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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Segmented wall-less hall thruster

Disclosed is a miniaturized plasma propulsion device with minimized surface area of the thruster walls exposed to the plasma and, as a result, reduced plasma-surface interactions including a set of segmented electrodes to facilitate the following improvements compared to relevant existing technologies: 1) control of the plasma flow including focusing of the plasma plume 2) increase of the thrust 2) reduction of inefficiencies associated with the electron cross field current, and 3) mitigation of low frequency oscillations. The electrodes affect all these actions when a DC or modulated voltage is applied to one or all of them with the same or different amplitudes, with the same or different frequencies or phases which are all optimized to realize the best performance through changes in the acceleration and/or ionization regions. In addition, the applied voltage to the main electrodes may also be modulated.

Simmonds, Jacob↗
DOE OSTI2024

Kinetic Control over Disproportionation Stabilizes Wurster’s Blue Catholyte for Nonaqueous Redox Flow Batteries

Redoxmers are organic molecules that serve as charge carriers in redox flow batteries. While these materials are affordable and easy to source, insufficient stability of their charged states (radical ions) remains a challenge. A common reaction of these species is their disproportionation. Furthermore, this reversible reaction yields unstable multiply charged states, shifting the overall charge transfer equilibrium toward the decomposition products. Here we show how kinetic controls can be engineered into a redoxmer molecule to suppress these unwanted charge transfer reactions. This approach is used to transform Wurster's blue, which is historically the first example of a stable radical ion in organic chemistry, into an exceptionally durable redoxmer molecule that persists over thousands of electrochemical cycles.

Cations↗
DOE OSTI2025

Tracking Local pH Dynamics during Water Electrolysis via In-Line Continuous Flow Raman Spectroscopy

The performance of electrochemical devices, which play a critical role in decarbonization efforts, is often governed by proton-coupled electron transfer reactions at the electrode–electrolyte interface. These reactions are highly sensitive to the complex and dynamic microenvironment present at the electrode surface. However, characterizing this environment─particularly monitoring interfacial pH and its evolution under reaction conditions─remains challenging, necessitating the development of advanced analytical tools. Here, in this study, we introduce in-line continuous flow Raman spectroscopy (CFRS) as a spectroelectrochemical platform for quantifying interfacial pH swings generated during water-splitting. By monitoring phosphate ion speciation and controlling the hydrodynamics with a flow cell, we measure pH swings as a function of current density, flow rate, and distance from the electrode. Comparison with theoretical models reveals the impact of bulk pH, boundary layer thickness, and bubble dynamics at high current densities. Collectively, these findings establish CFRS as a platform for quantitatively investigating pH dynamics, offering critical insights for advancing electrochemical energy conversion technologies.

Marquez, Raul A. [Univ. of Texas, Austin, TX (Unit↗
DOE OSTI2024

Novel plasma actuator for mitigation of dynamic stall

A novel plasma actuator, the Linear Counter-flow using a Point Embedded Electrode (LCPEE), is developed for the prevention of dynamic stall for a sinusoidal pitching movement between α = 4° and α = 18°. The LCPEE is implemented on a NACA0012 airfoil and tested at a Reynolds Number of Re c = 2 × 105 and reduced frequency of k = π/16. Prior investigations using a standard linear actuator showed that the exposed electrode introduced perturbations passively which delayed dynamic stall when the actuator was off. For the LCPEE actuator, when turned off, there is least passive delay. When the LCPEE is turned on at St f = 50, the dynamic stall is prevented for the sinusoidal pitching motion of the airfoil. The LCPEE actuator is also tested for the same sinusoidal motion between α = 6° and α = 20°. Four cases are considered for the higher α range of motion: actuator off, actuator on at St f = 50 with a sinusoidal input waveform, actuator on at St f = 50 with a triangular input waveform, and actuator on at Stf = 100 with a sinusoidal input waveform. Specifically for the last case, experiment shows no flow reversal demonstrating the efficacy of LCPEE in controlling the dynamic stall. The effects of LCPEE on the flow energy distribution have also been studied by using proper orthogonal decomposition (POD) method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Enabling "Fuel" Switching through On-Demand Wind Control

This work demonstrates that classical shear-flow stability theory can be successfully applied to modify wind turbine wakes and also explains the success of several emerging, empirically-arrived control methods (i.e., dynamic induction and helix control). Linear stability theory predictions are extended to include the effects of non-axisymmetric inflow profiles, such as wind shear, which is shown to not strongly affect the primary forcing frequency. The predictions, as well as idealized large-eddy simulations using actuator-line representation of the turbine blades, agree that the n = 0 and ±1 modes have faster initial growth rates than higher-order modes, suggesting the lower-order modes are more appropriate for wake control. Exciting the lower-order modes with periodic pitching of the blades produces higher entrainment into the wake and consequently faster wake recovery.

17 WIND ENERGY↗
DOE OSTI2025

Unraveling the Determinant Mechanisms in Flow-Mediated Crystal Growth and Phase Behaviors

To uncover the critical mechanisms responsible for mesoscopic level development during flow-mediated crystal growth, we develop a semi-two-way hydrodynamic coupled structural phase-field crystal formalism (HXPFC-s2). The new formalism, inspired by previous attempts at coupling hydrodynamic and phase-field crystal (PFC) equations, allows for studying mesoscopic flow-mediated crystallization at diffusive timescales pertinent to industrial applications. Unlike previous efforts, the devised coupling to the structural PFC (XPFC) equations allows generalization to more complex crystal structures through explicit parameterization of the direct correlation function (DCF). Utilizing the HXPFC-s2 formalism, we seek to uncover the determinant physical mechanisms in crystallization under simple shear flows by comparing temperature-driven crystallization to flow-mediated crystallization under varying flow-strengths. Parallels and deviations of under-cooling and flow-strength effects on crystal growth are drawn using the crystal cluster-size and system ordering time evolutions. In doing so, we identify scaling behaviors with a Peclet-like number, Pe∼, a critical Peclet-like number, Pe∼*, and flow-field-crystal plane-dependent interactions. Our findings may be relevant for controlling crystal growth and phase behaviors in flow applications.

Willis, L. Connor (ORCID:0009000961321848)↗
DOE OSTI2024

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias: Preprint

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between the energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid generation-demand imbalances is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS systems provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 seconds from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS with a high-inertia motor may be able operate over a broader range of frequency variations whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗
DOE OSTI2025

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a high-inertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗
DOE OSTI2024

Optimizing Grid Regulation with Gravity Energy Storage Systems: A Comparative Analysis with Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a highinertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

ENERGY STORAGE,POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗
DOE OSTI2026

HDG-1 Experiment Irradiation Monitoring Data Qualification Final Report

SUMMARY The U.S. Department of Energy (DOE) Advanced Reactor Technologies (ART) Graphite Research and Development (GRD) Program is conducting a series of six experiments to quantify the effects of irradiation on nuclear-grade graphite. This report documents the qualification of irradiation monitoring data for the fifth experiment, High Dose Graphite-1 (HDG-1). Qualified monitoring data are required by the ART program to support the design and licensing of the first high-temperature reactor (HTR) nuclear plant. Data are classified as Qualified if they meet the usage requirements described in the experiment planning and quality assurance (QA) documents, Failed if they do not meet those requirements and provide no usable information, or Trend if they do not fully meet all requirements but still provide useful information subject to an assessment of how any deficiencies may affect a particular use of the data. HDG-1 irradiation began with Advanced Test Reactor (ATR) Cycle 168B on August 24, 2020, and concluded after Cycle 173C on January 27, 2025. The HDG-1 capsule was removed from the reactor core twice—during core internal change (CIC) Cycle 170A and powered axial locator mechanism (PALM) Cycle 172A—to prevent overheating of the graphite specimens during high-power PALM cycles. The capsule was therefore irradiated during a total of seven normal ATR cycles: 168B, 169A, 171A, 171B, 173A, 173B, and 173C. Irradiation monitoring data evaluated in this report include thermocouple (TC) temperature, gas flow rate, gas moisture, gas pressure, specimen load, and graphite stack displacement. Temperature. A total of 14,508,065 TC temperature records were captured. Of these, 13,901,785 (95.8%) are Qualified and 606,280 (4.2%) are Failed. The principal source of failed temperature data was the instrument failure of TC-9 (Zone 2) on June 24, 2024, and TC-10 (Zone 1) on July 5, 2024, near the end of Cycle 173A, which resulted in 595,554 Failed readings. An additional 379 missing values and 10,347 slightly negative values from TC-13 during ATR outages are also Failed. Neither TC-9 nor TC-10 was used as a temperature-control TC, and their failures did not compromise capsule condition monitoring. Correlation analysis of all 13 TCs found no evidence of virtual junction formation. Control chart analysis revealed clear downward drift of approximately 80°C for TC-6 (Zone 3) relative to other stable TCs, and possible downward drift of approximately 60°C for TC-13 relative to the Zone 5 control TC (TC-1), though TC-13 remained consistent with the Zone 2 control TC (TC-12). Gas flow. A total of 20,088,090 gas flow rate records were captured. Of these, 19,941,463 (99.3%) are Qualified and 146,627 (0.7%) are Failed due to missing values. All argon, helium, and total gas flow data were within expected ranges throughout the irradiation. Gas moisture. A total of 1,116,005 outlet gas moisture values were captured. Of these, 1,101,421 (98.7%) are Qualified and 14,584 (1.3%) are Failed, comprising 14,556 out-of-range values and 28 missing values. The out-of-range moisture values exceeded 22,000 ppmv for approximately 1 week at the beginning of Cycle 173A, when accumulated moisture evaporated after the capsule was retrieved from water storage during PALM Cycle 172A and reinserted into the east flux trap. Moisture levels returned to below 25 ppmv for the remaining three cycles, and the transient high-moisture event did not affect the integrity of specimen irradiation. Gas pressure. A total of 7,812,035 gas pressure values were captured. Of these, 6,642,048 (85.0%) are Qualified and 1,169,987 (15.0%) outlet pressure values are Failed, comprising 718,537 zero outlet pressure values due to sensor failure from Cycle 168B through Cycle 171B, 54,550 missing values, and 396,900 too-low outlet pressure values, ranging from 1.1 to 1.6 psia after sensor replacement during Cycle 173A. Load. A total of 6,696,030 load values were captured. Of these, 6,694,580 (99.98%) are Qualified and 1,450 (0.02%) are Failed due to missing values. Applied loads to the six specimen stacks were stable throughout the irradiation. Stack displacement. A total of 6,696,030 displacement values were captured. Of these, 5,713,297 (85.32%) are Qualified and 3,781 (0.06%) are Failed due to missing values. Stack displacement increased consistently throughout the irradiation, reaching approximately 3.08 in. for Channels 5 and 6 by the end of irradiation. 978,952 (14.62%) substantially elevated displacements observed for Channel 6 beginning in Cycle 171A and for Channel 5 beginning in Cycle 173A are assigned Trend status. Raising pressure. A total of 1,115,999 raising pressure values were captured. Of these, 1,115,430 (99.95%) are Qualified and 569 (0.05%) are Failed due to missing values. Ram pressure. A total of 6,696,030 ram pressure values were captured. Of these, 6,692,249 (99.95%) are Qualified and 3,484 (0.05%) are Failed due to missing values. Stack raising was perf

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

An integrated experimental–modeling approach to identify key processes for carbon mineralization in fractured mafic and ultramafic rocks

Abstract Controlling atmospheric warming requires immediate reduction of carbon dioxide (CO2) emissions, as well as the active removal and sequestration of CO2 from current point sources. One promising proposed strategy to reduce atmospheric CO2 levels is geologic carbon sequestration (GCS), where CO2 is injected into the subsurface and reacts with the formation to precipitate carbonate minerals. Rapid mineralization has recently been reported for field tests in mafic and ultramafic rocks. However, unlike saline aquifers and depleted oil and gas reservoirs historically considered for GCS, these formations can have extremely low porosities and permeabilities, limiting storage volumes and reactive mineral surfaces to the preexisting fracture network. As a result, coupling between geochemical interactions and the fracture network evolution is a critical component of long-term, sustainable carbon storage. In this paper, we summarize recent advances in integrating experimental and modeling approaches to determine the first-order processes for carbon mineralization in a fractured mafic/ultramafic rock system. We observe the critical role of fracture aperture, flow, and surface characteristics in controlling the quantity, identity, and morphology of secondary precipitates and present where the influence of these factors can be reflected in newly developed thermo-hydro-mechanical–chemical models. Our findings provide a roadmap for future work on carbon mineralization, as we present the most important system components and key challenges that we are overcoming to enable GCS in mafic and ultramafic rocks.

58 GEOSCIENCES↗
DOE OSTI2024

Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields

Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗
DOE OSTI2025

Cu‐Catalyzed Aerobic Oxidative C─C Cleavage in Lignin‐Derived Oligomers and Biological Funneling of the Monomeric Products

Existing methods for lignin deconstruction to aromatic monomers primarily cleave carbon–oxygen bonds within the polymer, resulting in sub-optimal monomer yields and formation of oligomers that retain intact carbon–carbon bonds. Here, we demonstrate that copper-catalyzed aerobic oxidation under aqueous alkaline conditions promotes oxidative cleavage of carbon–carbon bonds in lignin oligomers derived from reductive catalytic fractionation (RCF) of pine and poplar biomass. Fundamental insights are gained from reactions of model compounds that resemble subunits present in RCF oligomers. Optimal results are achieved in a flow reactor that provides precise control over O2 delivery, temperature, and reaction residence time. The Cu-catalyzed aerobic oxidation conditions access aromatic monomers in 19 and 34 wt% monomer yields, respectively, from pine- and poplar-derived RCF oligomers. Overall, the sequence consisting of biomass RCF into monomers and oligomers followed by oxidative deconstruction of the RCF oligomers generates substantially higher yields of aromatic monomers from lignin. Engineered strains of Pseudomonas putida support biological funneling of the oligomer-derived oxygenated aromatic compounds into cis,cis-muconic acid from pine or 2-pyrone-4,6-dicarboxylic acid from poplar.

09 BIOMASS FUELS↗
DOE OSTI2025

Effects of Strain and Strain Rate on Dynamic Grain Growth and Subgrain Evolution During Plastic Deformation of an Interstitial-Free Steel at 850 ° C

Here, the effects of strain and strain rate on dynamic grain growth (DGG) and subgrain evolution are reported for an interstitial-free steel deformed at 850 ° C. Microstructures produced during tension tests at true-strain rates of 10 -4 and to 10 -3 s -1 true strains ranging from 0.02 to 0.2 were preserved following deformation. These were characterized using electron backscatter diffraction (EBSD), including the application of spherical harmonic transform indexing to produce high-angular-resolution EBSD (HR-EBSD) data. HR-EBSD data resolved the small misorientation angles of subgrain boundaries while imaging much larger data fields than possible with previously available techniques. The resulting data confirmed that steady-state flow stress is inversely proportional to the average subgrain size and that subgrain boundary misorientation angle increases with strain. The following new observations are reported. The rate of DGG increased with respect to time but decreased with respect to strain as strain rate increased. This behavior is rationalized through a simple model using separate rate parameters for the effects of time and strain. Subgrain size was not constant during steady-state deformation, but decreased slowly with increasing strain. Subgrain size distributions and subgrain boundary misorientation angle distributions were measured, and both remained approximately log-normal during steady-state deformation. Subgrain evolution demonstrated no dependence on parent grain size, crystallographic orientation, or Taylor factor. These new data suggest that steady-state flow stress is more likely controlled by the dislocation density internal to subgrains than by the spacing between subgrain boundaries.

dynamic grain growth↗
DOE OSTI2024

Temperature and Composition Dependence Modeling of Viscosity and Electrical Conductivity of Low-Activity Waste Glass Melts

The development of models that accurately relate the properties of a glass melt to its temperature and composition is important for glass formulation, melter control, and modeling the melt flow, refractory corrosion, and production rate. Using a database consisting of more than 4,000 data points measured between 900 °C and 1250 °C for over 600 unique low-activity waste glass compositions, we developed models for the melt viscosity and electrical conductivity. Models based on the Gaussian process regression approach outperformed models based on the Vogel–Fulcher–Tammann equation according to four standard metrics and yielded reliable prediction intervals. The models found primarily linear effects between properties and individual components, except for the effect of the Na 2 O mass fraction on the electrical conductivity. The effects were found to be consistent with current theories on physical processes involved with those properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bifunctional Electrocatalysts with High-Entropy Alloys: Bridging Hydrogen Evolution and Oxygen Reduction

High-entropy alloys (HEAs) have emerged as a promising class of bifunctional electrocatalysts capable of simultaneously driving the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) with high activity and durability. Their near-equiatomic multicomponent compositions give rise to unique physicochemical characteristics, including lattice distortion, sluggish diffusion, high-entropy stabilization, and pronounced electronic heterogeneity, that collectively generate diverse and synergistic active sites inaccessible in conventional alloys. This review summarizes recent progress in HEA-based bifunctional electrocatalysis, with a focus on the fundamental mechanisms governing HER and ORR activity, stability, and selectivity. We discuss advances in synthesis strategies, ranging from confined growth and step-alloying to scalable continuous-flow methods, that enable precise control over composition, size, and surface structure. Complementary computational and data-driven approaches, including density functional theory, machine-learning-assisted screening, and descriptor development, are highlighted as essential tools for navigating the vast HEA design space and establishing structure−property relationships. Particular attention is paid to adsorption-energy distributions, multisite cooperativity, and environmental effects under realistic electrochemical conditions. Finally, we outline current challenges and future opportunities for integrating mechanistic understanding with AI-guided, closed-loop design frameworks to accelerate the discovery of next-generation HEA bifunctional electrocatalysts for sustainable energy conversion.

Alloys↗