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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Resonance ultrasound prediction of residual stress within a hybrid layer for additively manufactured samples

Hybrid additive manufacturing (AM) involves secondary processes or energy sources to alter specified locations within the build volume. Each hybrid step can refine the grain size, increase dislocation density, or modify residual stresses. Typically, the changes in mechanical properties are not confined within a single layer but have a compounding effect on preceding layers. Existing methods of measuring AM residual stress are limited in terms of their sensitivity, or they are destructive measurements. We propose using resonant ultrasound spectroscopy (RUS) to measure the residual stress in hybrid-AM components noninvasively, based on changes to the resonances, compared to a stress-free component. In this paper, we use finite element models to simulate residual stress in hybrid-AM components and to examine the sensitivity of RUS measurements in terms of frequency shifts and mode shapes with respect to single hybrid layers. Then, the RUS results are used to predict stress for a layer at a known location with unknown stress. Here, the approach highlights the capabilities of RUS to address an AM characterization challenge.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Self-Assembled BaTiO 3 –Au x Ag 1– x Low-Loss Hybrid Plasmonic Metamaterials with an Ordered “Nano-Domino-like” Microstructure

Metallic plasmonic hybrid nanostructures have attracted enormous research interest due to the combined physical properties coming from different material components and the broad range of applications in nanophotonic and electronic devices. However, the high loss and narrow range of property tunability of the metallic hybrid materials have limited their practical applications. In this study, a metallic alloy-based self-assembled plasmonic hybrid nanostructure, i.e., a BaTiO 3 –Au x Ag 1– x (BTO) vertically aligned nanocomposite, has been integrated by a templated growth method for low-loss plasmonic systems. Comprehensive microstructural characterizations including high-resolution scanning transmission electron microscopy (HRSTEM), energy-dispersive X-ray spectroscopy (EDS), and three-dimensional (3D) electron tomography demonstrate the formation of an ordered “nano-domino-like” morphology with Au 0.4 Ag 0.6 nanopillars as cylindrical cores and BTO as square shells. By comparing with the BTO–Au hybrid thin film, the BTO–Au 0.4 Ag 0.6 alloyed film exhibits much broader plasmon resonance, hyperbolic dispersion, low-loss, and thermally robust features in the UV–vis–NIR wavelength region. This study provides a feasible platform for a complex alloyed plasmonic hybrid material design with low-loss and highly tunable optical properties toward all-optical integrated devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Minimizing hydrogen vacancies to enable highly efficient hybrid perovskites

Defect-induced non-radiative losses are currently limiting the performance of hybrid perovskite devices. Experimental reports have indicated the existence of point defects that act as detrimental non-radiative recombination centres under iodine-poor synthesis conditions. However, the microscopic nature of these defects is still unknown. Here we demonstrate that hydrogen vacancies can be present in high densities under iodine-poor conditions in the prototypical hybrid perovskite MAPbI 3 (MA = CH 3 NH 3 ). They act as very efficient non-radiative recombination centres with an exceptionally high carrier capture coefficient of 10 –4 cm 3 s –1 . By contrast, the hydrogen vacancies in FAPbI 3 [FA = CH(NH 2 ) 2 ] are much more difficult to form and have a capture coefficient that is three orders of magnitude lower. Our study unveils the critical but overlooked role of hydrogenvacancies in hybrid perovskites and rationalizes why FA is essential for realizing high efficiency in hybrid perovskite solar cells. Furthermore, minimizing the incorporation of hydrogen vacancies is key to enabling the best performance of hybrid perovskites.

14 SOLAR ENERGY↗
DOE OSTI2020

Designing a hybrid electrode toward high energy density with a staged Li + and PF 6 - deintercalation/intercalation mechanism

Existing lithium-ion battery technology is struggling to meet our increasing requirements for high energy density, long lifetime, and low-cost energy storage. Here, a hybrid electrode design is developed by a straightforward reengineering of commercial electrode materials, which has revolutionized the “rocking chair” mechanism by unlocking the role of anions in the electrolyte. Our proof-of-concept hybrid LiFePO 4 (LFP)/graphite electrode works with a staged deintercalation/intercalation mechanism of Li + cations and PF 6 - anions in a broadened voltage range, which was thoroughly studied by ex situ X-ray diffraction, ex situ Raman spectroscopy, and operando neutron powder diffraction. Introducing graphite into the hybrid electrode accelerates its conductivity, facilitating the rapid extraction/insertion of Li + from/into the LFP phase in 2.5 to 4.0 V. This charge/discharge process, in turn, triggers the in situ formation of the cathode/electrolyte interphase (CEI) layer, reinforcing the structural integrity of the whole electrode at high voltage. Consequently, this hybrid LFP/graphite-20% electrode displays a high capacity and long-term cycling stability over 3,500 cycles at 10 C, superior to LFP and graphite cathodes. Importantly, the broadened voltage range and high capacity of the hybrid electrode enhance its energy density, which is leveraged further in a full-cell configuration.

25 ENERGY STORAGE↗
DOE OSTI2020

Natural selection maintains species despite frequent hybridization in the desert shrub Encelia

Natural selection is an important driver of genetic and phenotypic differentiation between species. For species in which potential gene flow is high but realized gene flow is low, adaptation via natural selection may be a particularly important force maintaining species. For a recent radiation of New World desert shrubs ( Encelia : Asteraceae), we use fine-scale geographic sampling and population genomics to determine patterns of gene flow across two hybrid zones formed between two independent pairs of species with parapatric distributions. After finding evidence for extremely strong selection at both hybrid zones, we use a combination of field experiments, high-resolution imaging, and physiological measurements to determine the ecological basis for selection at one of the hybrid zones. Our results identify multiple ecological mechanisms of selection (drought, salinity, herbivory, and burial) that together are sufficient to maintain species boundaries despite high rates of hybridization. Given that multiple pairs of Encelia species hybridize at ecologically divergent parapatric boundaries, such mechanisms may maintain species boundaries throughout Encelia .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Automated Hybrid Variance Reduction on Advanced Architectures in the Shift Monte Carlo Code

Monte Carlo transport methods are the most accurate schemes for solving problems with complex energy and spatial features, but they come with a high computational cost. Although hybrid methods have enabled the use of Monte Carlo transport for a large class of problems, they still require significant computing resources. Modern multicore CPUs with large numbers of compute cores and graphical processing units (GPUs) provide opportunities to optimize the memory and run-time costs of hybrid Monte Carlo methods. This paper documents the development and analysis of three Monte Carlo transport algorithms that support hybrid transport using the consistent adjoint-driven importance sampling (CADIS) and forward-weighted CADIS methods in the Shift Monte Carlo code: history-based transport using static and dynamic threading on multicore CPUs and event-based transport enabling weight window tracking on GPUs. The results are shown for two challenging hybrid problems on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility. The results show that all three methods yield good performance and enable solutions of difficult fixed-source transport problems in less than 2 min on 20 nodes of Frontier. Dynamic threading was observed to give up to 20% better scaling behavior than static threading. Moreover, the AMD Instinct 250X GPU was found to give 9 to 11 times greater throughput per graphics compute die than the best CPU performance. In conclusion, additional opportunities for optimization of hybrid transport on GPUs are discussed.

Denovo↗
DOE OSTI2023

Design and Techno-Economic Analysis of a 150-MW Hybrid CSP-PV Plant

The interest in concentrated solar power (CSP) has increased significantly over the years since it is dispatchable and requires thermal storage instead of electric storage. When compared to photovoltaics (PV), CSP has a higher Levelized Cost of Electricity (LCOE). In this paper, we present the design of a hybrid power plant using CSP and PV technologies. The hybrid system offers a lower LCOE than CSP but will still have dispatchability. The 150-MW hybrid system consists of 100-MW CSP and 50-MW PV capacity. Furthermore, the CSP system (central receiver system) has a molten salt-based thermal storage of 12 hours. The geographical focus of this study is Pakistan, which is a developing country struggling with energy crises, but which has high solar potential. The hybrid system is modeled using the System Advisor Model (SAM). The results show that by hybridizing CSP with PV, the LCOE can be reduced by 18.5%.

concentrated solar power↗
DOE OSTI2022

Hybrid Organic Inorganic Perovskites: Physical Properties and Applications (in 4 Volumes)

This four-volume handbook gives a state-of-the-art overview of hybrid organic inorganic perovskites, both two dimensional (2D) and three dimensional (3D), from synthesis and characterization and simulation to optoelectronic devices (such as solar cells and light emitting diodes), spintronics devices and catalysis application. The editors, coming from academia and national laboratory, are known for their didactic skills as well as their technical expertise. Coordinating the efforts of 30 expert authors in 21 chapters, they construct the story of hybrid perovskite structural and optical properties, electronic and spintronic response, laser action, and catalysis from varied viewpoints: materials science, chemical engineering, and energy engineering. The four volumes are arranged according to the focus material properties. Volume 1 is focused on the material physical properties including structure, deposition characteristic and the structure of the electronic bands and excitons of these compounds. Volume 2 covers the hybrid perovskite optical properties including the ultrafast optical response, photoluminescence and laser action. Volume 3 contains the spin response of these compounds including application such as spin valves, photogalvanic effect, and magnetic response of light emitting diodes and solar cell devices. Finally, and highly relevant to tomorrow's energy challenges, volume 4 is focused on the physics and device properties of the most relevant applications of the hybrid perovskites, namely photovoltaic solar cells. The text contains many high-quality colorful illustrations and examples, as well as thousands of up-to-date references to peer-reviewed articles, reports and websites for further reading. This comprehensive and well-written handbook is a must-have reference for universities, research groups and companies working with the hybrid organic inorganic perovskites.

applications↗
DOE OSTI2020

Opportunities for Research and Development of Hybrid Power Plants

Hybrid power plants show promise to provide significant value to the electric grid system especially as shares of renewable energy in systems increase from 10% to 20% or more. Many manufacturers and developers are proactively developing hybrid power plant strategies to ensure plant profitability in markets where it’s important to provide energy that is more predictable and controllable, with higher capacity values, as well as various ancillary services to the grid system. However, there still are many questions around if and when hybrid power plants make sense versus leaving it to the larger grid system to ensure low cost and reliable supply by engaging directly with all individual assets. This report summarizes literature on the state-of-the-art in research concerning hybrid power plants from multiple perspectives including: 1) resource and market opportunities, 2) technology selection and sizing, 3) physical design, and 4) operation and control. The emphasis was placed on wind and solar hybrid power plants (with or without storage) but additional technologies were briefly considered and merit further investigation.

17 WIND ENERGY↗
DOE OSTI2020

Hybrid Electric Drivetrain Testing and Design (CRADA CRD-17-00699 Final Report)

Hybrid electric drivetrains have recently become of a great interest in the medium and heavy-duty vehicle market as it enables substantial reduction of petroleum use, vehicle level fuel use and criteria pollutant emissions. These vehicle performance improvements are not only economically beneficial for business operations relying on large fleets of vehicles, they are also paramount for curbing energy use and the negative effects of vehicle operations on the environment. Efficient Drivetrains, Inc. (EDI), acquired in July 2018 by Cummins, Inc., is a small company focused on development of medium and heavy-duty hybrid electric drivetrains. EDI has already developed the general hardware architecture of their drivetrain system, but there is still a significant effort to be done on optimizing the system in terms of control strategies and component sizing in order to maximize the benefits of the hybrid drivetrain. Historically, hybrid electric systems have proven to deliver better fuel economy in certain applications than their conventional counterparts. Particular areas of advantageous applications are vocations with kinetically intensive transient duty cycles and operations requiring some sort of power take off whose power demand is not well matched to the size of the vehicle’s main engine, thus forcing it to operate in extremely inefficient operating modes. Hybrid drivetrains can be at a disadvantage when pressed into duty cycle operation consisting of extensive steady state highway cruise due to various design compromises optimized for more transient operation. This can also lead to increase in vehicle emissions if the system is not optimized properly. Ample opportunity for extensive optimization is needed to overcome these obstacles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Hybrid Electric Drivetrain Testing and Design (CRADA CRD-17-00699 Final Report)

Hybrid electric drivetrains have recently become of a great interest in the medium and heavy-duty vehicle market as it enables substantial reduction of petroleum use, vehicle level fuel use and criteria pollutant emissions. These vehicle performance improvements are not only economically beneficial for business operations relying on large fleets of vehicles, they are also paramount for curbing energy use and the negative effects of vehicle operations on the environment. Efficient Drivetrains, Inc. (EDI), acquired in July 2018 by Cummins, Inc., is a small company focused on development of medium and heavy-duty hybrid electric drivetrains. EDI has already developed the general hardware architecture of their drivetrain system, but there is still a significant effort to be done on optimizing the system in terms of control strategies and component sizing in order to maximize the benefits of the hybrid drivetrain. Historically, hybrid electric systems have proven to deliver better fuel economy in certain applications than their conventional counterparts. Particular areas of advantageous applications are vocations with kinetically intensive transient duty cycles and operations requiring some sort of power take off whose power demand is not well matched to the size of the vehicle’s main engine, thus forcing it to operate in extremely inefficient operating modes. Hybrid drivetrains can be at a disadvantage when pressed into duty cycle operation consisting of extensive steady state highway cruise due to various design compromises optimized for more transient operation. This can also lead to increase in vehicle emissions if the system is not optimized properly. Ample opportunity for extensive optimization is needed to overcome these obstacles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Hybrid Heavy Duty Diesel Powertrain for Off-Road Applications (Final Technical/Scientific Report)

In this program, a heavy-duty hybrid powersystem, consisting of a 30% downsized diesel engine and a front-end accessory drive (FEAD) incorporating a high-speed flywheel (HSFW) energy storage system, a mechanical-drive turbocharger (SuperTurbo), and motor-generator units (MGU) was developed and demonstrated. The high efficiency core 13L engine coupled with the hybrid elements was physically validated across various off-road machine and transient work cycles with the ultimate goal of demonstrating 17% efficiency improvement with equivalent transient response as the 18L diesel engine this concept powersystem would replace. The project culminated in a physical demonstration of the high-efficiency powersystem in a high-capability test cell with the engine, all the hybrid devices, controls, and required performance and emissions measurements. Based on the combination of physical validation and rigorous system simulation, the following program conclusions may be drawn: (1) The developed hybrid H2D2 powersystem demonstrated a range of efficiency improvement of 10.5 - 25.6%, with a midpoint of 17.9%; (2) Transient load response on; (3) The HSFW system was validated to achieve peak assisting of 110kW at 12,000 Nm/sec ramp rates; (4) The powersystem was validated to be capable of meeting U.S. EPA Tier 4 Final off-road emissions through transient NRTC testing; (5) A Total Cost of Ownership (TCO) analysis and found that the core 13L engine would pay back immediately (adoption of start/stop would pay back in less than one year, and the full hybrid system payback was three years.)

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterization of Gramicidin A in Triblock and Diblock Polymersomes and Hybrid Vesicles via Continuous Wave Electron Paramagnetic Resonance Spectroscopy

Studying membrane proteins in a native environment is crucial to understanding their structural and/or functional studies. Often, widely accepted mimetic systems have limitations that prevent the study of some membrane proteins. Micelles, bicelles, and liposomes are common biomimetic systems but have problems with membrane compatibility, limited lipid composition, and heterogeneity. To overcome these limitations, polymersomes and hybrid vesicles have become popular alternatives. Polymersomes form from amphiphilic triblock or diblock copolymers and are considered more robust than liposomes. Hybrid vesicles are a combination of lipids and block copolymers that form vesicles composed of a mixture of the two. These hybrid vesicles are appealing because they have the native lipid environment of bilayers but also the stability and customizability of polymersomes. Gramicidin A was incorporated into these polymersomes and characterized using continuous wave electron paramagnetic resonance (CW-EPR) and transmission electron microscopy (TEM). EPR spectroscopy is a powerful biophysical technique used to study the structure and dynamic properties of membrane proteins in their native environment. Spectroscopic studies of gramicidin A have been limited to liposomes; in this study, the membrane peptide is studied in both polymersomes and hybrid vesicles using CW-EPR spectroscopy. Lineshape analysis of spin-labeled gramicidin A revealed linewidth broadening, suggesting that the thicker polymersome membranes restrict the motion of the spin label more when compared to liposome membranes. Statement of Significance: Understanding membrane proteins’ structures and functions is critical in the study of many diseases. In order to study them in a native environment, membrane mimetics must be developed that can be suitable for obtaining superior biophysical data quality to characterize structural dynamics while maintaining their native functions and structures. Many currently widely accepted methods have limitations, such as a loss of native structure and function, heterogeneous vesicle formation, restricted lipid types for the vesicle formation for many proteins, and experimental artifacts, which leaves rooms for the development of new biomembrane mimetics. The triblock and diblock polymersomes and hybrid versicles utilized in this study may overcome these limitations and provide the stability and customizability of polymersomes, keeping the biocompatibility and functionality of liposomes for EPR studies of membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Renewable-Storage Hybrids in a Decarbonized Electricity Supply

We explore the potential impacts of growing industry interest in hybrid systems comprising PV and battery technologies on the results and findings of the Solar Futures Study (2021). Through comparison of Solar Futures Study scenarios with and without PV-battery hybrid configurations enabled (in the same grid planning model), we find that the highest net-value hybrid configuration depends strongly on power sector carbon policy, which increases the value of more forward-looking designs. While the availability of PV-battery hybrid configurations primarily displaces standalone PV and battery capacity, we find that it (a) increases solar's share of total capacity and generation and (b) reduces required transmission expansion and associated costs under scenarios that combine aggressive cost reductions and power sector decarbonization policy. Results will also be presented for the complementarity and economic value of wind-PV hybrids with varying amounts of energy storage.

complementarity↗
DOE OSTI2025

Hybrid Doping Strategy with High‐Entropy Cu/Fe Surface Modification and Zr Bulk Incorporation for Ni‐Rich Cathodes

A hybrid doping strategy combining Zr 4+ bulk doping with high-entropy Cu 2+ /Fe 3+ surface doping is developed to enhance the structural and interfacial stability of Ni-rich layered oxide cathodes. Cu and Fe are selectively introduced at the particle surface via a surface-selective ion-exchange process, forming a ≈15 nm Fe-rich layer while preserving the layered framework. Compared to the pristine cathode, the hybrid sample exhibits significantly improved electrochemical performance in both half-cell and full-cell configurations. In half-cells, the hybrid retains 88.5% and 90.2% after 100 cycles at 1C under 4.6 and 4.5 V, respectively. During high-voltage full-cell cycling, the hybrid cathode maintains over 80% capacity retention, whereas the pristine counterpart retains less than 10% under identical conditions over the same cycling period. XPS, EELS, and DEMS analyses confirm improved oxygen retention, suppressed gas evolution, and stable surface chemistry, while DFT calculations indicate enhanced Me–O bonding in the selected Fe 0.75 Cu 0.25 (Mn 1/16 Co 2/16 Ni 13/16 )O 2 surface composition, which is identified through DFT-calculated mixing energy reaching a minimum at this ratio, indicating the most thermodynamically favorable configuration. In conclusion, these results demonstrate the effectiveness of this hybrid doping strategy in mitigating coupled degradation pathways in Ni-rich cathodes.

15 GEOTHERMAL ENERGY↗