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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
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 OSTI2024

Advanced thermal/environmental barrier coatings of high-entropy rare earth disilicates tuned by strong anharmonicity of Eu 2 Si 2 O 7

Advancing thermal/environmental barrier coating (TEBC) materials with integrated thermal-mechanical functions is paramount for safeguarding SiC-based ceramic matrix composites (CMCs) in high-efficiency gas turbines. Herein, we employ a synergistic approach, combining density functional theory (DFT) methods and combinatorial chemistry techniques, to design high-performance and low-cost RE 2 Si 2 O 7 (RE = rare earth elements) TEBC materials tailored for enhanced compatibility with SiC-based CMCs. Expanding on phase stability of alloying pure RE 2 Si 2 O 7 , the investigation extends to the mechanical and thermal properties of solid solution systems, including Er 1/2 Y 3/4 Yb 3/4 Si 2 O 7 , Gd 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 , and Eu 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 . The solid solution systems exhibit a major reduction in lattice thermal conductivity relative to their pure counterparts, achieving ultralow values of 0.25 to 0.39 W m −1 K −1 at 1500 K. Furthermore, the coefficients of thermal expansion (CTE) of these solid solutions are precisely tuned within the desired range for SiC (4.4 to 5.5 × 10 −6 K −1 ), while maintaining good mechanical properties. Here, in particular, the addition of Eu 2 Si 2 O 7 demonstrates to be an important variable to the tuning of CTE and lattice thermal conductivity by leveraging its strong anharmonicity, presenting a pioneering avenue for fine-tuning material properties. In summary, this research not only identifies promising TEBC materials with superior thermal properties, but also introduces a valuable computational material design methodology for the rapid discovery of complex materials for harsh environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Subexponential Decay of Local Correlations from Diffusion-Limited Dephasing

Chaotic quantum systems at finite entropy density are expected to act as their own heat baths, rapidly dephasing local quantum superpositions. Here, we argue that in fact this dephasing is generically subexponential in one-dimensional systems with conservation laws: all local correlation functions decay as exp⁡[−𝒪⁡(𝑡 𝛼 )] with 0 ≤ 𝛼 ≤ 2/3, even when the operators are orthogonal to all hydrodynamic modes. The mechanism is diffusion-limited dephasing, in which rare low-entropy regions (“voids”) protect quantum coherences. This intrinsically quantum effect lies beyond standard hydrodynamics and disappears under extrinsic dephasing. In random charge-conserving circuits we find 𝛼 = 1/2, while in generic translation-invariant Floquet systems we bound 𝛼 ≤ 2/3. Our arguments are general, subject principally to the assumption that thermal fluctuations can create regions of zero entropy density. In systems with energy conservation, this assumption is automatically satisfied because of the third law of thermodynamics.

information scrambling↗
DOE OSTI2025

Doping Effects on the Ductility of a Lightweight Refractory High-Entropy Alloy: Grain Boundary and Bulk Lattice Aspects

Doping elements in small amounts often segregate to grain boundaries (GBs) in alloys and can significantly impact mechanical properties and performance. Refractory high-entropy alloys (RHEAs) are known for their poor ductility, especially at low temperatures. Promoting GB cohesion through segregation can be an effective approach to mitigate embrittlement. Here, in this study, first-principles density functional theory (DFT) calculations were performed to examine the effects of important interstitial dopants (O, B, C, and N) and substitutional dopants (Cr, Y, La, and Ce) on the Σ5(310) [001] tilt GB of a lightweight RHEA Nb 32.5 Ti 27.5 Mo 22.5 Ta 12.5 Hf 2.5 Zr 2.5 . The DFT calculations reveal that certain dopants, such as B, C, Cr, N, and Y, exhibit favorable GB strengthening effects by improving bonding interactions with the bulk alloy. The impact of doping on the ductility parameter of the bulk lattice, defined as the ratio of surface energy to unstable stacking fault energy for the {110} <111> slip system, was also studied; and the results show that doping reduces the intrinsic ductility of the alloy, decreasing the D-parameter from 2.90 to 2.55, depending on the specific dopant. The present findings provide a foundational understanding at atomic level of the effect of representative dopants on mechanical properties of RHEAs and can be used to guide future alloy design for improved mechanical properties.

deformation charge density↗
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 OSTI2022

Direct observation of elemental fluctuation and oxygen octahedral distortion-dependent charge distribution in high entropy oxides

The enhanced compositional flexibility to incorporate multiple-principal cations in high entropy oxides (HEOs) offers the opportunity to expand boundaries for accessible compositions and unconventional properties in oxides. Attractive functionalities have been reported in some bulk HEOs, which are attributed to the long-range compositional homogeneity, lattice distortion, and local chemical bonding characteristics in materials. However, the intricate details of local composition fluctuation, metal-oxygen bond distortion and covalency are difficult to visualize experimentally, especially on the atomic scale. Here, we study the atomic structure-chemical bonding-property correlations in a series of perovskite-HEOs utilizing the recently developed four-dimensional scanning transmission electron microscopy techniques which enables to determine the structure, chemical bonding, electric field, and charge density on the atomic scale. The existence of compositional fluctuations along with significant composition-dependent distortion of metal-oxygen bonds is observed. Consequently, distinct variations of metal-oxygen bonding covalency are shown by the real-space charge-density distribution maps with sub-ångström resolution. The observed atomic features not only provide a realistic picture of the local physico-chemistry of chemically complex HEOs but can also be directly correlated to their distinctive magneto-electronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Defect graph neural networks for materials discovery in high-temperature clean-energy applications

We present a graph neural network approach that fully automates the prediction of defect formation enthalpies for any crystallographic site from the ideal crystal structure, without the need to create defected atomic structure models as input. Here we used density functional theory reference data for vacancy defects in oxides, to train a defect graph neural network (dGNN) model that replaces the density functional theory supercell relaxations otherwise required for each symmetrically unique crystal site. Interfaced with thermodynamic calculations of reduction entropies and associated free energies, the dGNN model is applied to the screening of oxides in the Materials Project database, connecting the zero-kelvin defect enthalpies to high-temperature process conditions relevant for solar thermochemical hydrogen production and other energy applications. The dGNN approach is applicable to arbitrary structures with an accuracy limited principally by the amount and diversity of the training data, and it is generalizable to other defect types and advanced graph convolution architectures. In conclusion, it will help to tackle future materials discovery problems in clean energy and beyond.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Thermodynamic Data For 50 Chemical Elements

Report presents data on thermo-dynamic properties of 50 chemical elements, isotope (deuterium) of one of elements, and electron gas, all in standard reference states. Data tabulated as functions of temperature; also given in form of least-squares-fit coefficients of two functional forms for heat capacities at constant pressure in standard states, with constants of integration for enthalpy and entropy.

Mcbride, Bonnie J.↗
NASA NTRS2014

Experimental and Theoretical Study of Thermodynamics of the Reaction of Titania and Water at High Temperatures

The transpiration method was used to determine the volatility of titanium dioxide (TiO2) in water vapor-containing environments at temperatures between 1473 and 1673 K. Water contents ranged from 0 to 76 mole % in oxygen or argon carrier gases for 20 to 250 hr exposure times. Results indicate that oxygen is not a key contributor to volatilization and the primary reaction for volatilization in this temperature range is: TiO2(s) + H2O(g) = TiO(OH)2(g). Data were analyzed with both the second and third law methods to extract an enthalpy and entropy of formation. The geometry and vibrational frequencies of TiO(OH)2(g) were computed using B3LYP density functional theory, and the enthalpy of formation was computed using the coupled-cluster singles and doubles method with a perturbative correction for connected triple substitutions [CCSD(T)]. Thermal functions are calculated using both a structure with bent and linear hydroxyl groups. Calculated second and third heats show closer agreement with the linear hydroxyl group, suggesting more experimental and computational spectroscopic and structural work is needed on this system.

equilibrium↗
DOE OSTI2020

Predicting the Phase Stability of Multicomponent High-Entropy Compounds

A generic method to estimate the relative feasibility of formation of high-entropy compounds in a single phase, directly from first principles, is developed. As a first step, the relative formation abilities of 56 multicomponent, AO, oxides were evaluated. These were constructed from five cation combinations chosen from A = {Ca, Co, Cu, Fe, Mg, Mn, Ni, Zn}. Candidates for multicomponent oxides are predicted from descriptors related to the enthalpy and configurational entropy obtained from the mixing enthalpies of two-component oxides. The utility of this approach is evaluated by comparing the predicted combinations with the experimentally realized entropy-stabilized oxide, (MgCoCuNiZn)O. In the second step, Monte Carlo simulations are utilized to investigate the phase composition and local ionic segregation as a function of temperature. This approach allows for the evaluation of potential secondary phases, thereby making realistic predictions of novel multicomponent compounds that can be synthesized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Chemical Environment and Structural Variations in High Entropy Oxide Thin Film Probed with Electron Microscopy

For this work, we employ analytical transmission electron microscopy (TEM) to correlate the structural and chemical environment variations within a stacked epitaxial thin film of the high entropy oxide (HEO) Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 O (J14), with two layers grown at different substrate temperatures (500 and 200 °C) using pulsed laser deposition (PLD). Electron diffraction and atomically resolved STEM imaging reveal the difference in out-of-plane lattice parameters in the stacked thin film, which is further quantified on a larger scale using four-dimensional STEM (4D-STEM). In the layer deposited at a lower temperature, electron energy loss spectroscopy (EELS) mapping indicates drastic changes in the oxidation states and bonding environment for Co ions, and energy-dispersive X-ray spectroscopy (EDX) mapping detects more significant cation deficiency. Ab initio density functional theory (DFT) calculations validate that vacancies on the cation sublattice of J14 result in significant electronic and structural changes. The experimental and computational analyses indicate that low temperatures during film growth result in cation deficiency, an altered chemical environment, and reduced lattice parameters while maintaining a single phase. Our results demonstrate that the complex correlation of configurational entropy, kinetics, and thermodynamics can be utilized for accessing a range of metastable configurations in HEO materials without altering cation proportions, enabling further engineering of functional properties of HEO materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Plastic deformation of single crystals of the equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloy in tension and compression from 10 K to 1273 K

In this report the plastic deformation behavior of single crystals of the quinary, equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloy (HEA) with the face-centered cubic structure has been investigated in tension and compression as a function of crystal orientation and temperature from 10 K to 1373 K. The critical resolved shear stress (CRSS) for {111}<110> slip at room temperature is 42-45 MPa. It does not depend much on crystal orientation (i.e., the Schmid law holds true) and the sense (tension vs. compression) of the applied load. The CRSS for {111}<110> slip increases with the decrease in temperature, without showing any significant inertia effects at cryogenic temperatures below 77 K. Extrapolation from the measured yield stresses down to 10 K yields a CRSS value at 0 K of 168 MPa. At cryogenic temperatures, the measured strain-rate sensitivity of flow stress is consistent with a very small activation volume. The concept of stress equivalence holds true both for the temperature dependence of CRSS and the stress dependence of activation volume, indicating that solid-solution hardening is the major strengthening mechanism. Deformation twinning occurs at 77 K but not at room temperature, resulting in higher tensile elongation to failure at 77 K than at room temperature. Deformation twinning at 77 K occurs at a shear stress of 378 MPa on conjugate ($\bar1\bar11$) planes in the form of Lüders deformation after large plastic strain (about 85%) achieved by the stage I (easy glide) and stage II (linear work-hardening) deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lithium superoxide-based high rate Li-Air batteries enabled by Di-iridium sulfur bridge active sites

Li-oxygen (Li-O 2 ) batteries can potentially provide much higher energy density than Li-ion batteries; however, the practical application of these batteries is hindered due to several drawbacks such as low current rates and high overpotential for the charging process. Here, in this paper, we report a novel Li-Air battery system that operates under high current rates (up to 1mAcm -2 ) with LiO 2 as the primary discharge product instead of the commonly reported Li 2 O 2 . This LiO 2 based battery at high rates is through a combination of an as-synthesized new one-dimensional (1D) transition metal trichalcogenide mid-entropy alloy of SnIrS 3.6 as a cathode catalyst and an electrolyte blend with a SnI 2 bi-functional additive. It is revealed that SnIrS 3.6 has a microporous structure composed of six- and five-coordinated metal atoms, forming octahedral and triangular bipyramids which has not been observed in other layered chalcogeide materials. DFT calculations reveal that the SnIrS 3.6 structure can result in LiO 2 formation through di-iridium sulfur bridge active sites that results in strong binding of O 2 and LiO 2 preventing disproportionation to Li 2 O 2 and enabling high rates. This finding will open a new perspective in designing advanced LiO 2 -based Li-O 2 batteries for real practices.

25 ENERGY STORAGE↗
DOE OSTI2024

A note on higher-order and nonlinear limiting approaches for continuously bounds-preserving discontinuous Galerkin methods

In Dzanic (2024), a limiting approach for high-order discontinuous Galerkin schemes was introduced which allowed for imposing constraints on the solution continuously (i.e., everywhere within the element). While exact for linear constraint functionals, this approach only imposed a sufficient (but not the minimum necessary) amount of limiting for nonlinear constraint functionals. This short note shows how this limiting approach can be extended to allow exactness for general nonlinear quasiconcave constraint functionals through a nonlinear limiting procedure, reducing unnecessary numerical dissipation. Finally, some examples are shown for nonlinear pressure and entropy constraints in the compressible gas dynamics equations, where both analytic and iterative approaches are used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Era of entropy: Synthesis, structure, properties, and applications of high-entropy materials

The field of high-entropy materials (HEMs) has emerged as a dynamic area of scientific exploration, driven by the exceptional properties arising from their compositional complexity. Encompassing both high-entropy alloys (HEAs) and high-entropy ceramics (HECs), these materials have garnered significant attention across diverse research domains. From investigations into phase evolution and mechanical characteristics to studies of ionic, electronic, and magnetic behaviors, HEMs demonstrate remarkable potential for a wide array of applications. These range from catalysis and tribology to energy storage and superconductivity. Fundamental research has shed light on crucial phenomena such as configurational entropy, lattice distortion, and sluggish diffusion. These discoveries are paving the way for materials design strategies that enable new functional tunability and resistance to application-specific harsh environments. This burgeoning field promises to revolutionize material design and performance across numerous technological sectors. Here, this special collection between Applied Physics Letters and the Journal of Applied Physics provides a timely overview of the latest research in this area. It highlights the growing interest in understanding the impact of high compositional complexity on conventional structure–process–property–performance relationships in HEMs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mean-field entanglement transitions in random tree tensor networks

Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a mean-field theory of such transitions by studying the entanglement properties of random tree tensor networks. As a function of bond dimension, we find a phase transition separating area-law from logarithmic scaling of the entanglement entropy. Using a mapping onto a replica statistical mechanics model defined on a Cayley tree and the cavity method, we analyze the scaling properties of such transitions. Our approach provides a tractable, mean-field-like example of an entanglement transition. Furthermore, we verify our predictions numerically by computing directly the entanglement of random tree tensor network states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Glass Refraction Distortion Object Detection via Abstract Features

Glass reflection and refraction lead to missing and distorted object feature data, affecting the accuracy of object detection. In order to solve the above problems, this paper proposed a glass refraction distortion object detection via abstract features. The number of parameters of the algorithm is reduced by introducing skip connections and expansion modules with different expansion rates. The abstract feature information of the object is extracted by binary cross-entropy loss. Meanwhile, the abstract feature distance between the object domain and source domain is reduced by a loss function, which improves the accuracy of object detection under glass interference. To verify the effectiveness of the algorithm in this paper, the GRI dataset is produced and made public on GitHub. The algorithm of this paper is compared with the current state-of-the-art Deep Face, VGG Face, TBE-CNN, DA-GAN, PEN-3D, LMZMPM, and the average detection accuracy of our algorithm is 92.57% at the highest, and the number of parameters is only 5.13 M.

Cai, Lei↗