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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fractionalized Excitations Revealed by Entanglement Entropy

Fractionalized excitations develop in many unusual many-body states such as quantum spin liquids, disordered phases that cannot be described using any local order parameter. Also, because these exotic excitations correspond to emergent degrees of freedom, how to probe them and establish their existence is a long-standing challenge. We present a general procedure to reveal the fractionalized excitations using real-space entanglement entropy in critical spin liquids that are particularly relevant to experiments. Furthermore, we show how to use the entanglement entropy to construct the corresponding spinon Fermi surface. Our work defines a new pathway to establish and characterize exotic excitations in novel quantum phases of matter.

2-dimensional systems↗
DOE OSTI2022

Postquantum Quench Growth of Renyi Entropies in Low-Dimensional Continuum Bosonic Systems

The growth of Renyi entropies after the injection of energy into a correlated system provides a window upon the dynamics of its entanglement properties. Here we develop a simulation scheme by which this growth can be determined in Luttinger liquids systems with arbitrary interactions, even those introducing gaps into the liquid. We apply this scheme to an experimentally relevant quench in the sine-Gordon field theory. While for short times we provide analytic expressions for the growth of the second and third Renyi entropy, to access longer times, we combine our scheme with truncated spectrum methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Microscopic Origin of the Entropy of Black Holes in General Relativity

We construct an infinite family of microstates with geometric interiors for eternal black holes in general relativity with a negative cosmological constant in any dimension. Wormholes in the Euclidean path integral for gravity cause these states to have small, but nonzero, quantum mechanical overlaps that have a universal form. The overlaps have a dramatic consequence: The microstates span a Hilbert space of log dimension equal to the Bekenstein-Hawking entropy. The semiclassical microstates we construct contain Einstein-Rosen bridges of arbitrary size behind their horizons. Our results imply that all these bridges can be interpreted as quantum superpositions of wormholes of size at most exponential in the entropy.

Physics↗
DOE OSTI2025

Pressure-induced irreversible volume collapse in a high-entropy alloy

At ambient conditions, the high-entropy alloy superconductor R⁢e 0.6⁢ (NbTiZrHf) 0.4 exhibits exceptional mechanical properties among high-entropy alloys, with its hexagonal phase achieving nanoindentation hardness of 18.5 GPa. We report on a unique pressure-induced structural transformation from a hexagonal phase to a body-centered cubic (BCC) phase, revealed by synchrotron x-ray diffraction measurements up to 70 GPa. This first-order transition, accompanied by a 6.1% volume collapse, occurs at 44 GPa and results in a BCC structure with random site occupancy by the five constituent elements, which is remarkably retained upon decompression to ambient conditions. The transformation proceeds via a martensiticlike, diffusionless mechanism without elemental segregation, enabled by pressure-induced electronic redistribution and atomic-scale disorder. These findings demonstrate a rare case of metastable phase retention in a chemically complex alloy and offer new insights into structure-stability relationships under pressure.

Alloys↗
DOE OSTI2023

Optimization of Dimensions of Smooth and Twisted-Tape-Inserted Tubes for Heat Transfer with NaCl/KCl/MgCl 2 Molten Salts by Principle of Entropy Generation Minimization

The entropy generation minimization principle is used as the criterion to optimize the flow and heat transfer of solar collectors and heat exchangers that use molten salts NaCl–KCl–MgCl 2 and KCl–MgCl 2 . The Gnielinski correlation for the Nusselt number versus Reynolds number, as well as the Moody friction factor given by Petukhov, was used for the calculation of the convective heat transfer coefficient and pressure loss due to friction in smooth tubes. For twisted-tap-inserted tube, equations of Nu and friction factor provided by Manglik and Bergles were used. The objective function, the entropy generation rate of the heat transfer system, was expressed as the function of Reynolds number, Prandtl number, heating flux, tube diameter, etc. As a result of the analysis, the optimum Reynolds number was determined and thereby to determine the optimum Nusselt number, convective heat transfer coefficient, friction factor, and tube diameter, which also allows the calculation of optimum flow velocity. The analysis was conducted in the fluid temperature range of 500–700 °C, which covers the operation temperature for supercritical CO 2 power cycles in concentrated solar power (CSP) system. Here, optimized results from the smooth tube and twisted-tap-inserted tube are compared, which is important to the design of solar receivers for CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2015

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection

Purpose: Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Methods: Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors’ proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. Results: The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p < 0.03). In the atlas database study, the authors showed that the MAS using larger atlas databases generated better performance curves than the MAS using smaller ones, indicating larger atlas databases could produce more accurate segmentation. Conclusions: The authors have developed a new MAS framework for automatic WHS of CTA and investigated alternative implementations of MAS. With the proposed atlas ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation within practically acceptable computation time. This method can be useful for the development of new clinical applications of cardiac CT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Misanthropic entropy and renormalization as a communication channel

A central physical question is the extent to which infrared (IR) observations are sufficient to reconstruct a candidate ultraviolet (UV) completion. We recast this question as a problem of communication, with messages encoded in field configurations of the UV being transmitted to the IR degrees of freedom via a noisy channel specified by renormalization group (RG) flow, with noise generated by coarse graining/decimation. We present an explicit formulation of these considerations in terms of lattice field theory, where we show that the “misanthropic entropy” — the mutual information obtained from decimating neighbors — encodes the extent to which information is lost in marginalizing over/tracing out UV degrees of freedom. Our considerations apply both to statistical field theories as well as density matrix renormalization of quantum systems, where in the quantum case, the statistical field theory analysis amounts to a leading-order approximation. As a concrete example, we focus on the case of the 2D Ising model, where we show that the misanthropic entropy detects the onset of the phase transition at the Ising model critical point.

Physics↗
DOE OSTI2023

Entropy-driven Optimal Sub-sampling of Fluid Dynamics for Developing Machine-learned Surrogates

Optimal sub-sampling of large datasets from fluid dynamics simulations is essential for training reduced-order machine learned models. A method using Shannon entropy was developed to weight flow features according to their level of information content, such that the most informative features can be extracted and used for training a surrogate model. The method is demonstrated in the canonical flow over a cylinder problem simulated with OpenFOAM. Both time-independent predictions and temporal forecasting were investigated as well as two types of prediction targets: local per-grid-point predictions and global per-time-step predictions. When tested on training a surrogate model, results indicate that our entropy-based sampling method typically outperforms random sampling and yields more reproducible results in less iterations. Finally, the method was used to train a surrogate model for modeling turbulence in magnetohydrodynamic flows, which revealed various challenges and opportunities for future research.

Brewer, Wes↗
DOE OSTI2024

Quantifying the Temperature Dependence of the Multi-Species, Multi-Reaction Model: Part II. Estimation of Entropy Coefficient for Meso-Carbon Micro-Bead Graphite

In Part 1 of this paper, the temperature impact on the Multi-Species, Multi Reaction (MSMR) model was studied. This was accomplished by acquiring data from slow rate lithiation and delithiation of a meso-carbon micro-bead (MCMB) graphite. Through this analysis, the temperature impact on the total fraction of available host sites in a particular MSMR gallery (X j ), the impact on the reference potential (U$^o_j$), and the impact on the parameter detailing the deviation from Nernstian behavior (ω j ) was determined. Here, the intercalation material is discussed, compared to traditional methods of acquiring the entropy coefficient, and comparison is made to previous mathematical estimates. Some of the challenges in using temperature dependent constant rate charge and discharge data as compared to the potentiodynamic entropy coefficient calculation method are also discussed, and a recommendation for future applications is proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

High-entropy materials

We report that primarily over the last decade, the concept of multiple-principal-element metallic materials, commonly referred to as high-entropy alloys, or more generally, high-entropy materials, has taken the field of materials science, particularly structural metallurgy, by storm, at least as measured by the plethora of publications that are focused on this topic. In this article and the following six articles, we attempt to distill what all this is about, with a description of why these materials may be important, why they may differ from traditional materials and how theoretical, computational, and experimental studies can shed light on the science underlying their behavior and potential application.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-dimensional maximum-entropy phase space tomography

Reconstructing 4D or 6D phase space distributions from 1D or 2D measurements is a challenging inverse problem encountered in particle accelerators. Entropy maximization is an established method to incorporate prior information in the reconstruction, but it is typically infeasible in high-dimensional spaces. In this paper, I review two recent approaches to high-dimensional entropy maximization. The first approach utilizes differentiable simulations and a class of generative models known as normalizing flows, whereas the second approach employs the method of Lagrange multipliers and Markov Chain Monte Carlo (MCMC) sampling. My aim is to provide a short explanation of each method using a common notation. I conclude by mentioning several unsolved problems in phase space tomography.

Hoover, Austin [ORNL] (ORCID:0000000153136962)↗
DOE OSTI2023

Constraining braneworlds with entanglement entropy

We propose swampland criteria for braneworlds viewed as effective field theories of defects coupled to semiclassical gravity. We do this by exploiting their holographic interpretation. We focus on general features of entanglement entropies and their holographic calculations. Entropies have to be positive. Furthermore, causality imposes certain constraints on the surfaces that are used holographically to compute them, most notably a property known as causal wedge inclusion. As a test case, we explicitly constrain the Dvali-Gabadadze-Porrati term as a second-order-in-derivatives correction to the Randall-Sundrum action. We conclude by discussing the implications of these criteria for the question on whether entanglement islands in theories with massless gravitons are possible in Karch-Randall braneworlds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Subsystem Rényi entropy of thermal ensembles for SYK-like models

The Sachdev-Ye-Kitaev model is an N N -modes fermionic model with infinite range random interactions. In this work, we study the thermal Rényi entropy for a subsystem of the SYK model using the path-integral formalism in the large- N N limit. The results are consistent with exact diagonalization and can be well approximated by thermal entropy with an effective temperature when subsystem size M\leq N/2 M ≤ N / 2 . We also consider generalizations of the SYK model with quadratic random hopping term or U(1) U ( 1 ) charge conservation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Additive Manufacturing of Hierarchical Multi-Phase High-Entropy Alloys for Nuclear Component

In recent years, high entropy alloys (HEAs), composed of four or more metallic elements mixed in equal or near equal atomic percent, have attracted significant attention due to their excellent mechanical properties and good corrosion resistance. They show significant promise as candidates for high temperature fission and fusion structural applications. However, the conventional synthesis methods are unlikely to present an industrially suitable route for the production and use of HEAs. Recognizing rapidly evolving additive manufacturing (AM) techniques, the goal of this proposal is to optimize the AM process to fabricate HEAs with predesigned chemical compositions and phase morphologies for nuclear components. For this project, two HEAs FeCrNiMn and FeCrNiMnAl have been successfully synthesized. Correlated mechanical response has been systematically characterized under a variety of laser processing and ion irradiations. Both high entropy alloys are found to present comparable swelling and extraordinary irradiation tolerance (limited voids and stabilized phase structure under high irradiation dose). In addition, the microstructure and radiation-induced hardening can be tailored by laser processing under additive manufacturing. And we have assembled at LANL a unique database of HEAs containing a total of 674 compositions with Phase Stability information. Based on this, the machine learning and Artificial Intelligence capability now are established to predict the microstructure of casted HEAs by given chemical compositions. This unique integration will lead to an optimal AM recipe for fabricating radiation tolerant HEAs. The development of both modeling models and experimental capability will also benefit other programs at LANL.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Understanding the Deformation Mechanisms of FeNiMnAlCr High Entropy Alloys

The aim of this project was to understand the microstructure and mechanical properties of Fe-Ni-Mn-Al-Cr high entropy alloys. High entropy alloys are defined as materials containing five or more elements with each element constituting 5-35 atomic percent of the alloy. We performed several different tasks in this project. 1) We showed that reducing the crystal or grain size in single-phase Fe40Ni11Mn35Al8Cr6 containing either 1.1 atomic percent carbon added or with no carbon added produced a substantial increase in strength with a small reduction in ductility. The finer grain size material was produced by cold rolling followed by heating to recrystallize the microstructure. The changes in strength and ductility were related to observed changes in deformation structure as determined by transmission electron microscopy. We also examined how the deformation behavior changed with temperature from -200°C to 200°C. 2) We showed that heating Fe36Ni18Mn33Al13 with and without 1.26 at.% carbon led to ordered body-centered cubic precipitates forming in the materials, which were both initially two-phase. The heat treatment again led to substantial increases in strength with some reduction in ductility. 3) We examined whether titanium additions (2 atomic percent) to Fe42Ni18Mn33Al13 could improve the mechanical properties. We examined both as-cast material and material that had been recrystallized to produce a fine grain size. In both cases ordered body-centered cubic precipitates were present. Again, the recrystallization and resulting reduction in grain size increased the yield strength and reduced the ductility. We also showed, using high-resolution electron microscopy, that contrary to some predictions, having an alloy containing a range of atoms with different atomic diameters produced no lattice distortions. 4) We used scanning electron microscopy and transmission electron microscopy coupled with energy dispersive x-ray spectroscopy to show that carbides formed during intermediate temperature (≤800oC) heating of carbon-doped Fe40Ni11Mn35Al8Cr6. In addition to forming within the grains, the carbides coated the grain boundaries. This produced an increase in strength but a drastic reduction in ductility. However, we showed by hot rolling we could get both high strength and high ductility for this material. The work led to nine publications in referred journals and contributed to the education of two Ph.D. students. In addition, ten presentations (six of which were invited) at conferences, at a university and at a national laboratory in Germany.

36 MATERIALS SCIENCE↗
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↗
DOE OSTI2026

High Entropy Rare-earth Oxide (HERO) Coatings for Refractory Alloys

The HERO coating was developed to protect refractory alloys for application in the harsh hot section of the turbine engine environment addressing ARPA-E ULTIMATE Project Topic 2: Coating Development. The effort was both innovative in its utilization of high entropy rare earth oxides as well as transformational in our approach: holistic design of a single layer thermal/environmental barrier coating (T/EBC) for refractory alloys, with an excellent coefficient of thermal expansion (CTE) match to the alloy substrate, chemical compatibility with the underlying alloy, low oxidant permeability, stability in combustion environments, low thermal conductivity, thermal shock resistance, and resistance to degradation by siliceous debris (calcium magnesium alumino-silicates-CMAS). The high entropy rare earth oxide approach enables two critical coating properties: tailoring CTE match to the substrate and, most significantly, substantially reduced thermal conductivity. The summation of these proposed coating capabilities goes well beyond the technical requirements specified in the ULTIMATE program objectives, and additionally is essential for a successful first stage turbine blade application.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient First-Order Algorithms for Large-Scale, Non-Smooth Maximum Entropy Models with Application to Wildfire Science

Maximum entropy (MaxEnt) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, MaxEnt models need efficient optimization algorithms to scale well for big data applications. State-of-the-art algorithms for MaxEnt models, however, were not originally designed to handle big data sets; these algorithms either rely on technical devices that may yield unreliable numerical results, scale poorly, or require smoothness assumptions that many practical MaxEnt models lack. In this paper, we present novel optimization algorithms that overcome the shortcomings of state-of-the-art algorithms for training large-scale, non-smooth MaxEnt models. Our proposed first-order algorithms leverage the Kullback–Leibler divergence to train large-scale and non-smooth MaxEnt models efficiently. For MaxEnt models with discrete probability distribution of n elements built from samples, each containing m features, the stepsize parameter estimation and iterations in our algorithms scale on the order of O(mn) operations and can be trivially parallelized. Moreover, the strong ℓ1 convexity of the Kullback–Leibler divergence allows for larger stepsize parameters, thereby speeding up the convergence rate of our algorithms. To illustrate the efficiency of our novel algorithms, we consider the problem of estimating probabilities of fire occurrences as a function of ecological features in the Western US MTBS-Interagency wildfire data set. Our numerical results show that our algorithms outperform the state of the art by one order of magnitude and yield results that agree with physical models of wildfire occurrence and previous statistical analyses of wildfire drivers.

Physics↗