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At least 1,297 records · Page 72

Classifying thermodynamic cloud phase using machine learning models

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) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the 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 pixels 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 multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 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 that 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 data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. 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. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

Systems Level Fuel Cycle Modeling in TMAP8 - A Demonstration

The tritium migration analysis program (TMAP) has been used for tritium inventory tracking and analysis for several years, and the Multiphysics Object Oriented Simulation Environment (MOOSE)-based TMAP8 has several improvements over TMAP4 and TMAP7, such as support for multiple dimensions and non-cartesian coordinate systems, as well as interoperability with sub-apps at higher and lower length scales. We demonstrate that TMAP8 has the additional capacity to solve systems-level problems using zero-dimensional ordinary differential equations by reproducing a literature model which describes a systems-level fuel-cycle of tritium inventory in a hypothetical fusion power plant. The capacity to run several coupled multi-scale physics calculations as part of a single package will be necessary for accurate blanket and fuel-cycle design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Analysis of Air-Purifying Respirator (APR) Cartridge Performance Testing on Hanford Tanks SX-101 and SX-104 (Vol.1)

Washington River Protection Solutions (WRPS) conducted tests on two types of chemical cartridges for use in air-purifying respirators to determine the period of time that the cartridges would provide adequate performance1 to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPC) from vapors exiting the headspaces of Hanford tanks SX-101 and SX-104. The Occupational Safety and Health Administration (OSHA) considers cartridge testing a valid approach for establishing cartridge change schedules.2 Testing is commonly applied in situations where mixtures of COPCs exist and where other approaches such as manufacturer recommendations and modeling are less reliable. The tests were designed and conducted to ensure measurement and/or control of the key variables OSHA identified as important to estimate the cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Testing was conducted from June 16-17, 2017, and June 23-24, 2017, using headspace vapors from Hanford tank SX-104 and Hanford tank SX-101, respectively. Headspace vapors under static conditions were fed to a respirator cartridge test stand developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Multipurpose respirator cartridges, SCOTT 7422-SD1 and SCOTT 7422-SC1 (SCOTT Safety, Monroe, North Carolina), were assessed on separate days. Sample media (sorbent tubes) were used to collect samples of the vapor stream entering and exiting the respirator cartridges, and subsequently were analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and service life.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Thermodynamic investigation of the NaCl-KCl salt system from 25 to 950 °C

NaCl-KCl molten salt system has been proposed as a primary component of several promising heat transfer eutectics and fuel host for Generation IV molten salt reactors (MSR). In this work, several key thermodynamic parameters, including high temperature enthalpies, isobaric heat capacities (C p ) and molar enthalpies of mixing (ΔH mix ), of the NaCl -KCl system (NaCl, 75mol% NaCl – 25mol% KCl, 51mol% NaCl – 49mol% KCl, 25mol% NaCl – 75mol% KCl, and KCl) were measured by high temperature drop calorimetry (HTDC) utilizing laser sealed nickel and aluminum crucibles. Salts were checked for phase purity by X-ray diffraction (XRD), and water content by Karl Fischer coulometric titrimetry and thermogravimetric analysis (TGA). Thermo-mechanical analysis (TMA) utilizing custom-built boron nitride (BN) crucibles was employed to determine temperatures of phase transitions (solid $\rightarrow$ liquid) for the salts and plotted against the pseudobinary phase diagram for the NaCl-KCl system. Small deviations (3-10 %) were found among C p values obtained from HTDC, differential scanning calorimetry (DSC), and NIST, comparable to the average uncertainty based on two standard deviations of measured data that are ~6% for DSC and ~3% for HTDC. Additionally, the measured enthalpies and C p values of mixed NaCl-KCl salts (e.g., 51mol% NaCl – 49mol% KCl eutectic) were shown to behave as statistical mixtures of its pure endmembers, consistent with ΔH mix = ~ 0 kJ/mol at 800 °C, and a regular interaction parameter of Ω = 1.20 ± 0.76 kJ/mol. In conclusion, this study represents a step towards improved accuracy and precision in determinations of thermodynamic parameters of molten salts by using DSC, TMA, and HTDC, in completion of the Molten Salt Thermal Properties Database (MSTDB).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fast and Scalable Synthesis of LiNi 0.5 Mn 1.5 O 4 Cathode by Sol–Gel-Assisted Microwave Sintering

High-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) is a promising cathode material for high-energy-density and high-power-density lithium-ion batteries (LIBs). The high cost of the currently available LIBs needs to be addressed urgently for wide application in the transport sector (electric vehicles, buses) and large-scale energy storage systems (ESS). Of significance, herein, novel fast and scalable microwave-assisted synthesis of LNMO is reported, which leads to a production cost cut. X-ray diffraction (XRD) analysis confirms the formation of the desired phase with high crystallinity. Field emission scanning (FE-SEM) and transmission electron microscopy (TEM) analyses indicate that the synthesized phase is of nanometric size (50–150 nm) due to an extremely short sintering time (20 min). The material synthesized at 750 °C shows a higher initial discharge capacity (130 mA h g -1 ) than that synthesized at 650 °C (115 mA h g -1 ). The materials heat treated at higher temperatures show better electrochemical performance in terms of initial capacity, rate capability, and improved cycling. The improved electrochemical performance of LNMO at 750 °C is attributed to the formation of a stable crystal structure, low charge transfer resistance at the electrode/electrolyte interface, high electrical conductivity due to the presence of a disorder structure, and improved ionic diffusivity.

25 ENERGY STORAGE↗

Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida

Abstract The genome-scale model of metabolism and gene expression (ME-model) forPseudomonas putidaKT2440,iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model,iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. Multi-omics analysis using RNA sequencing and ribosomal profiling data revealed translational prioritization inP. putida, with core pathways, such as nicotinamide biosynthesis and queuosine metabolism, exhibiting higher translational efficiency, while secondary pathways displayed lower priority. Notably, the ME-model significantly outperformed the M-model in alignment with multi-omics data, thereby validating its predictive capacity. Thus,iPpu1676-ME offers valuable insights intoP. putida’s proteome allocation and presents a powerful tool for understanding resource allocation in this industrially relevant microorganism.

Mathematical & Computational Biology↗

Data Placement Optimization for ATLAS in a Multi-Tiered Storage System within a Data Center

Scientific experiments and computations, especially in High Energy Physics, are generating and accumulating data at an unprecedented rate. Effectively managing this vast volume of data while ensuring efficient data analysis poses a significant challenge for data centers, which must integrate various storage technologies. This paper proposes addressing this challenge by designing and developing a precise data popularity prediction model utilizing state-of-theart AI/ML techniques. This model is crafted from the analysis of ATLAS data and access patterns. It enables us to migrate infrequently accessed data to more economical storage media, such as tape drives, while storing frequently accessed data on faster yet costlier storage media like HDD or SSD. This strategic approach ensures data is placed optimally into the appropriate storage classes, thereby maximizing storage capacity while minimizing data access latency for end-users. Furthermore, the paper includes a performance evaluation of the prediction model using various key metrics such as F1 score, accuracy, precision and recall. Finally, we present a prototype use case, leveraging real-world file access data to assess the model’s impact on performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

On the scale of heterogeneity in composite electrodes of batteries

An electrode in cylindrical or pouch cell batteries contains millions of active particles embedded in a conductive network. Battery performance, such as voltage, capacity, and cyclic efficiency, is a collective response of the particle network. We use optical microscopy to measure the local, heterogeneous state of charge of individual particles upon charging and discharging. The optical reflectivity is proportional to Li composition in the ternary oxide LiNi x Mn y Co z O 2 (NMC) cathode. Through clustering analysis, we determine the scale of heterogeneity where a representative volume in the composite electrode contains 100 to 1,000 particles. The heterogeneous activity in the particle network can be described by Weibull defect population at the particle interface with the conductive matrix.

batteries↗

Elastic and thermodynamic properties of cerium-doped yttrium aluminum garnets

Cerium-doped yttrium aluminum garnets (Y 3-x Ce x Al 5 O 12 , Ce:YAGs) are promising yellow light-emitting components of solid-state white light-emitting diodes. Although there have been numerous studies examining the effects of Ce concentrations on the luminescent properties of Y 3-x Ce x Al 5 O 12 , the impacts of Ce dopant on the elastic and thermodynamic properties are not well understood. In this work, we used resonant ultrasound spectroscopy (RUS) to determine the effects of Ce doping (0.025, 0.1, 1 at. %) on the elastic and thermodynamic properties of Y 3-x Ce x Al 5 O 12 . The elastic moduli calculated via the Voigt–Reuss–Hill (VRH) method demonstrated that low Ce dopant concentrations (≤0.1 at. %) induced negligible effects on the elasticity of the YAG host matrix, while a high Ce concentration (1 at. %) yielded significant softening. RUS spectral analysis and SEM images suggested that the elastic softening originated from microstructural differences induced at higher Ce dopant concentrations. Additionally, we demonstrated an increase in elastic anisotropy at higher Ce concentrations, which further elucidated the correlations between structure and elasticity of Y 3-x Ce x Al 5 O 12 . Debye temperatures ($θ_D$), heat capacities ($C_p$), and thermal conductivities ($\mathit{κ}$) were calculated for Ce:YAGs through the relations of RUS-derived parameters (sound velocities, elastic moduli) and previously determined thermal expansion coefficients. Ce:YAG was found to have a significant reduction in $θ_D$, Cp, and $\mathit{κ}$ at Ce concentrations ≥1 at. %. Lastly, extrapolation of $C_p$ and $\mathit{κ}$ to higher temperatures allowed the modeling of thermal stress experienced by Y 3-x Ce x Al 5 O 12 disks up to 1073.15 K.

36 MATERIALS SCIENCE↗

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DISSPATCH H2: Assessing Subsurface Storage Potential for Hydrogen

This project evaluates the technical feasibility of long-term underground hydrogen storage in the Anadarko Basin, integrating subsurface science, reservoir engineering, and system-level analysis to build a cohesive understanding of how hydrogen may be stored and recovered in porous media. Although salt caverns currently dominate commercial-scale hydrogen storage, their limited geographic availability necessitates alternative options that can support a more resilient energy system. Depleted oil and gas reservoirs offer a widely distributed and potentially high-capacity solution, but their suitability depends on formation-specific geologic, petrophysical, microbial, and operational factors. This study provides the first coordinated assessment of these factors within the Simpson Group of Oklahoma.

03 NATURAL GAS↗

Computational Analysis of Hydraulic Efficiency of Michigan DOT Covers J and K

Drainage structures are used in urban street and highway systems to capture stormwater runoff. These structures typically consist of catch basins fitted with grates, inlets, or combination grate/inlet configurations that collect runoff and convey it through buried drainage systems. They are strategically placed within curb-and-gutter systems to enhance public safety by efficiently removing water from roadways and thereby reducing the risk of hydroplaning. The performance of drainage structures is commonly evaluated in terms of hydraulic efficiency, defined as the percentage of flow captured by the basin relative to the total flow reaching the structure. Understanding the hydraulic performance of these structures allows designers to properly space inlets, resulting in cost-effective designs that also help ensure the safety of the traveling public. MDOT uses a variety of drainage structures for runoff capture, as documented in Michigan Department of Transportation (MDOT) Drainage Manual. Many of these structures incorporate sinusoidal-type grates that are not addressed in HEC-22. Because physical modeling of these structures has been limited, further analysis is needed to verify their capture efficiency. Under current MDOT practice, the capture efficiency of these grates is estimated by assuming performance similar to that of a comparably sized reticuline grate described in HEC22. The first phase of this effort, titled Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C, focused on evaluating the hydraulic performance of MDOT’s Cover C grate. Cover C was selected as the initial test candidate because its sinusoidal pattern is representative of other MDOT grates, while it is typically used in high-volume, higher-speed applications. A similar version, Cover CX, is used on interstate highways but does not include transverse bars for bicycle safety. The current second phase of the study expands this work to evaluate MDOT’s Covers J and K. These grates were selected for additional analysis to further assess the hydraulic performance of MDOT drainage structures that are not directly represented by grate configurations in HEC-22. The results of this phase will build on the findings from the Cover C analysis and support improved understanding of the capture efficiency of MDOT’s standard drainage grates. This report is intended to serve as a companion document to the earlier study, Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C [3]. The present work applies the same overall CFD-based evaluation approach to MDOT Covers J and K and compares the resulting performance trends with those previously identified for Cover C. In particular, both studies assess on-grade interception efficiency, sag-location hydraulic capacity, and the effects of partial obstruction relative to HEC-22-based design estimates.

42 ENGINEERING↗

Geothermal Representation in Power System Models

Power system models generally fail to capture the range of characteristics geothermal resources provide and the value they potentially contribute to decarbonization and reliability of future electricity grids as firm, dispatchable, non-combustion power resources. This study reviews the results of power system modeling efforts to investigate geothermal deployment potential in the United States, including the U.S. DOE GeoVision analysis and ongoing modeling and analysis efforts to support planning and development of future grids with 100% renewable energy in California. Several themes are identified that could be implemented immediately to improve the accuracy of geothermal representation in power system models: consistency of model inputs, modeling of baseload and dispatchable geothermal resources, accurate valuation of grid services, improved representation of capacity factor, use of contemporary LCOE estimates, improved understanding of the evolution of geothermal value, and use of accurate resource potential constraints. Many of the models reviewed produced significantly different amounts of geothermal resource selection - even when modeling the same region and time period. This highlights the variability of inputs and assumptions among models, so creating a consistent set of geothermal inputs is a first step toward more accurate representation of geothermal in models. Research opportunities are identified that could help improve geothermal data inputs in modeling efforts, including analyses of historical data, sensitivity to model inputs, and comparative value of geothermal generators as baseload or dispatchable resources. Outcomes of such research can inform the geothermal community about how best to guide geothermal development toward wider deployment in support of future electricity grids through improved understanding of the evolution of geothermal value over time and the characteristics that contribute to that value.

capacity expansion models↗

Resilience Analytics for Interdependent Power and Water Distribution Systems

The occurrence of large-scale outages in power distribution systems (PDSs) caused, for instance, by extreme weather events has raised concerns on the cascading impact of the power outages on the resilience of other critical infrastructures, including water distribution systems (WDSs), whose healthy operation highly relies on the availability of power from PDSs. Here, this paper proposes an analytics model for quantifying the interdependence between the resilience of power and water distribution systems. The proposed model first performs spatio-temporal outage analysis on the PDS and WDS to determine the PDS power serving capability and the resulting cascading impact on the WDS water serving capability during the occurrence of disruptions. The resilience interdependence is then determined by a proposed set of six metrics calculated using the power and water serving capability profiles, which trace and quantify the cascading impacts of power outages in the operation of WDSs during the degradation and recovery stages. The proposed analytics model is implemented on the IEEE 33-bus power distribution system supplying power for pumping stations of a 15-node test WDS, considering multiple cases of water storage capacity, single and multiple outage scenarios, and availability of distributed generation. The numerical results demonstrate that the proposed metrics track the temporal and spatial interdependence between the resilience of power and water distribution systems, providing a mechanism to identify weak spots, and assess options to enhance the resilience of the critical water infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Least-Cost Storage Mix for Low-Carbon Operations

As communities plan for high- or ultrahigh-renewable power systems, they face diverse options for energy storage. Each energy storage technology has a unique power capacity and discharge duration, and each community has a unique load, generation mix, and weather pattern. Determining the optimal storage portfolio across these parameters could save planners significant costs when building out high-renewable power systems.

analysis↗

Analysis of Respirator Cartridge Performance Testing on the 702-AZ Primary Exhauster for the Hanford AY/AZ Tank Farms during a Waste-Disturbing Event

Washington River Protection Solutions (WRPS) conducted tests using two types of chemical cartridges for use in air-purifying respirators (APR) to determine the period of time that the cartridges would provide adequate performance1 for APRs used to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPC) from vapors exiting the 702-AZ Primary Exhauster for the Hanford AY-AZ tank farms. Unlike prior cartridge testing on the 702-AZ Primary Exhauster, the recent tests were performed during a waste-disturbing event. The Occupational Safety and Health Administration (OSHA) identifies cartridge testing as a valid approach for establishing a cartridge change schedules. Testing is commonly applied in situations where mixtures of COPCs exist, and where other approaches, such as manufacturer recommendations and modeling, are less reliable. The tests were designed and conducted to assure measurement and/or control of the key variables OSHA identified as important to estimate the cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Testing was conducted from February 10–11, 2017, on a slipstream from the 702-AZ exhauster fed to a respirator cartridge test stand developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Multipurpose respirator cartridges, SCOTT 7422-SD1 and SCOTT 7422-SC1 (SCOTT Safety, Monroe, North Carolina), were assessed on separate days. Sample media (sorbent tubes) and canisters (e.g., Summa) sampling were used to collect samples of the vapor stream entering and exiting the respirator cartridge and were subsequently analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and service life.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Out With the Old: Empirical Trends in U.S. Land‐Based Wind Turbine Decommissioning and Repowering

A growing number of wind turbines (WTs) across the globe are now reaching or exceeding their expected service lifetime; WT decommissioning is on the rise. Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.

Decommissioning / End-of-life↗

Fluorinated Rocksalt Cathode with Ultra-high Active Li Content for Lithium-ion Batteries

The key to increasing the energy density of lithium-ion batteries is to incorporate high contents of extractable Li into the cathode. Unfortunately, this triggers formidable challenges including structural instability and irreversible chemistry under operation. Here, we report a new kind of ultra-high Li compound: Li 4+x MoO 5 F x (1≤x≤3) for cathode with an unprecedented level of electrochemically active Li (>3 Li + per formula), delivering a reversible capacity up to 438 mAh g –1 . Unlike other reported Li-rich cathodes, Li 4+x MoO 5 F x presents distinguished structure stability to immunize against irreversible behaviors. In this work, through spectroscopic and electrochemical techniques, we find an anionic redox-dominated charge compensation with negligible oxygen release and voltage decay. Our theoretical analysis reveals a “reductive effect” of high-level fluorination stabilizes the anionic redox by reducing the oxygen ions in pure-Li conditions, enabling a facile, reversible, and high Li-portion cycling.

36 MATERIALS SCIENCE↗