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At least 595 records · Page 33

Beyond conventional batteries: a review on semi-solid and redox targeting flow batteries-LiFePO{sub 4} as a case study.

Clean and sustainable energy is becoming increasingly crucial to tackle the current energy crisis. However, the intermittent nature of renewable energy sources presents a challenge for their effective implementation. Redox flow batteries (RFBs) have emerged as a promising solution to this problem, as they can help enhance the stability of grid networks and promote the use of renewable energy sources. RFBs are highly modular and scalable systems that can be customized to meet the power and energy requirements of different renewable energy plants. Moreover, they offer several advantages over conventional battery technologies, including cost and safety concerns. However, conventional RFBs have limited energy densities due to the low solubility of their active species in electrolyte. To overcome this limitation, semi-solid (SSRFBs) and redox targeting (RTFBs) flow batteries have been proposed. These systems feature high concentrations of active species and impressive energy densities, making them highly attractive for renewable energy applications. LiFePO4 (LFP) is a highly promising active material for semi-solid and targeting flow batteries. One of the key advantages of LFP is its low raw materials cost, as it is composed of Earth-abundant elements such as iron and phosphorus. This makes it an attractive option for large-scale battery production. The recent developments in SSRFBs and RTFBs using LFP as catholyte hold great promise for the future of sustainable energy storage. The combination of LFP's low cost, safety, durability, and high energy density with the modularity and scalability of flow battery systems make for a compelling solution to the challenges of intermittent renewable energy sources. Ongoing research and development in this area will likely yield even further improvements in the performance and efficiency of LFP-based flow batteries, opening exciting new possibilities for sustainable energy storage.

El Halya, Nabil↗

Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration

Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).

Ward, Laura (ORCID:0000000345501581)↗

Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Abstract Large‐scale power systems exhibit more complex dynamics due to the increasing integration of inverter‐based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide‐Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large‐scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra‐high density synchrophasor and point‐on‐wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)‐based advanced applications are introduced, including AI‐based inertia estimation, AI‐based disturbance size and location estimation, AI‐based system stability assessment, and AI‐based data authentication.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Eliminating the Burn‐in Loss of Efficiency in Organic Solar Cells by Applying Dimer Acceptors as Supramolecular Stabilizers

Abstract The meta‐stable active layer morphology of organic solar cells (OSCs) is identified as the main cause of the rapid burn‐in loss of power conversion efficiency (PCE) during long‐term device operation. However, effective strategies to eliminate the associated loss mechanisms from the initial stage of device operation are still lacking, especially for high‐efficiency material systems. Herein, the introduction of molecularly engineered dimer acceptors with adjustable thermal transition properties into the active layer of OSCs to serve as supramolecular stabilizers for regulating the thermal transitions and optimizing the crystallization of the absorber composites is reported. By establishing intimate π‐π interactions with small‐molecule acceptors, these stabilizers can effectively reduce the trap‐state density (N t ) in the devices to achieve excellent PCEs over 19%. More importantly, the lowN t associated with an initially optimized morphology can be maintained under external stresses to significantly reduce the PCE burn‐in loss in devices. This research reveals a judicious approach to improving OPV stability by establishing a comprehensive correlation between material properties, active‐layer morphology, and device performance, for developing burn‐in‐free OSCs.

Chemistry↗

Distribution Grid Incentive Design with Unknown Agent Behavior

Motivation: During extreme events, traditional grid regulation methods (e.g., energy prices, net power injection limits) may be insufficient. While system operators typically lack control over end-user grid interactions, (e.g., energy demand), incentives can influence behavior - for example, a user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. Problem: Optimize for the best incentive subject to system stability constraints. However, user behavior is unknown to the SO - i.e., for a given incentive, the amount of curtailed load or control variables exposed is unknown.

feedback based control↗

Epitaxial Stabilization and Oxygen Evolution Reaction Activity of Metastable Columbite Iridium Oxide

Non-rutile polymorphs of binary iridium oxide such as columbite IrO 2 (α-IrO 2 ) are promising candidates for highly active acid-stable oxygen evolution reaction (OER) catalysts, yet their synthesis has been challenging due to the dominant thermodynamic stability of rutile IrO 2 (R-IrO 2 ). Here, we report the growth of α-IrO 2 via epitaxial thin films using pulsed laser deposition. We observe that, in competition with R-IrO 2 (100), the films can be optimized to be predominantly (100)-oriented α-IrO 2 . Surprisingly, the activity of α-IrO 2 shows a large discrepancy of ~0.2 V in the overpotential compared to its predicted activity, which is resolved via theoretical calculations to be a crystal orientation effect. This demonstrates that the electrocatalytic activity can be significantly varied upon crystal orientation, a parameter that is difficult to control in conventional polycrystalline systems but accessible in epitaxial thin films. In total, this study demonstrates epitaxial thin film growth as a powerful technique, which can overcome large energetic instabilities on the order of ~300 meV to stabilize metastable material structures inaccessible by bulk synthesis. As a result, this provides unique opportunities to effectively identify the atomic structure of active catalysts by combining investigations of metastable materials with theoretical predictions.

36 MATERIALS SCIENCE↗

A Multidisciplinary Approach to Integrated Energy Systems: Advanced Nuclear Plants with Thermal Storage for Dynamic and Flexible Operation in Diverse Markets

Energy supply, distribution, and demand are continuously evolving in accordance with the integration of new power generation sources. In the United States, there is a progressive shift toward incorporating fluctuating energy sources such as wind and solar into the energy mix, alongside the distributed generation. Simultaneously, we are seeing a revolution in consumer technologies such as electric vehicles, energy devices for both residential and commercial use, and industrial processes—all contributing to a fundamental change in energy consumption dynamics. These scenarios have led to huge demand for enhanced flexibility from nuclear power plants (NPPs), requiring them to operate with unprecedented adaptability. Furthermore, advanced NPPs (A-NPPs) could potentially apply to scenarios in which power generation flexibility is prioritized over its current and conventional baseload generation capacity for traditional demand patterns. The present work covers several configurations for coupling nuclear energy production with thermal energy storage (TES). Previous work evaluated systems entailing a simple nuclear-TES configuration that used steam as a heat source for the TES of three different advanced reactors (ARs), but its heat diversion ratio (HDR) for charging was limited. The present work proposes a new configuration that features full decoupling of the nuclear reactor and the power cycle, using reactor coolant (i.e., gas) as a heat source for the TES and offering a theoretically unlimited HDR. This configuration is, however, more complex, as both high- and low-temperature TES (HT-TES and LT-TES) systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Conventional TES systems take advantage of nominal efficiency when discharging, whereas the reheat cycle in the fully decoupled TES system affords a significant efficiency increase over conventional cases. Material selection, component/equipment sizing, and costing analyses were performed, followed by economic dispatch and size optimization. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation (e.g., drops in cycle efficiency), and these models enable exploration of potential mitigation strategies for addressing such drops. The models also highlight the need to design fail-safes that ensure continuous operational stability and minimize the impact of power ramping on the reactor parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics

Online transient analysis plays an increasingly important role in dynamic power grids as the renewable generation continues growing. Traditional numerical methods for transient analysis not only are computationally intensive but also require precise contingency information as input, and therefore, are not suitable for online applications. Existing online transient assessment studies focus on the determination of post-contingency system stability or stability margin. Here, this paper develops a novel graph-learning framework, Deep-learning Neural Representation or DNR, for online prediction, of the time-series trajectories of the system states using initial system responses that can be measured by phasor measurement units (PMUs). The proposed DNR framework consists of two sequential modules: a Network Constructor that captures network dependencies among generators, and a Dynamics Predictor that predicts the system trajectories. The key to improved prediction performance is the introduction of the spatio-temporal message-passing operations into graph neural networks with structural knowledge. Its effectiveness and scalability are validated through comparative studies, demonstrating the prediction performance under different contingency scenarios for systems of different sizes. This framework provides a solution to online predicting post-fault system dynamics based on real-time PMU measurements. Additionally, it can also be applied to facilitate the offline transient simulation without simulating the entire trajectories.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantification of storage required for preserving frequency security in wind‐integrated systems

Abstract The penetration of wind power generation into the power grid has been accelerated in recent times due to the aggressive emission targets set by governments and other regulatory authorities. Although wind power has the advantage of being environment‐friendly, wind as a resource is intermittent in nature. In addition, wind power contributes little inertia to the system as most wind turbines are connected to the grid via power electronic converters. These negative aspects of wind power pose serious challenges to the frequency security of power systems as penetration increases. In this work, an approach is proposed where an energy storage system (ESS) is used to mitigate frequency security issues of wind‐integrated systems. ESSs are well equipped to supply virtual inertia to the grid due to their fast‐acting nature, thus replenishing some of the energy storage capability of displaced inertial generation. In this work, a probabilistic approach is proposed to estimate the amount of inertia required by a system to ensure frequency security. Reduction in total system inertia due to the displacement of conventional synchronous generation by wind power generation is considered in this approach, while also taking into account the loss of inertia due to forced outages of conventional units. Monte Carlo simulation is employed for implementing the probabilistic estimation of system inertia. An ESS is then sized appropriately, using the system swing equation, to compensate for the lost inertia. The uncertainty associated with wind energy is modeled into the framework using an autoregressive moving average technique. Effects of increasing the system peak load and changing the wind profile on the expected system inertia are studied to illustrate various factors that might affect system frequency security. The proposed method is validated using the IEEE 39‐bus test system.

17 WIND ENERGY↗

Fabrication and installation of the Mu2e cryogenic distribution system

The muon-to-electron conversion (Mu2e) experiment at Fermilab will be used to search for the charged lepton flavor-violating conversion of muons to electrons in the field of an atomic nucleus. The Mu2e experiment is currently in the construction stage. The scope of this paper is the cryogenic distribution system and superconducting power leads for four superconducting solenoid magnets: Production Solenoid (PS), an Upstream and Downstream Transport Solenoids (TSu and TSd) and Detector Solenoid (DS). The design of the cryogenic distribution system and the fabrication of several sub-systems was reported previously. This paper reports on additional fabrication and installation progress that has been performed over the past two years. Lessons learned during fabrication and testing of the cryogenic distribution system components are described. In particular, the challenges and solutions implemented for aluminum welding are reported. A description of the process used to qualify the welding procedure and welders for welding the aluminium stabilized NbTi superconducting power leads is provided. Additionally, the progress made with regards to installing the power leads into the cryogenic Feedboxes is covered.

White, Michael J.↗

A Compact, Single Stage, >1 kV Medium-Voltage Line Impedance Stabilization Network

This paper presents the design of a single-phase, single-stage line impedance stabilization network (LISN) for medium-voltage (MV) applications. More than 1 kV rated widebandgap (WBG) power semiconductor switches are increasingly utilized in new, emerging power electronics energy systems to improve power density and efficiency. However, due to inherently fast-switching speeds, WBG switch modules emit considerable electromagnetic interference (EMI) (e.g., common mode (CM) or differential mode (DM)). State-of-the-art offers standardized LISN solutions to validate and certify the new energy system for electromagnetic compatibility (EMC). However, most are for low voltage applications (i.e., < 1 kV). MV LISNs (i.e., > 1 kV) are rare until recently and literature does not provide sufficient guidelines for designing and characterizing such devices. It has been a critical challenge for many scientists and engineers to reliably certify the emerging MV energy systems (e.g., electric ships and aircraft). This paper addresses such a technology gap. Specifically, a CISPR 16-1-2 compliant 50Ω/50μH LISN with 1.5kV, 75A and 30MHz measurement capability has been proposed. Detailed performance study versus non-linear parasitic parameters variations in MV inductors and capacitors have been done. Based on new understandings, novel techniques to intuitively mitigate unwanted parasitic have been proposed to develop the proposed LISN successfully. Thorough characterization of important LISN parameters are presented and factors influencing them are analyzed. A rigorous analysis, experimental tests, and in-depth comparisons over state-of-the-art have been made to validate the effectiveness. This is done through the state-of-the-art 300kVA MV EMI testbed.

42 ENGINEERING↗

Modifications to Solar Titan-130 Combustion Systems for Efficient, High Turndown Operation

The project team of Southwest Research Institute® (SwRI®), Solar Turbines Incorporated (Solar), the Electric Power Research Institute (EPRI), the University of California, Irvine (UCI), and the Georgia Institute of Technology (Georgia Tech) investigated methods to allow higher efficiency part-load operation of a Solar Titan 130 gas turbine. The objective was to develop a low-emission combustion system capable of sustaining combustion and avoiding lean blowout during high turndown operation, which would allow the gas turbine to operate as efficiently as possible at part load. Currently, electric utility markets are beginning to experience substantial increases in renewable energy generation. Some of these renewable energy sources have highly variable output in an uncontrolled manner. In order to maintain grid stability, there is a need for power plants to ramp up power to the grid rapidly to make up for drops in renewable generation. This is often termed spinning reserve, but the size of this reserve may need to increase as renewable penetration into the electric utility market increases. Small combined heat and power (CHP) power plants provide a promising option for meeting this spinning reserve requirement. In order to operate in spinning reserve while still meeting the heat requirements for the CHP, the gas turbine needs to operate efficiently at very low loads. Efficient, high turndown operations in this engine are limited by the lean flammability limit of the premixed combustion system. This project sought enhance the lean operability range of the Titan 130 combustor. First, the project team participated in a brainstorming activity and ultimately selected two concepts to explore: fuel augmentation with hydrogen (H2) to improve the stability at lean operating conditions and modifications to the fuel nozzle to improve the emissions performance at lean operating conditions. Analytical and laboratory investigations were accomplished by UCI to investigate the efficacy of H2 addition at improving lean blow out (LBO) limits and the resulting emissions. These investigations used a variety of chemical reactor network (CRN) and CFD models, validated against laboratory data, to model the impact of H 2 and inform the experimental efforts accomplished by SwRI and Solar. Ultimately, both the CRN and CFD models yielded generally good agreement with the experimental data below a particular temperature threshold. Atmospheric tests of a full-scale T130 annular combustor were performed at SwRI facilities in San Antonio, Texas, to investigate the use of H 2 addition. For these tests, the T130 combustion system remained largely unchanged; minor modifications were performed to the fuel ducting to allow for the safe use of H 2 . The test ultimately demonstrated that the addition of H 2 to the fuel mixture significantly increased the AFR ratio at which the combustor could operate. This improvement to the LBO limit should allow for less use of compressor bleed and less throttling needed by the inlet guide vanes (IGV). This in turn could result in more efficient operation of the gas turbine at lower load points. The second modification explored in this work was a direct modification to the T130 injector. The project team hypothesized that modifications to the pilot of the T130 injector could provide lower emissions at high turn-down operations. These modifications were manufactured and explored by the team at Solar. High pressure rig tests, originally slated to occur at SwRI, were ultimately accomplished by Solar to maintain overall project budget and mitigate cost growth attributable to supply chain issues and inflation. The pressurized rig tests ultimately showed that the SwRI Project No. 18.24153 - DE-EE0008415 Page 2 Final Technical Report January 24, 2024 modifications did not significantly alter the performance of the combustion system at the high turn-down conditions; both the modified injectors and the baseline configuration exhibited elevated emissions comparted to the full-load operating condition. A final set of studies performed by EPRI investigated the benefit-cost of flexible CHP as well as a grid interconnection study for the California Independent System Operator (CAISO) grid. These studies considered: traditional CHP with no spinning reserve available for on-demand grid support, 50% flexible CHP where 50% of the machine’s capacity is consumed by on-site baseload operations while providing an additional 50% capacity for on-demand grid support, and 70% flexible CHP where 70% of capacity is consumed on-site by baseload operations and 30% is available for on-demand grid support. In all cases, the analyses showed a benefit-to-cost ratio greater than unity implying a positive net present value for all configurations. However, the traditional CHP showed the most economic benefit. These results are sensitive to several factors, many of which are not fully known and may vary over time. Thus site owners must be convinced that taking up the increased costs and risks from flexible CHP would be worth implementing. As the grid in California and across the country transition to incorporate larger renewable energy generation, flexible CHP can provide much needed operating reserves and dispatchability. Alternative fuel options, such as hydrogen blending and biofuels, may also lower carbon intensities of CHP. Flexible CHP should be examined in the evolving market to understand innovative business models, changes market rules and services, and new technologies.

20 FOSSIL-FUELED POWER PLANTS↗

Inertia estimation for power grids: A review of methods, challenges, and future prospects

The electric power grid is undergoing a significant transformation, shifting from traditional synchronous generators to inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and energy storage systems. This evolution leads to a reduction in system inertia, a critical attribute for maintaining frequency stability in response to disturbances. Consequently, the ability to monitor and estimate system inertia has become increasingly essential. This paper provides a comprehensive review of existing inertia estimation methodologies, analyzing them from multiple perspectives, including the types of data utilized, underlying estimation principles, operational modes, and system-wide applicability. A comparative summary table is included to distill commonalities and key characteristics across various studies. In addition, the paper examines practical implementations of inertia estimation across several major power systems worldwide, including the U.S. interconnections, the Nordic power system, and the U.K. grid. Key challenges are identified, particularly in estimating contributions from virtual inertia sources and load-induced inertia in increasingly converter-dominated networks. To address these emerging challenges, the paper proposes an integrated framework for real-time inertia estimation and monitoring. This framework encompasses critical components such as data acquisition, inertia estimation from both synchronous and non-synchronous sources, load-induced effects, optimization techniques, forecasting, and virtual inertia scheduling. Collectively, these elements enable dynamic, system-wide monitoring and adaptive control of grid inertia.

Inertia estimation↗

Cost and Performance Baseline for Fossil Energy Plants, Volume 5: Natural Gas Electricity Generating Units for Flexible Operation

To address the data needs of energy system designers and to serve as a baseline for research and development, NETL has carried out a study to characterize the flexibility attributes - both performance and cost - of nine common commercial natural gas-fueled electricity generating units. The intermittent output of low-carbon, renewable power generation sources such as wind and solar create challenges to grid stability and reliability. Fossil-fueled power generation technologies are currently used to provide reliable, on-demand power during periods of reduced renewable output. Dispatchable generators must be able to accommodate increasing renewable generation as the nation pursues the Administration’s target of a decarbonized energy sector by 2035. As energy system experts seek to identify least-cost approaches to decarbonization, accurate cost and performance data characterizing dispatchable fossil generators that operate flexibly, at capacity factors that have been declining over time, and are needed to inform models for capacity expansion. Furthermore, these technologies continue to be a significant source of carbon dioxide emissions, providing the impetus for research and development, including the advancement and potential incorporation of carbon capture technologies. This study characterizes the cost and performance of select state-of-the-art natural gas-fueled power generation technologies: reciprocating internal combustion engines (RICE), simple cycle combustion turbines, and natural gas combined cycles (NGCC). An emphasis is placed on flexibility characteristics, such as part-load heat rate, ramp rates, start up times, and start up costs.

03 NATURAL GAS↗

Safe Exploration Reinforcement Learning for Load Restoration using Invalid Action Masking

This paper addresses the load restoration problem after a power outage event. Our primary proposed methodology uses a multi-agent reinforcement learning method to make the optimal sequential decisions on picking up critical loads. Typically, a negative reward is provided to discourage the agents from selecting decisions that violate physical constraints during the restoration process. However, the main disadvantage of this approach is its difficulty in applying it to large-scale systems due to the curse of dimensionality. This paper introduces the invalid action masking technique to overcome this limitation. The features of this technique include zero physical constraint violations, reduced training time, and stabilization of the explo- ration process. Simulation results are performed in IEEE 13-node and IEEE 123-node systems showing the better performance of the proposed algorithm in comparison to the conventional approaches both in terms of restored power and learning curve.

reinforcement learning, blackstart, artificial int↗

From Event Data to Wind Power Plant DQ Admittance and Stability Risk Assessment

This paper presents a dynamic event data-based stability risk assessment method for power grids with high penetrations of inverter-based resources (IBRs). This method relies on obtaining the IBRs' DQ admittance through dynamic event data and computing the system's eigenvalues based on the admittance models. Two critical technologies are employed in this research, including time-domain and frequency-domain data fitting and dq-frame voltage and current signal derivation. The first technology is key to obtaining the s-domain expressions from the transient response data, and the s-domain DQ admittance model from the frequency-domain measurements. The second technology is key to obtaining the dq-frame voltage and current signals from either the three-phase instantaneous measurements or the phasor measurement unit (PMU) data. The method is illustrated using data generated from a Type-4 wind power plant modeled in PSCAD. This paper demonstrates the technical feasibility of the proposed approach.

17 WIND ENERGY↗

Solid State Power Substations (SSPS): A Multi-Hierarchical Architecture from Substation to Grid Edge

With the growing deployment of distributed generation, or power electronic interfaced renewable energy and storage technologies, the nature and behavior of the grid is changing. Synchronous machine-driven asset contributions to the generation mix are shrinking, leading to concerns regarding grid stability. Furthermore, the scale of smaller distributed PE resources needed for managing the electrical network could dwarf the existing system leading to more complex optimization problems and communication interconnections. This paper introduces the concept of a hierarchal system of controllers that spans the grid edge or the customer end to distribution scale substations or solid-state power substation (SSPS). This concept focuses on minimizing the number of interfaces and optimization considerations in the grid by clustering resources into nodes and hubs. The work validates the concept in a controller hardware-in-the-loop (cHIL) platform.

Chinthavali, Madhu Sudhan↗

Oxidation‐Driven Enhancement of Intrinsic Properties in MXene Electrodes for High‐Performance Flexible Energy Storage

Abstract MXenes, a novel class of 2D materials, exhibit great potential for energy storage due to their unique layered structure and excellent electrical conductivity. However, improving the intrinsic electrochemical storage capacity of MXenes remains a significant challenge, often requiring the incorporation of other Faradaic materials. Oxidation, in particular, poses a key issue that impacts the capacity of MXene devices. In this study, controlled oxidation is employed to create nanoscale holes within MXene, transforming them into holey MXene (H‐MXene) nanosheets. These porous structures shorten ion transport distances and increase ion transport pathways, thereby significantly enhancing the electrochemical storage capacity of MXenes. The resulting H‐MXene micro‐supercapacitors (MSCs) demonstrate exceptional performance, achieving an aerial capacitance 2.5 times that of unmodified MXene electrodes, along with excellent cycling stability, retaining 91.7% of their capacitance after 10 000 cycles. Additionally, a flexible integrated system combining energy storage and sensing functionalities is developed, showcasing its scalability in self‐powered sensing applications. The incorporation of self‐healing polyurethane (PU) enables the device to retain 90% of its storage capacity after undergoing self‐healing. This study presents a novel approach for developing high‐performance MXene‐based energy storage devices and provides valuable insights into efficient ion transport and storage in 2D materials.

Cheng, Yongfa [Department of Materials Science and↗