 cycles at 100 mA g −1 ), and enhanced cycling stability (98% capacity retention after 200 cycles at 100 mA g −1 ) compared to its layered oxide counterparts. It is proposed that this order–disorder coherent structure design can promote a more synchronous and homogeneous structure evolution during charge and discharge, thus minimizing lattice strain, which significantly prevents layer collapse and collective degradation at high voltage, improving the electrochemical stability. The study displays the feasibility of optimizing the performance of Li-rich cathode materials through a dedicated order–disorder structure control for sustainable energy storage.

Xu, Shenyang [Peking University, Shenzhen (China)]↗
DOE OSTI2021

Revisiting the role of Zr doping in Ni-rich layered cathodes for lithium-ion batteries

We report the realization of high performance Ni-rich layered cathodes remains a challenge because of the multiple degradation factors that concurrently operate during battery cycling. In particular, depletion of oxygen charge and consequent lattice oxygen instability at deep charge state accelerate the subsequent chemomechanical degradation mechanisms. Among the proposed methodologies, doping has proven to be effective in enhancing the cathode cycle life by stabilizing the layered structure. Herein, we achieved the electrochemically stabilized Ni-rich LiNi 0.92 Co 0.04 Mn 0.04 O 2 through Zr doping, resulting in a 15% increase of the capacity retention after 100 cycles. In-depth investigations are conducted to unveil the effects of Zr doping on the layered cathode, and in particular, the critical role of Zr doping on the lattice oxygen stability is systematically studied. By combining state-of-the-art magnetometer characterization, X-ray analysis, and first-principles calculation, we reveal that Zr doping positively contributes the to lattice oxygen stability by alleviating the oxygen charge loss at deep charge, thereby improving the cathode electrochemical reversibility. Our findings provide an insight into the Zr doping mechanism and help to design the Ni-rich layered oxides for future applications.

25 ENERGY STORAGE↗
DOE OSTI2020

A high-capacity cathode for rechargeable K-metal battery based on reversible superoxide-peroxide conversion

Abstract As a promising low-cost energy storage device, the development of a rechargeable potassium-ion battery (KIB) is severely hindered by the limited capacity of cathode candidates. Regarded as an attractive capacity-boosting strategy, triggering the O-related anionic redox activity has not been achieved within a sealed KIB system. Herein, in contrast to the typical gaseous open K-O2 battery (O2/KO2 redox), we originally realize the reversible superoxide/peroxide (KO2/K2O2) interconversion on a KO2-based cathode. Controlled within a sealed cell environment, the irreversible O2 evolution and electrolyte decomposition (induced by superoxide anion (O2−) formation) are effectively restrained. Rationally controlling the reversible depth-of-charge at 300 mAh/g (based on the mass of KO2), no obvious cell degradation can be observed during 900 cycles. Moreover, benefitting from electrolyte modification, the KO2-based cathode is coupled with a limited amount of K-metal anode (merely 2.5 times excess), harvesting a K-metal full-cell with high energy efficiency (∼90%) and long-term cycling stability (over 300 cycles).

25 ENERGY STORAGE↗
DOE OSTI2025

Review of Layered Transition Metal Oxide Materials for Cathodes in Sodium-Ion Batteries

The growing interest in sodium-ion batteries (SIBs) is driven by scarcity and the rising costs of lithium, coupled with the urgent need for scalable and sustainable energy storage solutions. Among various cathode materials, layered transition metal oxides have emerged as promising candidates due to their structural similarity to lithium-ion battery (LIB) counterparts and their potential to deliver high energy density at reduced costs. However, significant challenges remain, including limited capacity at high charge/discharge rates and structural instability during extended cycling. Addressing these issues is critical for advancing SIB technology toward industrial applications, particularly for large-scale energy storage systems. This review provides a comprehensive analysis of layered sodium transition metal oxides, focusing on their structural properties, electrochemical performance, and degradation mechanisms. Special attention is given to the intrinsic and extrinsic factors contributing to their instability, such as structural phase transitions, and cationic/anionic redox behavior. Additionally, recent advancements in material design strategies, including doping, surface modifications, and composite formation, are discussed to highlight the progress toward enhancing the stability and performance of these materials. This work aims to bridge the knowledge gaps and inspire further innovations in the development of high-performance cathodes for sodium-ion batteries.

Ahangari, Mehdi (ORCID:0000000345803969)↗
DOE OSTI2021

Complementary Electrolyte Design for Li Metal Batteries in Electric Vehicle Applications

In this report a complementary electrolyte system with 0.8 M lithium bis(fluorosulfonylimide) (LiFSI) salt and 2 wt % lithium perchlorate (LiCLO4) additive in fluoroethylene carbonate (FEC)/ethyl methyl carbonate (EMC) solution enables not only stable cycling of lithium metal batteries (LMBs) with practical loading (<30 μm lithium anode, cathode loading > 4 mAh/cm 2 ) but also outstanding degradation stability toward the end of cycle life when compared to the conventional electrolyte. Although the use of LiFSI salt can increase the electrolyte conductivity and lengthen the cycle life of LMBs, the aged lithium anode morphology formed by the sacrificial decomposition of LiFSI is highly porous, leading to an abrupt cell capacity drop toward the end of cycling. Moreover, the inability to stop aluminum corrosion by the LiFSI-based electrolyte also causes cracking of the cathode tab during prolonged cycling. It is observed that a highly porous aged lithium consumed electrolyte at a higher rate, leading to the dry-out of electrolyte solvents. On the contrary, dense aged lithium anode morphology increased the localized current applied on the lithium, causing the formation of lithium dendrite. Thus, porosity control is the key to enhance battery performance. In this complementary system, LiClO 4 was introduced as an advanced additive to not only improve the capacity retention rate but also mitigate the abrupt capacity drop toward the end of cycle life because LiClO 4 acted as a pore astringent reducing the porosity of the aged lithium metal anode to the desired level. Moreover, the addition of LiClO 4 can also suppress the AI corrosion, allowing stable high-voltage cycling of LMBs. The synergistic effect of combining LiFSI salt and a LiClO 4 additive leads to an electrolyte system that can facilitate the application of high-energy LMBs with practical electrode loading.

25 ENERGY STORAGE↗
DOE OSTI2021

Editors’ Choice—Examining Performance and Durability of Anion Exchange Membrane Fuel Cells with Novel Spirocyclic Anion Exchange Membranes

A series of spirocyclic copolymer membranes with varying ion exchange capacities (IECs) were investigated to probe the impact of polymer properties on in situ fuel cell performance and stability. In-situ electrochemical tests and post-mortem electron microscopy analysis of cross-sectioned membrane electrode assemblies (MEAs) have been combined with voltage loss breakdown analysis to evaluate the performance and degradation of different MEAs, and to probe the catalyst morphology and electrode structure at different stages of operation. Voltage loss breakdown results show that membrane degradation and kinetic losses played only a minor role in observed performance degradation and that performance losses were primarily related to increasing mass transport losses. From microscopy studies, carbon corrosion and Pt nanoparticle growth were identified at both the cathode and anode although more pronounced on the cathode resulting in significant structural changes. The membrane with the lowest IEC (1.3 mmolg −1 ) demonstrated the lowest peak power density ~ 1.16 W cm −2 , however, it showed the most stable performance (constant 0.6 A cm −2 hold) with ~ 5% degradation over 540 h. Isolation of performance losses and microscopic analysis of electrodes for anion exchange membrane fuel cells has not been reported previously, and these results help identify critical performance degradation concerns.

25 ENERGY STORAGE↗