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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Supply Chain for Energy Technologies

Understanding manufacturing cost implications of technologies is critical to aid adoption of next-generation energy solutions. It is important to understand not only of the manufacturing costs and value-add along the supply chain, but also gain understanding of manufacturing location decisions. By identifying a technology's competitive strengths and weaknesses, analyses give researchers and program decision makers the data and insights needed to create strategies and plans that better promote U.S. economic growth and pursue R&D activities that have the greatest long-term potential to yield significant energy savings for U.S. consumers. In this talk, we present examples of analysis from a variety of energy technologies to demonstrate how manufacturing cost analysis can be used to answer specific policy or research questions. In addition, we present case studies showing the importance of understanding trade flow, manufacturing locations, and capacity and utilization to inform economic growth and potential for technology adoption.

benchmarking↗
DOE OSTI2022

Study of Classifiers for U-235 Source Signatures Using Gamma Spectral Measurements

Signatures associated with low-level U-235 sources are studied from a classification analytics perspective, using NaI gamma-ray spectral measurements from detectors located at various distances from the source. Data sets collected at a shielded facility are utilized, wherein the source is introduced via a conduit into a formation of 21 NaI detectors deployed over 6 x 6 meters area in a formation of two concentric circles and one spiral. The activity levels in the spectral regions associated with potential U-235 signatures are estimated as counts at 1 second intervals, and are used as features to train classifiers for detecting the presence of the source. Eight different classifiers are trained and tested using the background and source measurements collected over multiple experimental runs. As expected, the classifier performance improved overall as measurements from the detectors closer to source are used, but also revealed unexpectedly low performance by two detectors that are identically produced and configured as others. Six of eight classifiers have an overall comparable performance, for example, three of them achieved zero training error and 99% detection at 4% false alarm rate for a detector located 1.3 meters away from the source. Also, larger training sets led to improved classification performance across all classifiers, and interestingly, the classifiers with the minimum training error did not necessarily achieve the highest classification performance on test data.

Rao, Nageswara↗
DOE OSTI2020

Tool for Developing Integrated Strategies for Decontamination and Waste Management - 20291

Management of waste from chemical, biological, and radiological incidents is complicated by the fact that decontamination decisions have a profound impact on the characteristics of resulting waste streams. Wide-area biological and radiological incidents could produce massive quantities of waste that may need to be treated on-site and sent for subsequent disposal as non-contaminated materials, or else be directly disposed of as contaminated materials. The EPA has developed the Waste Estimation Support Tool (WEST) for characterizing and quantifying biological and radiological waste that may be generated from decontamination efforts. This paper focuses on the WEST's uses for radiological incidents. WEST combines Geographic Information System (GIS)-based analysis of externally-supplied plume data, infrastructure databases derived from the Federal Emergency Management Agency's (FEMA's) Hazus tool [1], and satellite imagery surface recognition algorithms to combine the composition and square footage of the buildings in the plume with estimates of the materials between the buildings in the plume. The resulting GIS data files are then imported into a Microsoft Access database application, where they are combined with information about the nature and concentration of contaminants, and then subjected to decontamination strategies for different contaminated surfaces. The tool provides estimates of the type and quantities of potential wastes resulting from simulated decontamination and/or demolition activities and includes estimates of the remaining contamination levels including residual contamination contained within each waste stream. Estimates are presented at several levels of detail, allowing users to obtain needed data at the desired resolution. These include estimates for the total affected area, estimates by contamination zone, estimates by decontamination method(s), and estimates by building type (occupancy classification). EPA is currently developing the next version of WEST which will include several substantial enhancements. The most significant improvement for the next version of WEST will include the ability for users to develop contamination scenarios and waste estimates based on previously developed, readily available, and geographically specific infrastructure data. Instead of using WEST's default infrastructure data based on FEMA's Hazus tool, users will be able to import their own building data specific to the geographically affected area. This capability may substantially decrease uncertainties in the resulting waste estimates because the results will be based on actual building data (numbers of each type, square footage, building height, etc.). Two other significant enhancements will be the ability to generate waste estimates for vehicles and biomass. In addition to building debris and building decontamination waste, vehicles and biomass will likely constitute a significant percentage of the total waste which may result from wide area contamination events. This presentation will present the most recent version of WEST, which includes such considerations as affected biomass (e.g., trees), vehicles, and the ability to replace the default Hazus infrastructure databases with custom infrastructure databases. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Robust Method to Identify Groundwater Affected By Redox Conditions at Los Alamos National Laboratory Legacy Cleanup Site - 20497

To facilitate the mission of the Department of Energy's (DoE's) Environmental Management Program at Los Alamos National Laboratory (LANL), a significant number of groundwater monitoring wells with depths ranging from 152-396 meter were completed for characterization and monitoring. Groundwater at Los Alamos tends to be oxygen saturated with very low concentrations of organic matter. Drilling fluids can introduce residual carbon causing an increase in microbial activity and local reducing conditions around the well, potentially impacting representativeness of groundwater data quality for redox sensitive constituents. We assert that the redox state of the wells can robustly be identified by aqueous solution concentrations of iron and manganese. An automated review process has been built into a computer-based data management system enabling an efficient screening process for identifying reducing conditions that are not caught using standard data-validation protocol, and ensures that important data quality issues are thoroughly identified and addressed in an efficient and timely manner. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Determining the Overpotential of Electrochemical Fuel Synthesis Mediated by Molecular Catalysts: Recommended Practices, Standard Reduction Potentials, and Challenges

Molecular catalysts capable of performing electrochemical transformations are frequently utilized in the synthesis of fuels. A common benchmark for evaluating catalysts for electrochemical reactions is overpotential (η) and minimizing η remains an active goal in catalysis. This Review details approaches for the determination of thermodynamic potentials for common fuel-forming reactions and for the determination of electrochemical overpotential, and underscores the need to employ methods that enable meaningful comparisons between molecular catalysts. Strategies for minimizing overpotential while maintaining high activity are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Crystal Structure and Preparation of Li7La3Zr2O12 (LLZO) Solid-State Electrolyte and Doping Impacts on the Conductivity: An Overview

As an essential part of solid-state lithium-ion batteries, solid electrolytes are receiving increasing interest. Among all solid electrolytes, garnet-type Li7La3Zr2O12 (LLZO) has proven to be one of the most promising electrolytes because of its high ionic conductivity at room temperature, low activation energy, good chemical and electrochemical stability, and wide potential window. Since the first report of LLZO, extensive research has been done in both experimental investigations and theoretical simulations aiming to improve its performance and make LLZO a feasible solid electrolyte. These include developing different methods for the synthesis of LLZO, using different crucibles and different sintering temperatures to stabilize the crystal structure, and adopting different methods of cation doping to achieve more stable LLZO with a higher ionic conductivity and lower activation energy. It also includes intensive efforts made to reveal the mechanism of Li ion movement and understand its determination of the ionic conductivity of the material through molecular dynamic simulations. Nonetheless, more insightful study is expected in order to obtain LLZO with a higher ionic conductivity at room temperature and further improve chemical and electrochemical stability, while optimal multiple doping is thought to be a feasible and promising route. This review summarizes recent progress in the investigations of crystal structure and preparation of LLZO, and the impacts of doping on the lithium ionic conductivity of LLZO.

Raju, Md Mozammal (ORCID:0000000319040523)↗
DOE OSTI2025

An atomic cluster expansion potential for twisted multilayer graphene

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for density functional theory calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

2D materials↗
DOE OSTI2022

FINETUNA: fine-tuning accelerated molecular simulations

Abstract Progress towards the energy breakthroughs needed to combat climate change can be significantly accelerated through the efficient simulation of atomistic systems. However, simulation techniques based on first principles, such as density functional theory (DFT), are limited in their practical use due to their high computational expense. Machine learning approaches have the potential to approximate DFT in a computationally efficient manner, which could dramatically increase the impact of computational simulations on real-world problems. However, they are limited by their accuracy and the cost of generating labeled data. Here, we present an online active learning framework for accelerating the simulation of atomic systems efficiently and accurately by incorporating prior physical information learned by large-scale pre-trained graph neural network models from the Open Catalyst Project. Accelerating these simulations enables useful data to be generated more cheaply, allowing better models to be trained and more atomistic systems to be screened. We also present a method of comparing local optimization techniques on the basis of both their speed and accuracy. Experiments on 30 benchmark adsorbate-catalyst systems show that our method of transfer learning to incorporate prior information from pre-trained models accelerates simulations by reducing the number of DFT calculations by 91%, while meeting an accuracy threshold of 0.02 eV 93% of the time. Finally, we demonstrate a technique for leveraging the interactive functionality built in to Vienna ab initio Simulation Package (VASP) to efficiently compute single point calculations within our online active learning framework without the significant startup costs. This allows VASP to work in tandem with our framework while requiring 75% fewer self-consistent cycles than conventional single point calculations. The online active learning implementation, and examples using the VASP interactive code, are available in the open source FINETUNA package on Github.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Regulating in situ gaseous deposition to construct highly durable Fe–N–C oxygen-reduction fuel cell catalysts

The activity–stability trade-off challenges the design of high-performance atomically dispersed iron–nitrogen–carbon (Fe–N–C) catalysts for the acidic oxygen reduction reaction in polymer electrolyte fuel cells. Here we develop an in situ chemical vapour deposition approach during catalyst synthesis to break the trade-off, producing highly stable Fe–N–C catalysts while maintaining adequate oxygen reduction reaction activity. The optimal catalyst exhibits a half-wave potential of 0.867 V, remaining unchanged after an accelerated stress test (AST) of 100,000 potential cycles in rotating disk electrode tests. In membrane electrode assemblies under H 2 –air conditions, it delivers 93 mA cm −2 at 0.8 V after a standard AST of 30,000 voltage cycles, and shows minimal current density losses (2.9% at 0.6 V; 14.2% at 0.7 V) after an extended AST up to 120,000 cycles. Furthermore, the catalyst’s durability improvement is primarily due to the in situ chemical vapour deposition, which strengthens Fe–N bonds, increases active-site density, mitigates iron aggregates and reduces surface porosity.

Chemical engineering↗
DOE OSTI2020

Oil and Natural Gas Development near and beneath Uranium Tailings Cells and Other Remediated Sites - 20358

DOE LM is responsible for maintaining remedies at more than 50 remediated sites that require active long-term surveillance and maintenance (LTS and M). Institutional controls (ICs) were established to limit human and environmental exposures to residual contamination by controlling land use, restricting access to potential hazards, and making the public aware of potential dangers from the residual contamination. ICs for each site were developed based on current and foreseeable conditions; however, these controls should evolve to mitigate potential human health and other environmental risks from unanticipated changes in activities or site conditions. Activities conducted beyond the DOE long-term care boundaries by non-DOE parties may impact the effectiveness of ICs or even the long-term stability of disposal cells and groundwater remedies. Several sites that LM manages or that will transfer to LM for LTS and M are in active oil and gas production basins. The sites are associated with uranium ore milling or nuclear test sites and have been remediated or are in the process of remediation and have no ongoing DOE mission. Particularly since 2005, hydraulic fracturing ('fracking') combined with directional drilling has dramatically increased oil and natural gas (oil/gas) production in the United States, now making it the number one hydrocarbon-producing country. Fracking has allowed production from shale and other rocks of low natural permeability that were historically not considered viable oil/gas resources. Also, because wellbores can now be drilled as many as 5 kilometers or more horizontally, hydrocarbons can be recovered from zones without having access to the surface above them. Drilling activity near Rulison, Colorado, the location of an underground nuclear detonation managed by LM, has raised public concerns that remnant radioactivity in the detonation zone could migrate to producing wells and enter the natural gas distribution system. At sites like the Falls City, Texas, Disposal site, transitioned to LM with a split estate, increased production in the region has resulted in wellbores beneath the long-term care boundary of the site. While the DOE license for Falls City was approved by the NRC in 1997 without the acquisition of the subsurface rights, NRC has raised concerns on whether this activity impacts the integrity of the cell and/or groundwater remedies. In Wyoming, LM is anticipating receiving the license for the Bear Creek site and manages the Spook site, both locations of uranium mill tailings disposal cells. These Wyoming sites are in an active region of major oil and gas development. This change in surrounding land use will require LM to work collaboratively with NRC to address these concerns. At several DOE sites radioactive waste, and often intermixed nonradioactive constituents, is permanently isolated in engineered disposal cells. At other sites, residual contamination can be present in groundwater, blast cavities, and infinite amounts within soil. Areas targeted for oil and gas development at the Texas and Wyoming sites range from depths of 2440 to 3350 meters (8000-11000 feet) below ground surface. When most site remedies were designed, oil and gas development was not considered to be an issue within the site boundary. With the more recent uses of directional drilling, fracking, and associated wastewater injections, the evaluative criteria for incoming sites and ICs for managing long-term protectiveness and regulatory compliance are changing. Although DOE surface ownership was previously thought to be a robust IC to prevent surface and subsurface development, particularly at disposal sites, that may no longer be the case. Whereas the subsurface development at Texas and Wyoming sites is currently occurring at thousands of meters beneath the surface, shallower and direct onsite development would be more of a concern for LM. The energy introduced when a well is hydraulically fractured causes microseismic events (magnitude -2 to 1.0) as the fractures propagate but does not directly cause seismic events (earthquakes) of sufficient magnitude to damage surface structures. Additionally, the extent of the hydraulic fractures is limited to the targeted depths, which are far below the surface. However, earthquakes of sufficient magnitude to damage surface structures have been attributed to the injection of wastewater into disposal wells. States that have experienced these effects have enacted regulations that limit the rate and pressures that wastewater can be injected into disposal wells. Items LM may consider are the need for monitoring the volume of water injected into nearby disposal wells and possibly installing seismic stations at sites most susceptible to damage. While the need to demonstrate that no impact from oil and gas extraction activities on a site groundwater remedy or disposal cells will vary from site to site, LM is assessing risk criteria for this activity. Though LM has not experienced an issue yet at a uranium tailings disposal site, it cannot assume that there will be none, and must address NRC concerns. LM is building on past experiences at other sites and beginning to form new processes with the hope that these concepts can be applied for other future sites. (authors)

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2026

Probing Cellular Activity Via Charge‐Sensitive Quantum Nanoprobes

Nitrogen‐vacancy (NV) based quantum sensors hold great potential for real‐time single‐cell sensing with far‐reaching applications in fundamental biology and medical diagnostics. Although highly sensitive, the mapping of quantum measurements onto cellular physiological states has remained an exceptional challenge. Here, we introduce a novel quantum sensing modality capable of detecting changes in cellular activity. Our approach is based on the detection of environment‐induced charge depletion within an individual particle that, owing to a previously unaccounted transverse dipole term, induces systematic shifts in the zero‐field splitting (ZFS). Importantly, these charge‐induced shifts serve as a reliable indicator for lipopolysaccharide (LPS)‐mediated inflammatory response in macrophages. Furthermore, we demonstrate that surface modification of our diamond nanoprobes effectively suppresses these environment‐induced ZFS shifts, providing an important tool for differentiating electrostatic shifts caused by the environment from other unrelated effects, such as temperature variations. Notably, this surface modification also leads to significant reductions in particle‐induced toxicity and inflammation. Our findings shed light on systematic drifts and sensitivity limits of NV spectroscopy in a biological environment with ramifications for the critical discussion surrounding single‐cell thermogenesis. Notably, this work establishes the foundation for a novel sensing modality capable of probing complex cellular processes through straightforward physical measurements.

band bending↗
DOE OSTI2025

Circumventing Radical Generation on Fe–V Atomic Pair Catalyst for Robust Oxygen Reduction and Zinc–Air Batteries

Iron–nitrogen–carbon (Fe–N–C) catalysts are considered the most active platinum-free alternative for oxygen reduction reaction (ORR), yet the generated reactive oxygen species (ROS) from general mechanistic pathway rapidly impair the ORR activity and stability of Fe–N–C. Herein, we establish and report an ORR pathway-switching strategy to circumvent ROS generation and fundamentally improve the activity and stability of Fe–N–C via DFT guided catalyst design. The constructed Fe–V atomic pair catalyst (Fe 1 V 1 -NC) with N 2 Fe-N 2 -VN 2 configuration enables side-on adsorption of O 2 and subsequent direct-breaking of the O═O bond to form O*, thereby avoiding the formation of ROS radicals. Importantly, there is intersite electron interaction between FeN 4 and VN 4 , which further boosts the ORR activity. Consequently, Fe 1 V 1 -NC exhibits outstanding ORR activity with onset and half-wave (E 1/2 ) potentials at 1.02 and 0.89 V versus RHE, respectively, in 0.1 M KOH. Record-high stability is achieved on Fe 1 V 1 -NC with a minimal decay in E 1/2 by 16 mV over 50000 cycles, surpassing Fe–N–C counterpart and most of the catalysts reported to date. The Fe 1 V 1 -NC-based zinc-air battery reported here demonstrates exceptional durability up to 400 h at 10 mA·cm −2 . This work identifies the intrinsic correlation between ORR pathway, activity, and stability, advancing development of stable catalytic systems.

Fe-N-C↗
DOE OSTI2024

Predictions of Boron Phase Stability Using an Efficient Bayesian Machine Learning Interatomic Potential

Thermodynamic phase stability of three elemental boron allotropes, i.e., α-B, β-B, and γ-B, was investigated using a Bayesian interatomic potential trained via a sparse Gaussian process (SGP). SGP potentials trained with datasets from on-the-fly active learning achieve quantum mechanical level accuracy when employed in molecular dynamics simulations to predict wide-ranging thermodynamic, structural, and vibrational properties. The simulated phase diagram (500~1400 K and 0~16 GPa) agrees with experimental measurements. The SGP-based MD simulations also successfully predicted that the B13 defect is critical in stabilizing β-B below 700 K. At higher temperatures, the entropy becomes the dominant factor, making β-B the more stable phase over α-B. Furthermore, this Letter demonstrates that SGP potentials based on a training set consisting of defect-free-only systems could make correct predictions of defect-related phenomena in solid-state crystals, paving the path to investigate crystal phase stability and transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The mechanism for acetate formation in electrochemical CO (2) reduction on Cu: selectivity with potential, pH, and nanostructuring

Nanostructured Cu catalysts have increased the selectivities and geometric activities for high value C–C coupled (C 2 ) products (ethylene, ethanol, and acetate) in the electrochemical CO (2) reduction reaction (CO (2) RR). The selectivity among the high-value C 2 products is also altered, where for instance the yield of acetate increases with alkalinity and is dependent on the catalyst morphology. The reaction mechanisms behind the selectivity towards acetate vs. other C 2 products remain controversial. In this work, we elucidate the reaction mechanism for acetate formation by using ab initio simulations, a coupled kinetic-transport model, and loading dependent experiments. We find that trends in acetate selectivity can be rationalized from variations in electrolyte pH and the local mass transport properties of the catalyst and not from changes in Cu's intrinsic activity. The selectivity mechanism originates from the transport of ketene, a stable (closed shell) intermediate, away from the catalyst surface into solution where it reacts to form acetate. While this type of mechanism has not yet been discussed in the CO (2) RR, variants of it may explain similar selectivity fluctuations observed for other stable intermediates like CO and acetaldehyde. Our proposed mechanism suggests that acetate selectivity increases with increasing pH, decreasing catalyst roughness and significantly varies with the applied potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Automated Development of Molten Salt Machine Learning Potentials: Application to LiCl

The in silico modeling of molten salts is critical for emerging "carbon-free" energy applications but is inhibited by the cost of quantum mechanically treating the high polarizabilities of molten salts. Here, we integrate configurational sampling using classical force fields with active learning to automate and accelerate the generation of Gaussian approximation potentials (GAP) for molten salts. This methodology reduces the number of expensive ab initio evaluations required for training set generation to O(100), enabling the facile parametrization of a molten LiCl GAP model that exhibits a 19 000-fold speedup relative to AIMD. The developed molten LiCl GAP model is applied to sample extended spatiotemporal scales, permitting new physical insights into molten LiCl's coordination structure as well as experimentally validated predictions of structures, densities, self-diffusion constants, and ionic conductivities. The developed methodology significantly lowers the barrier to the in silico understanding and design of molten salts across the periodic table.

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

Symbiotic bacteriophages exhibit multiple adaptive strategies in activated sludge flocs and contribute to floc stability

Despite the importance of phages for the dynamics and functions of microbial communities, it remains largely unexplored how symbiotic phages adapt in activated sludge systems and influence microbial aggregate stability, which is critical for clarification and reliable performance. Here, based on 12,127 phage contigs recovered from 12 activated sludge microbiomes, the symbiotic phages exhibited broad host ranges and infected dominant prokaryotes in activated sludge. Moreover, these phage communities exhibited high lysogenicity (49% to 66% lysogenic phages) and harbored diverse auxiliary metabolic genes (AMGs) that could enhance microbial aggregate stability, such as genes coding for lipopolysaccharide, peptidoglycan, and extracellular polysaccharide biosynthesis. Additionally, prokaryotic antiviral systems were widely distributed in dominant prokaryotes, particularly the Restriction-Modification (RM) and CRISPR-Cas systems, which could mitigate potential harmful phage infections. Overall, this study reveals the contemporary beneficial relationship between phages and prokaryotic hosts in activated sludge microbiomes and the potential benefits of symbiotic phages on floc stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Modeling ethanol/water adsorption in all-silica zeolites using the real adsorbed solution theory

A comprehensive set of single-component and binary isotherms were collected for ethanol/water adsorption into the siliceous forms of 185 known zeolites using grand-canonical Monte Carlo simulations. Using these data, a systematic analysis of ideal/real adsorbed-solution theory (IAST/RAST) was conducted and activity coefficients were derived for ethanol/water mixtures adsorbed in different zeolites based on RAST. It was found that activity coefficients of ethanol are close to unity while activity coefficients of water are larger in most zeolites, indicating a positive excess free energy of the mixture. This observation can be attributed to water/ethanol interactions being less favorable than water/water interactions in the single-component adsorption of water at comparable loadings. The deviation from ideal behavior can be highly structure-dependent but no clear correlation with pore diameters was identified. Furthermore, our analysis also demonstrates the following: (1) accurate unary isotherms in the low-loading regime are critical for obtaining physically sensible activity coefficients; (2) the global regression scheme to solve for activity model parameters performs better than fitting activity models to activity coefficients calculated locally at each binary state point; and (3) including the dependence on adsorption potential offers only a minor benefit for describing binary adsorption at the lowest fugacities. Finally, the Margules activity model was found incapable of capturing the non-ideal adsorption behavior over the entire range of fugacities and compositions in all zeolites, but for conditions typical of solution-phase adsorption, RAST predictions using zeolite-specific or even bulk Margules parameters provide an improved description compared to IAST.

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

Redox Activity Modulation in Extended Fluorenone-Based Flow Battery Electrolytes with π-π Stacking Effect

Redox flow battery shows promise for grid-scale energy storage. Aqueous organic redox flow batteries are particularly popular due to their potentially low material cost and safe water-based electrolyte. Commonly, redox active molecules used in this field feature aromatic rings, and increasing π-aromatic conjugation has been a popular strategy to achieve high energy density, high power density, and reduced crossover in new material design. However, this approach can inadvertently hinder redox activity depending on redox mechanism. This study reveals the underlying π-π stacking effect in extended aromatic redox active compounds, where aromatic radical intermediates are involved in the redox process. We report a molecular design strategy to mitigate the negative effect of π-π stacking by altering solvation dynamics and introducing molecular steric hindrance.

25 ENERGY STORAGE↗