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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 1,171 records · Page 65
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DOE OSTI2024

Defect Properties, Anion Ordering, and Photochromic Mechanism in Yttrium Oxyhydride

Yttrium oxyhydride (YHO) undergoes a reversible photochromic transition when exposed to ultraviolet light. However, the mechanism for this transformation is not fully understood, and the structure and precise chemical composition of YHO remain under debate. Here, we use first-principles density functional theory calculations with a hybrid functional to study the structure, chemical stability, and point defect properties of YHO. As experiments have shown, we find that YHO prefers a cubic structure, with H and O anions present in equal concentrations and located on tetrahedral sites. Stoichiometric and ordered YHO is chemically stable, but it has a wide band gap of 5.01 eV, considerably larger than that measured in experiments (2.4–3.8 eV). On the other hand, Y4H10O has a smaller band gap of 2.97 eV and also has a region of chemical stability; thus, the actual material may include some fraction of this H-rich structure. The defect chemistry of YHO is dominated by anionic antisite species (H O and O H ), with hydrogen interstitials (H i ) and vacancies (V H ) also present in reasonably high concentrations. We show that antisite disorder lowers the band gap relative to the perfectly ordered structure, bringing the magnitude of the gap into closer agreement with experiment. Based on our calculations of defect migration and the positions of defect states relative to the band edges, we link the onset of photochromic behavior to the reaction H O – → V O 0 + H i – , which follows photoexcitation of a H O + defect. H i – can subsequently migrate away and be trapped by additional H O + defects, contributing to the persistence of the reaction, while the resultant oxygen vacancy, V O 0 , introduces an occupied defect state that leads to optical absorption at visible wavelengths. Our results can explain reported discrepancies between experimental and computational results for YHO, and they allow us to propose specific atomic-scale processes that can lead to photochromism. In conclusion, understanding these mechanisms is key for unlocking YHO’s application in devices ranging from smart windows and optoelectronics to electrochemical synapses for neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles

Abstract We design a deep-learning algorithm for the discovery and identification of the continuous group of symmetries present in a labeled dataset. We use fully connected neural networks to model the symmetry transformations and the corresponding generators. The constructed loss functions ensure that the applied transformations are symmetries and the corresponding set of generators forms a closed (sub)algebra. Our procedure is validated with several examples illustrating different types of conserved quantities preserved by symmetry. In the process of deriving the full set of symmetries, we analyze the complete subgroup structure of the rotation groups SO (2), SO (3), and SO (4), and of the Lorentz group S O ( 1 , 3 ) . Other examples include squeeze mapping, piecewise discontinuous labels, and SO (10), demonstrating that our method is completely general, with many possible applications in physics and data science. Our study also opens the door for using a machine learning approach in the mathematical study of Lie groups and their properties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

First High-Throughput Evaluation of Dark Matter Detector Materials

In this work we perform the first high-throughput search and evaluation of materials that can serve as excellent low-mass dark matter detectors. Using properties of close to 1000 materials from the Materials Project database, we project the sensitivity in dark matter parameter space for experiments constructed from each material, including both absorption and scattering processes between dark matter and electrons. Using the anisotropic materials in the dataset, we further compute the level of daily modulation in interaction rates and the resulting directional sensitivities, highlighting materials with prospects to detect the dark matter wind. Our methods provide the basic tools for the data-driven design of dark matter detectors, and our findings lay the groundwork for the next generation of highly optimized direct searches for dark matter as light as the keV scale. This represents a major step in the application of results from condensed matter physics to dark matter search design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Importance of bulk excitations and coherent electron-photon-phonon scattering in photoemission from PbTe(111): Ab initio theory with experimental comparisons

This paper presents a fully ab initio many-body photoemission framework that includes coherent three-body electron-photon-phonon scattering to predict the transverse momentum distributions and the mean transverse energies (MTEs) of bulk photoelectrons from single-crystal photocathodes. The need to develop such a theory stems from the lack of studies that provide complete understanding of the underlying fundamental processes governing the transverse momentum distribution of photoelectrons emitted from single crystals. For example, initial predictions based on density-functional theory calculations of effective electron masses suggested that the (111) surface of PbTe would produce very small MTEs (≤ 15 meV), whereas our experiments yielded MTEs ten to twenty times larger than these predictions and also exhibited a lower photoemission threshold than predicted. The ab initio framework presented in this paper correctly reproduces both the magnitude of the MTEs from our measurements in PbTe(111) and the observed photoemission below the predicted threshold. Our results show that both photoexcitations into states that propagate in the bulk of the material and coherent many-body electron-photon-phonon scattering processes, which initial predictions ignored, play surprisingly important roles in photoemission from PbTe(111). Lastly, from the lessons learned, we recommend a procedure for rapid computational screening of potential single-crystal photocathodes for applications in next-generation ultrafast electron diffraction and X-ray free-electron lasers, which will enable significant advances in condensed matter research.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Scaling adaptive quantum simulation algorithms via operator pool tiling

Adaptive variational quantum simulation algorithms use information from a quantum computer to dynamically create optimal trial wave functions for a given problem Hamiltonian. A key ingredient in these algorithms is a predefined operator pool from which trial wave functions are constructed. Finding suitable pools is critical for the efficiency of the algorithm as the problem size increases. Here, we present a technique called operator pool tiling that facilitates the construction of problem-tailored pools for arbitrarily large problem instances. By first performing an Adaptive Derivative-Assembled Problem-Tailored Ansatz Variational Quantum Eigensolver (ADAPT-VQE) calculation on a smaller instance of the problem using a large, but computationally inefficient, operator pool, we extract the most relevant operators and use them to design more efficient pools for larger instances. We demonstrate the method here on strongly correlated quantum spin models in one and two dimensions, finding that ADAPT automatically finds a highly effective ansatz for these systems. Given that many problems, such as those arising in condensed matter physics, have a naturally repeating lattice structure, we expect the pool tiling method to be a widely applicable technique apt for such systems. Published by the American Physical Society 2024

Van Dyke, John S. (ORCID:0000000167815480)↗
DOE OSTI2020

A Scalable Multigrid Reduction Framework for Multiphase Poromechanics of Heterogeneous Media

Simulation of multiphase poromechanics involves solving a multiphysics problem in which multiphase flow and transport are tightly coupled with the porous medium deformation. To capture this dynamic interplay, fully implicit methods, also known as monolithic approaches, are usually preferred. The main bottleneck of a monolithic approach is that it requires solution of large linear systems that result from the discretization and linearization of the governing balance equations. Because such systems are nonsymmetric, indefinite, and highly ill-conditioned, preconditioning is critical for fast convergence. Recently, most efforts in designing efficient preconditioners for multiphase poromechanics have been dominated by physics-based strategies. Current state-of-the-art “black-box” solvers such as algebraic multigrid (AMG) are ineffective because they cannot effectively capture the strong coupling between the mechanics and the flow subproblems, as well as the coupling inherent in the multiphase flow and transport process. In this work, we develop an algebraic framework based on multigrid reduction (MGR) that is suited for tightly coupled systems of PDEs. Using this framework, the decoupling between the equations is done algebraically through defining appropriate interpolation and restriction operators. One can then employ existing solvers for each of the decoupled blocks or design a new solver based on knowledge of the physics. We demonstrate the applicability of our framework when used as a “black-box” solver for multiphase poromechanics. Here, we show that the framework is flexible to accommodate a wide range of scenarios, as well as efficient and scalable for large problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and Networking - 2023

Employing quantum mechanical resources in computing and networking opens the door to new computation and communication models and potential disruptive advantages over classical counterparts. However, quantifying and realizing such advantages face extensive scientific and engineering challenges. Investments by the Department of Energy (DOE) have driven progress toward addressing such challenges. Quantum algorithms have been recently developed, in some cases offering asymptotic exponential advantages in speed or accuracy, for fundamental scientific problems such as simulating physical systems, solving systems of linear equations, or solving differential equations. Empirical demonstrations on nascent quantum hardware suggest better performance than classical analogs on specialized computational tasks favorable to the quantum computing systems. However, demonstration of an end-to-end, substantial and rigorously quantifiable quantum performance advantage over classical analogs remains a grand challenge, especially for problems of practical value. The definition of requirements for quantum technologies to exhibit scalable, rigorous, and transformative performance advantages for practical applications also remains an outstanding open question, namely, what will be required to ultimately demonstrate practical quantum advantage?

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and Networking - 2023

Employing quantum mechanical resources in computing and networking opens the door to new computation and communication models and potential disruptive advantages over classical counterparts. However, quantifying and realizing such advantages face extensive scientific and engineering challenges. Investments by the Department of Energy (DOE) have driven progress toward addressing such challenges. Quantum algorithms have been recently developed, in some cases offering asymptotic exponential advantages in speed or accuracy, for fundamental scientific problems such as simulating physical systems, solving systems of linear equations, or solving differential equations. Empirical demonstrations on nascent quantum hardware suggest better performance than classical analogs on specialized computational tasks favorable to the quantum computing systems. However, demonstration of an end-to-end, substantial and rigorously quantifiable quantum performance advantage over classical analogs remains a grand challenge, especially for problems of practical value. The definition of requirements for quantum technologies to exhibit scalable, rigorous, and transformative performance advantages for practical applications also remains an outstanding open question, namely, what will be required to ultimately demonstrate practical quantum advantage?

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

ν-point energy correletors with F AST EEC: Small-x physics from LHC jets

In recent years, energy correlators have emerged as a powerful tool for studying jet substructure, with promising applications such as probing the hadronization transition, analyzing the quark-gluon plasma, and improving the precision of top quark mass measurements. The projected N-point correlator measures correlations between N final-state particles by tracking the largest separation between them, showing a scaling behavior related to DGLAP splitting functions. These correlators can be analytically continued in N, commonly referred to as ν-correlators, allowing access to non-integer moments of the splitting functions. Of particular interest is the ν → 0 limit, where the small momentum fraction behavior of the splitting functions requires resummation. Originally, the computational complexity of evaluating ν-correlators for M particles scaled as 2 2M , making it impractical for real-world analyses. However, by using recursion, we reduce this to M 2M , and through the FastEEC method of dynamically resolving subjets, M is replaced by the number of subjets. This breakthrough enables, for the first time, the computation of ν-correlators for LHC data. In practice, limiting the number of subjets to 16 is sufficient to achieve percent-level precision, which we validate using known integer-ν results and convergence tests for non-integer ν. We have implemented this in an update to FastEEC and conducted an initial study of power-law scaling in the perturbative regime as a function of ν, using CMS Open Data on jets. The results agree with DGLAP evolution, except at small ν, where the anomalous dimension saturates to a value that matches the BFKL anomalous dimension.

Energy correlators↗
DOE OSTI2020

Unification of nonequilibrium molecular dynamics and the mode-resolved phonon Boltzmann equation for thermal transport simulations

Nano-size confinement induces many intriguing non-Fourier heat conduction phenomena, such as nonlinear temperature gradients, temperature jumps near the contacts, and size-dependent thermal conductivity. Over the past decades, these effects have been studied and interpreted by nonequilibrium molecular dynamics (NEMD) and phonon Boltzmann transport equation (BTE) simulations separately, but no theory that unifies these two methods has ever been established. In this work, we unify these methods using a quantitative mode-level comparison and demonstrate that they are equivalent for various thermostats. We show that different thermostats result in different non-Fourier thermal transport characteristics due to the different mode-level phonon excitations inside the thermostats, which explains the different size-dependent thermal conductivities calculated using different reservoirs, even though they give the same bulk thermal conductivity. Specifically, the Langevin thermostat behaves like a thermalizing boundary in phonon BTE and provides mode-level thermal-equilibrium phonon outlets, while the Nose-Hoover chain thermostat and velocity rescaling method behave like biased reservoirs, which provide a spatially uniform heat generation and mode-level nonequilibrium phonon outlets. These findings explain why different experimental measurement methods can yield different size-dependent thermal conductivity. They also indicate that the thermal conductivity of materials can be tuned for various applications by specifically designing thermostats. Finally, the unification of NEMD and phonon BTE will largely facilitate the study of thermal transport in complex systems in the future by, e.g., replacing computationally unaffordable first-principles NEMD simulations with computationally less expensive spectral BTE simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Hidden Rotation Symmetry of the Jordan–Wigner Transformation and Its Application to Measurement in Quantum Computation

Using a global rotation by 𝜃 about the z-axis in the spin sector of the Jordan–Wigner transformation rotates Pauli matrices 𝑋̂ and 𝑌̂ in the 𝑥−𝑦 -plane, while it adds a global complex phase to fermionic quantum states that have a fixed number of particles. With the right choice of angles, this relates expectation values of Pauli strings containing products of 𝑋̂ and 𝑌̂ to different products, which can be employed to reduce the number of measurements needed when simulating fermionic systems on a quantum computer. Here, we derive this symmetry and show how it can be applied to systems in Physics and Chemistry that involve Hamiltonians with only single-particle (hopping) and two-particle (interaction) terms. We also discuss the consequences of this for finding efficient measurement circuits in variational ground state preparation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Perspectives on van der Waals Density Functionals: The Case of TiS 2

The van der Waals interaction is of foundational importance for a wide variety of physical systems. In particular, van der Waals forces lie at the heart of potential device technologies that may be realized from the functional organization of layered two-dimensional (2D) nanomaterials. Furthermore, for intermediate to large-scale applications modeling, van der Waals density functionals have become the de facto choice for first-principles calculations. In particular, the vdW-DF family of functionals have provided a systematic approach to this theoretically challenging problem. While much progress has been made, there remains room for improvement in the microscopic description of vdW forces from these density functionals. In this work, we compute benchmark results for the binding energy and the electronic density response to binding in TiS2 via accurate diffusion quantum Monte Carlo calculations. We compare these benchmark data to results obtained from local, semilocal, and van der Waals functionals. In particular, we gauge the quality of the original vdW-DF/vdW-DF2 functionals, as well as updated variants such as vdW-DF-C09, vdW-DF-optB88, vdW-DF-optB86b, and vdW-DF2-B86R. We find a close relationship between the accuracy of predicted interlayer separation distances and binding energies for TiS 2 , with the vdW-DF-optB88 functional performing very well in terms of both quantities. In general, the more recently developed functionals are systematic improvements over older ones. However, when considering the response of the electron density to binding, we find that local-density approximation (LDA) and PBEsol generally outperform the vdW-DF functionals in describing the interlayer charge accumulation with vdW-DF-C09 variants performing the best overall.

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

Partitioned exponential methods for coupled multiphysics systems

Multiphysics problems involving two or more coupled physical phenomena are ubiquitous in science and engineering. This work develops a new partitioned exponential approach for the time integration of multiphysics problems. After a possible semi-discretization in space, the class of problems under consideration is modeled by a system of ordinary differential equations where the right-hand side is a summation of two component functions, each corresponding to a given set of physical processes. The partitioned-exponential methods proposed herein evolve each component of the system via an exponential integrator, and information between partitions is exchanged via coupling terms. Here, the traditional approach to constructing exponential methods, based on the variation-of-constants formula, is not directly applicable to partitioned systems. Rather, our approach to developing new partitioned-exponential families is based on a general-structure additive formulation of the schemes. Two method formulations are considered, one based on a linear-nonlinear splitting of the right hand component functions, and another based on approximate Jacobians. The paper develops classical (non-stiff) order conditions theory for partitioned exponential schemes based on particular families of T-trees and B-series theory. Several practical methods of third order are constructed that extend the Rosenbrock-type and EPIRK families of exponential integrators. Several implementation optimizations specific to the application of these methods to reaction-diffusion systems are also discussed. Numerical experiments reveal that the new partitioned-exponential methods can perform better than traditional unpartitioned exponential methods on some problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery

Passive permeation of cellular membranes is a key feature of many therapeutics. The relevance of passive permeability spans all biological systems as they all employ biomembranes for compartmentalization. A variety of computational techniques are currently utilized and under active development to facilitate the characterization of passive permeability. These methods include lipophilicity relations, molecular dynamics simulations, and machine learning, which vary in accuracy, complexity, and computational cost. This review briefly introduces the underlying theories, such as the prominent inhomogeneous solubility diffusion model, and covers a number of recent applications. Various machine-learning applications, which have demonstrated good potential for high-volume, data-driven permeability predictions, are also discussed. Due to the confluence of novel computational methods and next-generation exascale computers, we anticipate an exciting future for computationally driven permeability predictions.

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

Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study

Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).

42 ENGINEERING↗
DOE OSTI2024

Band Heater Heat Flux Characterization Using Inverse Heat Conduction Problem Models

Abstract An experimental apparatus was constructed to correlate water flowrate and temperature rise under an external band heater. Due to the physical characteristics of the band heater, its transient heating behavior is unknown. This paper investigates the application of inverse heat conduction problem (IHCP) methods to characterize the heat flux from the band heater. Three experiments with different heating times (5, 10, and 20 s) and no flowrate were conducted to measure the transient temperature under the 400 W band heater. Type-T thermocouples measure surface temperature at the centerline of the band heater. The experimental results are computed with five different heat conduction models. The models are chosen to identify how the heat flux response varies from a simplified to a realistic model. Additionally, the results of the experimental heat flux are compared to the manufacturer band heater data (58.9 kW/m2) for each model. The minimum time needed for the heater to fully energize the system is from 10 to 12 s. The residuals for each model are analyzed and used to evaluate the appropriateness of the five different models. The results show that the use of simpler models can achieve results similar to those of complex models, with less time and computational cost.

Engineering↗
DOE OSTI2022

Equivalent Fundamental-Mode Source Simulations for Spherical Uranium and Plutonium Systems

It is important in neutron noise measurements and reactor startup to understand how the source distribution in a system compares to the equivalent fundamental-mode (EFM) source. Deviation from the fundamental mode source distribution increases as the system $\kappa$ eff increases. A correction factor, g *, is a measure of this deviation, and is the focus of this work. Two methods were utilized to simulate g *. These methods are compared to each other and (where applicable) previous results. The effects associated with nuclear material inner radius, materials of reflectors, and reflector thickness are also investigated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗