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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Oxygen Effects and Selective Oxidation of Group IV Alloying Additions in Group V-Based Refractory Multi-principal Element Alloys

Refractory multi-principal element alloys (RMPEAs) hold significant potential for advancing ultra-high-temperature technologies due to their remarkable strength retention under these conditions. However, the beneficial effects of alloying on microstructural evolution and mechanical properties are often obscured by the presence of interstitial alloying elements. The intricate interactions between substitutional alloying elements of Groups IV, V, and VI and interstitial content, whether intentional or incidental, remain poorly understood. In this study, we investigate the impact of dissolved oxygen on the microstructural evolution and stability of RMPEAs primarily composed of Group V elements, Nb and V, along with Group IV elements Ti, Zr, and Hf. We show that the strong affinity of oxygen for Group IV elements Zr and Hf leads to the internal precipitation of oxides during heat treatment, which competes with the homogenization of the as-cast dendritic microstructure. Here, we demonstrate that careful control and design of oxygen content and Group IV alloying additions are essential to minimize micro-segregation and prevent the detrimental precipitation of internal oxides. To address these challenges, we propose employing non-equilibrium solidification calculations to predict and optimize as-cast solidification structures, thereby reducing the reliance on homogenization processes.

Alloy design↗
DOE OSTI2026

Long-range magnetic order and relaxor ferroelectricity in a hexagonal high-entropy ferrite

Multiferroics that combine ferroelectricity and magnetic order are attractive for electronic and spintronic technologies, yet chemical disorder that promotes relaxor ferroelectricity usually suppresses long-range magnetic order. Here, we report entropy-stabilized relaxor multiferroicity in epitaxial hexagonal (Tb0.2Dy0.2Ho0.2Lu0.2Yb0.2)FeO3 thin films. Structural, magnetic, dielectric, and synchrotron spectroscopic measurements show the coexistence of relaxor ferroelectricity and long-range ferromagnetic order. We find that improper ferroelectricity remains robust against A-site configurational disorder, while the Fe sublattice preserves magnetic exchange. This separation of the microscopic origins of the polar and magnetic responses enables chemically disordered multiferroicity. Our results establish entropy engineering in hexagonal ferrites as a route toward multifunctional oxide thin films and provide a general design strategy for high-entropy multiferroics.

Miertschin, Duncan [Baylor University]↗
DOE OSTI2026

From high-entropy ceramics to compositionally complex ceramics and beyond

Over the past decade, the field of high-entropy ceramics (HECs) has expanded rapidly to encompass a broad range of oxides, borides, silicides, and other ceramic solid solutions. In 2020, we proposed extending HECs to compositionally complex ceramics (CCCs), where non-equimolar compositions and the presence of long- or short-range order, although reducing configurational entropy, create new opportunities to tailor and enhance properties, often surpassing those of higher-entropy counterparts. Along these lines, several fundamental scientific questions arise. Is the entropy in HECs truly high? Is maximizing entropy always desirable? In this perspective article, I revisit key concepts and terminologies and highlight emerging directions, including dual-phase CCCs, ultrahigh-entropy phases, and novel processing routes such as ultrafast reactive sintering. I propose that exploring compositional complexity across vast non-equimolar spaces, together with exploiting correlated disorder (coupled chemical and structural short-range order), represents a transformative strategy for designing ceramics with superior performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance Prediction of High‐Entropy Perovskites La 0.8 Sr 0.2 Mn x Co y Fe z O 3 with Automated High‐Throughput Characterization of Combinatorial Libraries and Machine Learning

Perovskite oxides form a large family of materials with applications across various fields, owing to their structural and chemical flexibility. Efficient exploration of this extensive compositional space is now achievable through automated high-throughput experimentation combined with machine learning. In this study, we investigate the composition–structure–performance relationships of high-entropy La 0.8 Sr 0.2 Mn x Co y Fe z O 3±𝞭 perovskite oxides (0 < x, y, z <1; x+y+z≈1) for application as oxygen electrodes in Solid Oxide Cells. Following the deposition of a continuous compositional map using thin-film combinatorial pulsed laser deposition, compositional, structural, and performance properties are characterized using six different techniques with mapping capabilities. Random forests effectively model electrochemical performance, consistently identifying Fe-rich oxides as optimal compounds with the lowest area-specific resistance values for oxygen electrodes at 700 °C. Additionally, the models identify a statistical correlation between oxygen sublattice distortion—derived from spectral analysis of Raman-active modes—and enhanced performance.

high entropy oxides↗
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↗
DOE OSTI2024

Next-Generation Materials Design: Quantum Mechanics and Data-Driven Modeling

The future of materials design is rapidly advancing through the combination of quantum mechanics and data-driven modeling. These approaches integrate quantum principles with advanced data analysis, enabling precise insights into material behavior. This talk will highlight recent progress in using these methods for computational design, particularly in high-entropy alloy catalysts, emphasizing the role of hierarchical machine-learning architectures for accurate predictions. Additionally, I will discuss our work on developing machine learning interatomic potentials (MLPs) for single-element metals, metal oxides, and alloys under extreme conditions, focusing on melting behavior and phase properties at high temperatures and pressures. We have also refined our MLP models to capture dynamic surface interactions, such as CO2 and CO adsorption on MgO, using both static and molecular dynamics simulations. These models maintain high accuracy while significantly reducing computational costs compared to first-principles calculations. By enabling efficient and accurate simulations, this work supports broader community adoption, optimizes datasets for materials discovery, and extends the accessible time, size, and environmental conditions beyond the limits of experiments and traditional simulations.

machine learning↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
DOE OSTI2025

Facile One-Pot Block Copolymer-Mediated Solvothermal Approach for Synthesis of High-Entropy Alloy with Enhanced OER Activity

Herein, we introduce a straightforward synthesis approach for highly active dendritic multimetallic high-entropy alloy (DMHEA@PtIrPdAgRu) nanoparticles with sufficient entropic mixing, featuring uniform distribution of five noble group metals (Pt, Ir, Pd, Ag, and Ru) via a block copolymer-mediated one-pot solvothermal reduction method for oxygen evolution reaction (OER). In this synthesis, N,N -dimethylformamide (DMF) is used as a reductant as well as solvent and core–shell-corona-type (poly(styrene)- block -poly(vinylpyridine)- block -poly(ethylene oxide)) (PS-PVP-PEO) block copolymer as a structure directing agent. The cooperative effect between the copolymer architecture and the reducing environment of DMF promoted a confined nucleation mechanism for forming a single-phase dendritic structure HEA with high compositional uniformity, thereby mitigating phase segregation, a common challenge in the synthesis of multimetallic nanoparticles. This prepared DMHEA@PtIrPdAgRu catalyst exhibits a low overpotential of 490 mV to attain a high current density of 100 mA cm –2 with a Tafel slope of 442 mV dec –1 for oxygen evolution. The superior OER performance is attributed to the synergistic cooperation among its active and coordinated metal centers as well as the incorporation of corrosion-resistant metal like platinum.

block copolymer↗
DOE OSTI2025

Surface Nanostructure Control and Thermodynamic Stability Analysis of Femtosecond Laser-Ablated CuCoMn 1.75 NiFe 0.25 Nanoparticles

Surface nanostructure control is the key to functionalizing nanomaterials. This paper presents a characterization with thermodynamic stability analysis of CuCoMn 1.75 NiFe 0.25 high-entropy alloy (HEA) nanoparticles synthesized by femtosecond laser ablation in ethanol and liquid nitrogen (LN2). Using multimodal electron microscopy and spectroscopy, we examine phase, particle size, defect structure, chemical distribution, and surface composition and relate them to HEA stability. Elemental distributions are uniform in both media, but LN2 produces smaller particles with a narrower size distribution and mainly single- or few-domain interiors, whereas ethanol yields larger particles built from 2–4 nm crystallites with domain aggregation. Edge defects appear in both but energy-dispersive X-ray spectroscopy (EDS) is broadly uniform with local fluctuations in ethanol. X-ray photoelectron spectroscopy (XPS), supported by an attenuation model, indicates an ∼1 nm oxide overlayer that suppresses Mn 2p intensity; correcting for it returns Mn toward the bulk value. UV–NIR and photoluminescent spectra independently support a thin oxide shell. Composition-based thermodynamic descriptors place LN2 closer to bulk mixing parameters, while ethanol raises ΔH_mix and lowers Ω. Cooling simulations are consistent (LN2 ∼ 0.1 μs quench, ethanol ∼1 μs). In conclusion, these results connect solvent-controlled kinetics and thermodynamics to crystalline state and surface chemistry, informing surface control of HEA nanoparticles.

Femtosecond Laser Ablation↗
DOE OSTI2024

Halting Oxygen Evolution to Achieve Long Cycle Life in Sodium Layered Cathodes

Oxygen redox chemistries at high voltage have materialized as a revolutionary paradigm for cathodes with high-energy density; however, they are plagued by the challenges of labile oxygen loss and rapid degradations upon cycling, even after concerted endeavors from the research community. Here we propose a multi-concentration stratagem propelled by entropy reinforcement to enhance the electronic structure disorder (ESD) at high desodiation states for impeding undesired oxygen mobility and ensuring controlled oxygen activity, elucidated by density functional theory calculations. The increased disorder strengthens the reversible electrochemistry of lattice oxygen redox, leading to effectively suppressed P−O structural evolution and highly stable localized TMO 6 octahedral environments, as demonstrated by soft/hard X-ray absorption spectroscopy. Furthermore, through a comparative analysis of sodium-layered cathodes with different configuration entropy, we reveal that a high-entropy state induced by cationic disordering has the capacity to perturb cationic redox boundaries, significantly restraining the formation of detrimental O′3 phases. As a consequence, the high-voltage cycling stability has been greatly upgraded, up to 4.4 V versus Na + /Na, with an impressive 90.1 % capacity retention at 1 C over 100 cycles and 76.1 % capacity retention at 2 C over 300 cycles. In conclusion, the resilient oxygen redox, enabled through the control of ESD, broadens the horizons for entropy engineering and lays the foundation for advancements in high-energy, long-cycling, and safe batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

The Path towards Plasma Facing Components: A Review of State-of-the-art in W-Based Refractory High-Entropy Alloys

Developing advanced materials for plasma-facing components (PFCs) in fusion reactors is a crucial aspect for achieving sustained energy production. Tungsten (W) - based refractory high-entropy alloys (RHEAs) have emerged as promising candidates due to their superior radiation tolerance and high-temperature strength. This review paper will focus on recent advancements in W-based RHEA research, particularly emphasizing the key role of modelling using machine learning (ML) in the stage of discovery by predicting properties for each composition and expediting the identification of optimal RHEA compositions with desired properties. Additionally, the application of additive manufacturing (AM) techniques for fabricating W-based RHEAs is explored, highlighting their advantages for rapid prototyping and multi-compositional sample production in a high throughput manner. The review critically evaluates the current understanding of mechanical properties relevant to PFC applications, including high-temperature strength and ductility. Furthermore, the radiation tolerance of W-based RHEAs under irradiated conditions is discussed. Finally, the validity of current AM-manufactured W-based RHEAs as PFC materials is assessed, and key challenges and opportunities for future research are identified. This review aims to provide a comprehensive overview of W-based RHEAs for fusion applications and their potential to guide the development and validation of advanced refractory high entropy alloys.

Hatler, Caleb [University of Wisconsin-Madison]↗
DOE OSTI2024

Reactive flash sintering and characterization of bulk high entropy nitrides

Over the past decade, numerous high-entropy ceramics have been synthesized, often displaying attractive properties. However, the study on facile preparation of bulk high entropy nitrides (HEN) are limited, despite its broad potential applications. This research demonstrates for the first time rapid fabrication (within ∼6 min) of bulk high-entropy nitrides, especially (Al 0.17 Nb 0.17 Ta 0.17 Ti 0.32 Zr 0.17 )N, from binary nitride powder mixtures using a highly efficient reactive flash sintering (RFS) technique. X-ray diffraction (XRD) shows the HENs from RFS are near single-phase solid solutions with a rock salt crystal structure, while in situ synchrotron study carried out during RFS captured in real time the formation of HEN, which was preserved upon cooling, suggesting thermodynamic stability of the HEN phase, even up to extreme pressure (∼35.6 GPa). Microscopic analyses using SEM, STEM, and EDS reveal decent uniformity for HEN with no obvious segregation of elements, even to submicron scale. Some properties of the obtained bulk HENs are consistent with expectations. For example, their hardness and bulk modulus are close to estimates based on rule-of-mixture (ROM) values from the constituent binary nitrides. Meanwhile, some other measured properties seem to show surprises. For example, the fracture toughness for the HENs (e.g., 7.81 ± 1.40 MPa•m 1/2 or higher) turns out to be more than double of the expected ROM estimates. The significantly improved fracture toughness is attributed to the observed nano-layered structure of the HENs, despite the HEN’s cubic crystal structure and high hardness. In addition, the oxidation resistance shows improvement up till ∼800°C, possibly due to Ta doping that suppress oxygen vacancy formation in the oxide shell, while the 5-metal HEN of (Al 0.17 Nb 0.17 Ta 0.17 Ti 0.32 Zr 0.17 )N displays superconductivity (T c of ∼5–7 K from magnetism and resistivity measurements, slightly lower than ROM estimate), despite insulating property of starting AlN. Furthermore, future study combining experimental investigation using larger samples to confirm the observed increase in fracture toughness and oxidation resistance, theoretical modeling at different length scale, and more detailed structural/chemical characterization, especially at the atomic scale, are all needed to fully understand the inter-relationships between composition, processing, structure, and novel properties for these HENs and the development of related new materials for different applications.

Flash sintering↗
DOE OSTI2026

Compositional Phase Control in High-Entropy Alloy Electrocatalysts

High-entropy alloys (HEAs) provide uniquely tunable structural and electronic properties that enable robust electrocatalysis. While compositional manipulation of HEAs is well-known, systematically controlling the crystalline phase and morphology remains a challenge that could provide new avenues for controlling reactive sites and physical properties. Here, we show the preferential stabilization of mixed fcc/bcc to fcc phases by controlling the Au content in quinary AuPdFeCoNi HEA nanoparticles. This systematic structural and compositional control, when investigated with an ensemble of electronic, X-ray synchrotron, and surface techniques, allows us to identify the critical short- (few-Å) and medium- (6–10 Å) range structural motifs that deliver exceptional hydrogen evolution reaction (HER) catalysis. Specifically, these HEAs exhibit both outstanding durability (240 h) and high mass activity (50 A/mg PGM ) normalized to noble metal content, outperforming commercial Pt/C (3.18 A/mg PGM ). This structural control over HEA morphology, and its direct association with changes in specific metallic oxidation states and pair–pair atomic structural features, provides new means and strategies for finely designing robust and sustainable electrocatalysts with a majority nonprecious metal composition.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Modulating coordinate site occupancy in high-entropy spinel electrocatalysts

High entropy spinel oxides provide a versatile platform for electrocatalysis because multiple metal cations can be incorporated into a single crystalline lattice, enabling tunable electronic structures. However, controlling how these cations distribute between tetrahedral and octahedral coordination sites remains a major challenge, limiting rational catalyst design. Here, we modulate cation coordination site occupancy between tetrahedral and octahedral sites in a Co–Fe–Cr–Mn–Ni framework by introducing a sixth cation (Zn, Ga, Mg, or Al) with distinct site preference energies. Using density functional theory, synchrotron X-ray absorption spectroscopy, and magnetic circular dichroism, we demonstrate that Zn preferentially occupies tetrahedral sites, driving increased octahedral occupancy of cobalt. This redistribution increases the population of octahedrally coordinated cobalt in mixed oxidation states, enhances electrical conductivity, and improves oxygen evolution reaction activity. Our findings establish coordination site occupancy as a critical design parameter, providing a strategic pathway for tailoring multicomponent spinel electrocatalysts with optimized performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Non-equilibrium reducing flame aerosol process to create supported high-entropy alloy nanoparticles

High-entropy alloy (HEA) nanomaterials provide opportunities and property combinations for energy and electronic applications, but their practical synthesis faces challenges of elemental immiscibility, metal reducibility, and particle aggregation during their synthesis. Herein, we report a broadly applicable non-equilibrium, scalable, and in-situ reducing flame aerosol process for synthesis of supported HEA nanoparticles. This versatile process can directly load a high concentration of 2 ~ 4 nm HEA nanoparticles on various 1- to 3-dimensional supports. Notably, simultaneous formation of HEA nanoparticles and a mesoporous silica support was successfully realized in a single step. Exploration of this process demonstrates the role of kinetics and entropy on decreasing alloy particle size and altering the reducibility of elements. We propose an entropy-induced reduction mechanism to incorporate oxidizable elements into HEAs, which extends the compositional space of HEA nanoparticles. As a representative catalytic application, we present a RuPdOsIrPt/graphene electrocatalyst with high activity and stability for hydrogen oxidation reaction. Our findings open horizons for high-performance HEA design and applications in diverse fields such as catalysis, electrochemistry, and sensing.

organic↗
DOE OSTI2025

CALPHAD-based Bayesian optimization to accelerate alloy discovery for high-temperature applications

Two crucial properties influencing the performance of high-temperature alloys are coefficient of thermal expansion (CTE) and phase constitution. It is desirable to have alloys with low CTE, which reduces CTE mismatch with the surface oxide and the likelihood of oxide spallation. Reducing the amount of brittle intermetallic phases such as Sigma (σ) enhances alloy ductility and processability. Here, we propose a multi-objective Bayesian Optimization (BO) model to simultaneously minimize CTE (at an operational temperature of 1150 °C) and T σ (temperature when the Sigma phase completely dissolves in the metal matrix), properties which are obtained from high-throughput CALculation of PHAse Diagrams (CALPHAD). The model successfully identifies several alloys with CTE ≤ 2 × 10 –5 /K and T σ ≤ 500 °C by exploring just 7% of the nickel–chromium–cobalt–aluminum–iron (Ni–Cr–Co–Al–Fe) composition space. Such multi-objective alloy design frameworks can be used to inform additive manufacturing experiments and accelerate alloy discovery for high-temperature energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational Design of Cost-Effective High-Entropy Thermal/Environmental Barrier Coatings

Developing cost-effective thermal/environmental barrier coatings (TEBC) requires balance among various properties including low thermal conductivity, matching coefficient of thermal expansion (CTE), high thermal stability, high fracture toughness, and high recession resistance while being affordable. Low oxygen diffusivity is desirable as it can slow down oxygen transport to reach the underlying bond coating and hence delay oxidation of the bond coating. This project aims to design low-cost high-performance TEBC based on high entropy rare earth disilicates to protect SiC-based ceramic matrix composites from chemical and thermal attack for better performance of components in the hot section of gas turbine engines. To accelerate the TEBC design, we utilize first-principles density functional theory to predict key properties including phase stability, CTE, lattice thermal conductivity, temperature-dependent elastic constants, and oxygen diffusivity. Alloying elements including Yb, Y, Er, Eu, Gd, Lu, La, and Ce are considered, and modeling prediction are compared with available experimental results.

coefficient of thermal expansion↗
DOE OSTI2025

Ab Initio Design of High-Entropy Thermal/ Environmental Barrier Coatings

Next generation thermal/environmental barrier coatings (TEBC) require carefully balancing various properties including phase stability, thermal conductivity, coefficient of thermal expansion (CTE), mechanical properties, and resistance against hot corrosion and water vapor recession. This work mainly focuses on rapid design of cost-effective high entropy rare-earth disilicates and aluminum garnets to protect SiC-based ceramic matrix composites and nickel-based superalloys in the hot section of gas turbine engines using density functional theory methods. Our calculations identify several low-cost high entropy TEBC exhibiting ultralow thermal conductivity at 1500 K and desirable CTE while maintaining good mechanical properties, including Er1/2Y3/4Yb3/4Si2O7, Gd1/4Er1/4Y3/4Yb3/4Si2O7, Eu1/4Er1/4Y3/4Yb3/4Si2O7, and (Y1/4Gd1/4Er1/4Yb1/4)3Al5O12. This work also aims to gain fundamental understanding of oxygen diffusion in model disilicates. Minimizing oxidizer (such as water vapor and oxygen) permeability through the EBC layer can significantly decrease the growth rate of thermally grown oxide and extend the service life of the coating system. Oxygen diffusion mechanisms including formation energy of defects under varying oxygen conditions and defect migration energy barriers will be presented.

coefficient of thermal expansion↗