Structured and Unstructured Entropy-Stable High-Order Methods for Simulating High-Speed Compressible Turbulent Flows.
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We develop a discretely entropy-stable line-based discontinuous Galerkin method for hyperbolic conservation laws based on a flux differencing technique. By using standard entropy-stable and entropy-conservative numerical flux functions, this method guarantees that the discrete integral of the entropy is non-increasing. This nonlinear entropy stability property is important for the robustness of the method, in particular when applied to problems with discontinuous solutions or when the mesh is under-resolved. This line-based method is significantly less computationally expensive than a standard DG method. Numerical results are shown demonstrating the effectiveness of the method on a variety of test cases, including Burgers’ equation and the Euler equations, in one, two, and three spatial dimensions.
The realization of low thermal conductivity at high temperatures (0.11 W m –1 K –1 800 °C) in ambient air in a porous solid thermal insulation material, using stable packed nanoparticles of high-entropy spinel oxide with 8 cations (HESO-8 NPs) with a relatively high packing density of ≈50%, is reported. The high-density HESO-8 NP pellets possess around 1000-fold lower thermal diffusivity than that of air, resulting in much slower heat propagation when subjected to a transient heat flux. The low thermal conductivity and diffusivity are realized by suppressing all three modes of heat transfer, namely solid conduction, gas conduction, and thermal radiation, via stable nanoconstriction and infrared-absorbing nature of the HESO-8 NPs, which are enabled by remarkable microstructural stability against coarsening at high temperatures due to the high entropy. Furthermore, this work can elucidate the design of the next-generation high-temperature thermal insulation materials using high-entropy ceramic nanostructures.
Abstract Grain growth is prevalent in nanocrystalline (NC) materials at low homologous temperatures. Solute element addition is used to offset excess energy that drives coarsening at grain boundaries (GBs), albeit mostly for simple binary alloys. This thermodynamic approach is considered complicated in multi‐component alloy systems due to complex pairwise interactions among alloying elements. Guided by empirical and GB‐segregation enthalpy considerations for binary‐alloy systems, a novel alloy design strategy, the “ pseudo‐binary thermodynamic ” approach, for stabilizing NC‐high entropy alloys (HEAs) and other multi‐component‐alloy variants is proposed. Using Al 25 Co 25 Cr 25 Fe 25 as a model‐HEA to validate this approach, Zr, Sc, and Hf, are identified as the preferred solutes that would segregate to HEA‐GBs to stabilize it against growth. Using Zr, NC‐Al 25 Co 25 Cr 25 Fe 25 HEAs with minor additions of Zr are synthesized, followed by annealing up to 1123 K. Using advanced characterization techniques— in situ X‐ray diffraction (XRD), scanning/transmission electron microscopy (S/TEM), and atom probe tomography, nanograin stability due to coupling self‐stabilization and solute‐GB segregation effects is reported in HEAs up to substantially high temperatures. The self‐stabilization effect originates from the preferential GB‐segregation of constituent HEA‐elements that stabilizes NC‐Al 25 Co 25 Cr 25 Fe 25 up to 0.5 T m ( T m –melting temperature). Meanwhile, solute‐GB segregation originates from Zr segregation to NC‐Al 25 Co 25 Cr 25 Fe 25 GBs; this results in further stabilization of the phase and grain‐size (≈14 nm) up to ≈0.58 and ≈0.64 T m , respectively.
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Thermal degradation is a leading cause of automotive catalyst deactivation. Because high-entropy oxides are uniquely stabilized at high temperatures via an increase in configurational entropy, these materials may offer new mechanisms for preventing the thermal deactivation of precious metal catalysts. In this work, we evaluated platinum loaded on simple and high-entropy aluminate spinels (MAl 2 O 4 , where M = Co, Cu, Mg, Ni, or mixtures thereof) in carbon monoxide oxidation before and after aging at 800 °C. Pt supported on all simple spinels showed significant deactivation after thermal aging compared to the fresh samples, with T 90 increasing by at least 60 °C. However, Pt on high-entropy spinels had nearly the same or better activity after aging, with T 90 increasing by only 6 °C at most. During aging and reduction, copper exsolved from the spinel supports and alloyed with platinum. This interaction promoted low temperature oxidation activity, presumably through weakened CO binding, but did not prevent deactivation. On the other hand, Co, Mg, and Ni constituents promoted stronger CO bonding, as evidenced by apparent negative order kinetics and poor activity at low temperatures. High-entropy spinels, containing a variety of active metals, displayed synergetic reactant adsorption capacity and cooperative effects with supported platinum particles, which collectively prevented thermal deactivation.
A critical mission need exists to develop new materials that can withstand extreme environments and multiple sequential threats. High entropy materials, those containing 5 or more metals, exhibit many exciting properties which would potentially be useful in such situations. However, a particularly hard challenge in developing new high entropy materials is determining a priori which compositions will form the desired single phase material. The project outlined here combined several modeling and experimental techniques to explore several structure-property-relationships of high entropy ceramics in an effort to better understand the connection between their compositional components, their observed properties, and stability. We have developed novel machine learning algorithms which rapidly predict stable high entropy ceramic compositions, identified the stability interplay between configurational entropy and cation defects, and tested the mechanical stability of high entropy oxides using the unique capabilities at the Dynamic Compression Sector facility and the Saturn accelerator.
Prussian blue analogues (PBAs) used as sodium ion battery (SIB) cathodes are usually the focus of attention due to their three-dimensional open frame and high theoretical capacity. Nonetheless, the disadvantages of a low working voltage and inferior structural stability of PBAs prevent their further applications. Herein, we propose constructing the K x (MnFeCoNiCu)[Fe(CN) 6 ] (HE-K-PBA) cathode by high-entropy and potassium incorporation strategy to simultaneously realize high working voltage and cycling stability. In this study, the reaction mechanism of metal cations in HE-K-PBA are revealed by synchrotron radiation X-ray absorption spectroscopy (XAS), ex situ X-ray photoelectron spectroscopy (XPS), and in situ Raman spectra. We also investigate the entropy stabilization mechanism via finite element simulation, demonstrating that HE-K-PBA with small von Mises stress and weak structure strain can significantly mitigate the structural distortion. Benefit from the stable structure and everlasting K + (de)intercalation, the HE-K-PBA delivers high output voltage (3.46 V), good reversible capacity (120.5 mAh g –1 at 0.01 A g –1 ), and capacity retention of 90.4% after 1700 cycles at 1.0 A g –1 . Moreover, the assembled full cell and all-solid-state batteries with a stable median voltage of 3.29 V over 3000 cycles further demonstrate the application prospects of the HE-K-PBA cathode.
The study of conformal boundary conditions for two-dimensional conformal field theories (CFTs) has a long history, ranging from the description of impurities in one-dimensional quantum chains to the formulation of D-branes in string theory. Nevertheless, the landscape of conformal boundaries is largely unknown, including in rational CFTs, where the local operator data is completely determined. We initiate a systematic bootstrap study of conformal boundaries in 2d CFTs by investigating the bootstrap equation that arises from the open-closed consistency condition of the annulus partition function with identical boundaries. We find that this deceivingly simple bootstrap equation, when combined with unitarity, leads to surprisingly strong constraints on admissible boundary states. In particular, we derive universal bounds on the tension (boundary entropy) of stable boundary conditions, which provide a rigorous diagnostic for potential D-brane decays. We also find unique solutions to the bootstrap problem of stable branes in a number of rational CFTs. Along the way, we observe a curious connection between the annulus bootstrap and the sphere packing problem, which is a natural extension of previous work on the modular bootstrap. We also derive bounds on the boundary entropy at large central charge. These potentially have implications for end-of-the-world branes in pure gravity on AdS 3 .
In this paper, the effects of m = 0 modes on equilibrium Z-pinch plasmas are studied using a drift-ideal magnetohydrodynamic (MHD) model. The model equations are an extension of ideal MHD to include finite-ion-inertial-length/cyclotron-frequency (Ω i ) effects in Ohm's law and in the electron and ion heat transport equations. The linear modes contained in this model include the ideal interchange (sausage) mode and in the magnetized limit, Ω i τ i »1 with τ i the ion collision time, nonideal entropy modes. It is well known that these two modes are decoupled in the kρ s « 1 limit, where k is the axial mode number and ρ s = c s /Ω i is the gyro-Bohm scale with c s the sound speed [B. Kadomtsev, Sov. Phys. JETP-USSR 10, 780 (1960)]. For Bennett equilibrium profiles, it is shown that the regions of stability for both modes are completely governed by the adiabatic coefficient γ in these limits. Equilibria with Bennett profiles are stable to entropy modes for γ < 2 but unstable to ideal modes and vice versa for γ > 2. However, these modes are no longer decoupled when kρ s ≳1. The simulation results of the fully nonlinear set of equations in the magnetized limit show that seeded modes with kρ s ≳1 and γ = 5/3 display the characteristics of both ideal and entropy modes. The general heat flux for both ions and electrons as a function of the species magnetization is retained in the model. Both the linear and nonlinear behaviors of seeded modes for kρ s ≳1 display a strong dependence on the magnetization of the ions. Lastly, the growth rate increases linearly with k at large kρ s when the ions are magnetized but decreases with increasing k when Ω i τ i ≲1.
High-entropy alloys (HEAs) represent a promising class of materials with exceptional structural and functional properties. However, their design and optimization pose challenges due to the large composition-phase space coupled with the complex and diverse nature of the phase formation dynamics. In this study, a data-driven approach that utilizes machine learning (ML) techniques to predict HEA phases and their composition-dependent phases is proposed. By employing a comprehensive dataset comprising 5692 experimental records encompassing 50 elements and 11 phase categories, we compare the performance of various ML models. Our analysis identifies the most influential features for accurate phase prediction. Furthermore, the class imbalance is addressed by employing data augmentation methods, raising the number of records to 1500 in each category, and ensuring a balanced representation of phase categories. The results show that XGBoost and Random Forest consistently outperform the other models, achieving 86% accuracy in predicting all phases. Additionally, this work provides an extensive analysis of HEA phase formers, showing the contributions of elements and features to the presence of specific phases. We also examine the impact of including different phases on ML model accuracy and feature significance. Notably, the findings underscore the need for ML model selection based on specific applications and desired predictions, as feature importance varies across models and phases. This study significantly advances the understanding of HEA phase formation, enabling targeted alloy design and fostering progress in the field of materials science.
Abstract Superionic solid electrolytes (SEs) are essential for bulk‐type solid‐state battery (SSB) applications. Multicomponent SEs are recently attracting attention for their favorable charge‐transport properties, however a thorough understanding of how configurational entropy (ΔS conf ) affects ionic conductivity is lacking. Here, we successfully synthesized a series of halogen‐rich lithium argyrodites with the general formula Li 5.5 PS 4.5 Cl x Br 1.5‐x (0≤x≤1.5). Using neutron powder diffraction and 31 P magic‐angle spinning nuclear magnetic resonance spectroscopy, the S 2− /Cl − /Br − occupancy on the anion sublattice was quantitatively analyzed. We show that disorder positively affects Li‐ion dynamics, leading to a room‐temperature ionic conductivity of 22.7 mS cm −1 (9.6 mS cm −1 in cold‐pressed state) for Li 5.5 PS 4.5 Cl 0.8 Br 0.7 (ΔS conf =1.98R). To the best of our knowledge, this is the first experimental evidence that configurational entropy of the anion sublattice correlates with ion mobility. Our results indicate the possibility of improving ionic conductivity in ceramic ion conductors by tailoring the degree of compositional complexity. Moreover, the Li 5.5 PS 4.5 Cl 0.8 Br 0.7 SE allowed for stable cycling of single‐crystal LiNi 0.9 Co 0.06 Mn 0.04 O 2 (s‐NCM90) composite cathodes in SSB cells, emphasizing that dual‐substituted lithium argyrodites hold great promise in enabling high‐performance electrochemical energy storage.
Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. A total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.
We compute the four-derivative corrections to the geometry, extremality bound, and thermodynamic quantities of AdS-Reissner-Nordström black holes for general dimensions and horizon geometries. We confirm the universal relationship between the extremality shift at fixed charge and the shift of the microcanonical entropy, and discuss the consequences of this relation for the Weak Gravity Conjecture in AdS. The thermodynamic corrections are calculated using two different methods: first by explicitly solving the higher-derivative equations of motion and second, by evaluating the higher-derivative Euclidean on-shell action on the leading-order solution. In both cases we find agreement, up to the addition of a Casimir energy in odd dimensions. We derive the bounds on the four-derivative Wilson coefficients implied by the conjectured positivity of the leading corrections to the microcanonical entropy of thermodynamically stable black holes. These include the requirement that the coefficient of Riemann-squared is positive, meaning that the positivity of the entropy shift is related to the condition that c – a is positive in the dual CFT. We discuss implications for the deviation of η/s from its universal value and a potential lower bound.
The constant-Q Gabor atom is developed for spectral power, information, and uncertainty quantification from time–frequency representations. Stable multiresolution spectral entropy algorithms are constructed with continuous wavelet and Stockwell transforms. The recommended processing and scaling method will depend on the signature of interest, the desired information, and the acceptable levels of uncertainty of signal and noise features. Selected Lamb wave signatures and information spectra from the 2022 Tonga eruption are presented as representative case studies. Resilient transformations from physical to information metrics are provided for sensor-agnostic signal processing, pattern recognition, and machine learning applications.