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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Illuminating early-stage dynamics of heavy-ion collisions through photons at RHIC BES energies

Heavy-ion collisions at $\sqrt {^SNN}$~10 GeV probe the QCD phase diagram at large baryon densities. Because the longitudinal Lorentz contraction is small at these collision energies, understanding the dynamics during the early phase of the collision is essential for the subsequent modeling of the system evolution and for constraining the QGP transport properties at finite baryon densities. Direct photons provide undistorted information on early-stage dynamics. We model relativistic heavy-ion collisions at RHIC Beam Energy Scan energies with a hybrid dynamical approach consisting of a 3D-Glauber initial state followed by viscous hydrodynamics and hadronic transport (MUSIC + UrQMD). The implemented thermal photon emission takes into account the enhancement from finite baryon chemical potentials. We show that direct photon spectra and their anisotropic flow coefficients have a strong sensitivity to the early stage of heavy-ion collisions. Thus, they provide constraints on QGP dynamics complementary to those obtained from hadronic observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Optimal polynomial based quantum eigenstate filtering with application to solving quantum linear systems

We present a quantum eigenstate filtering algorithm based on quantum signal processing (QSP) and minimax polynomials. The algorithm allows us to efficiently prepare a target eigenstate of a given Hamiltonian, if we have access to an initial state with non-trivial overlap with the target eigenstate and have a reasonable lower bound for the spectral gap. We apply this algorithm to the quantum linear system problem (QLSP), and present two algorithms based on quantum adiabatic computing (AQC) and quantum Zeno effect respectively. Both algorithms prepare the final solution as a pure state, and achieves the near optimal $\mathcal{\tilde{O}}$(dκlog(1/ϵ)) query complexity for a d -sparse matrix, where κ is the condition number, and ϵ is the desired precision. Neither algorithm uses phase estimation or amplitude amplification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Noise-resistant Landau-Zener sweeps from geometrical curves

Landau-Zener physics is often exploited to generate quantum logic gates and to perform state initialization and readout. The quality of these operations can be degraded by noise fluctuations in the energy gap at the avoided crossing. We leverage a recently discovered correspondence between qubit evolution and space curves in three dimensions to design noise-robust Landau-Zener sweeps through an avoided crossing. In the case where the avoided crossing is purely noise-induced, we prove that operations based on monotonic sweeps cannot be robust to noise. Hence, we design families of phase gates based on non-monotonic drives that are error-robust up to second order. In the general case where there is an avoided crossing even in the absence of noise, we present a general technique for designing robust driving protocols that takes advantage of a relationship between the Landau-Zener problem and space curves of constant torsion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Sample-efficient verification of continuously-parameterized quantum gates for small quantum processors

Most near-term quantum information processing devices will not be capable of implementing quantum error correction and the associated logical quantum gate set. Instead, quantum circuits will be implemented directly using the physical native gate set of the device. These native gates often have a parameterization (e.g., rotation angles) which provide the ability to perform a continuous range of operations. Verification of the correct operation of these gates across the allowable range of parameters is important for gaining confidence in the reliability of these devices. In this work, we demonstrate a procedure for sample-efficient verification of continuously-parameterized quantum gates for small quantum processors of up to approximately 10 qubits. This procedure involves generating random sequences of randomly-parameterized layers of gates chosen from the native gate set of the device, and then stochastically compiling an approximate inverse to this sequence such that executing the full sequence on the device should leave the system near its initial state. We show that fidelity estimates made via this technique have a lower variance than fidelity estimates made via cross-entropy benchmarking. This provides an experimentally-relevant advantage in sample efficiency when estimating the fidelity loss to some desired precision. We describe the experimental realization of this technique using continuously-parameterized quantum gate sets on a trapped-ion quantum processor from Sandia QSCOUT and a superconducting quantum processor from IBM Q, and we demonstrate the sample efficiency advantage of this technique both numerically and experimentally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Simultaneous estimation of multiple eigenvalues with short-depth quantum circuit on early fault-tolerant quantum computers

We introduce a multi-modal, multi-level quantum complex exponential least squares (MM-QCELS) method to simultaneously estimate multiple eigenvalues of a quantum Hamiltonian on early fault-tolerant quantum computers. Our theoretical analysis demonstrates that the algorithm exhibits Heisenberg-limited scaling in terms of circuit depth and total cost. Notably, the proposed quantum circuit utilizes just one ancilla qubit, and with appropriate initial state conditions, it achieves significantly shorter circuit depths compared to circuits based on quantum phase estimation (QPE). Numerical results suggest that compared to QPE, the circuit depth can be reduced by around two orders of magnitude under several settings for estimating ground-state and excited-state energies of certain quantum systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantum Multiple Eigenvalue Gaussian filtered Search: an efficient and versatile quantum phase estimation method

Quantum phase estimation is one of the most powerful quantum primitives. This work proposes a new approach for the problem of multiple eigenvalue estimation: Quantum Multiple Eigenvalue Gaussian filtered Search (QMEGS). QMEGS leverages the Hadamard test circuit structure and only requires simple classical postprocessing. QMEGS is the first algorithm to simultaneously satisfy the following two properties: (1) It can achieve the Heisenberg-limited scaling without relying on any spectral gap assumption. (2) With a positive energy gap and additional assumptions on the initial state, QMEGS can estimate all dominant eigenvalues to ϵ accuracy utilizing a significantly reduced circuit depth compared to the standard quantum phase estimation algorithm. In the most favorable scenario, the maximal runtime can be reduced to as low as log(1/ϵ). This implies that QMEGS serves as an efficient and versatile approach, achieving the best-known results for both gapped and gapless systems. Numerical results validate the efficiency of our proposed algorithm in various regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Nonlinear Optimal Control of Electron Dynamics Within Hartree-Fock Theory

Consider the problem of determining the optimal applied electric field to drive a molecule from an initial state to a desired target state. For even moderately sized molecules, solving this problem directly using the exact equations of motion—the time-dependent Schrödinger equation (TDSE)—is numerically intractable. Here, we present a solution of this problem within time-dependent Hartree-Fock (TDHF) theory, a mean field approximation of the TDSE. Optimality is defined in terms of minimizing the total control effort while maximizing the overlap between desired and achieved target states. We frame this problem as an optimization problem constrained by the nonlinear TDHF equations; we solve it using trust region optimization with gradients computed via a custom-built adjoint state method. For three molecular systems, we show that with very small neural network parametrizations of the control, our method yields solutions that achieve desired targets within acceptable constraints and tolerances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

N2-to-NH3 conversion by excess electrons trapped in point vacancies on 5f-element dioxide surfaces

Ammonia (NH 3 ) is one of the basic chemicals in artificial fertilizers and a promising carbon-free energy storage carrier. Its industrial synthesis is typically realized via the Haber−Bosch process using traditional iron-based catalysts. Developing advanced catalysts that can reduce the N 2 activation barrier and make NH 3 synthesis more efficient is a long-term goal in the field. Most heterogeneous catalysts for N 2 -to-NH 3 conversion are multicomponent systems with singly dispersed metal clusters on supporting materials to activate N 2 and H 2 molecules. Herein, we report single-component heterogeneous catalysts based on 5 f actinide dioxide surfaces (ThO 2 and UO 2 ) with oxygen vacancies for N 2 -to-NH 3 conversion. The reaction cycle we propose is enabled by a dual-site mechanism, where N 2 and H 2 can be activated at different vacancy sites on the same surface; NH 3 is subsequently formed by H − migration on the surface via associative pathways. Oxygen vacancies recover to their initial states after the release of two molecules of NH 3 , making it possible for the catalytic cycle to continue. Our work demonstrates the catalytic activities of oxygen vacancies on 5 f actinide dioxide surfaces for N 2 activation, which may inspire the search for highly efficient, single-component catalysts that are easy to synthesize and control for NH 3 conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The saturation mechanism of thermal instability

The literature on thermal instability (TI) reveals that even for a simple homogeneous plasma, the nonlinear outcome ranges from a gentle reconfiguration of the initial state to an explosive one, depending on whether the condensations that form evolve in an isobaric or nonisobaric manner. After summarizing the recent developments on the linear and nonlinear theory of TI, here we derive several general identities from the evolution equation for entropy that reveal the mechanism by which TI saturates; whenever the boundary of the instability region (the Balbus contour) is crossed, a dynamical change is triggered that causes the comoving time derivative of the pressure to change the sign. This event implies that the gas pressure force reverses direction, slowing the continued growth of condensation. For isobaric evolution, this “pressure reversal” occurs nearly simultaneously for every fluid element in condensation and a steady state is quickly reached. For nonisobaric evolution, the condensation is no longer in mechanical equilibrium and the contracting gas rebounds with greater force during the expansion phase that accompanies the gas reaching the equilibrium curve. The cloud then pulsates because the return to mechanical equilibrium becomes wave mediated. We show that both the contraction rebound event and subsequent pulsation behavior follow analytically from an analysis of the new identities. Our analysis also leads to the identification of an isochoric TI zone and makes it clear that unless this zone intersects the equilibrium curve, isochoric modes can only become unstable if the plasma is in a state of thermal non-equilibrium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Impact of Surficial Biochar Treatment on Acute H2S Emissions during Swine Manure Agitation before Pump-Out: Proof-of-the-Concept

Acute releases of hydrogen sulfide (H2S) are of serious concern in agriculture, especially when farmers agitate manure to empty storage pits before land application. Agitation can cause the release of dangerously high H2S concentrations, resulting in human and animal fatalities. To date, there is no proven technology to mitigate these short-term releases of toxic gas from manure. In our previous research, we have shown that biochar, a highly porous carbonaceous material, can float on manure and mitigate gaseous emissions over extended periods (days–weeks). In this research, we aim to test the hypothesis that biochar can mitigate H2S emissions over short periods (minutes–hours) during and shortly after manure agitation. The objective was to conduct proof-of-the-concept experiments simulating the treatment of agitated manure. Two biochars, highly alkaline and porous (HAP, pH 9.2) made from corn stover and red oak (RO, pH 7.5), were tested. Three scenarios (setups): Control (no biochar), 6 mm, and 12 mm thick layers of biochar were surficially-applied to the manure. Each setup experienced 3 min of manure agitation. Real-time concentrations of H2S were measured immediately before, during, and after agitation until the concentration returned to the initial state. The results were compared with those of the Control using the following three metrics: (1) the maximum (peak) flux, (2) total emission from the start of agitation until the concentration stabilized, and (3) the total emission during the 3 min of agitation. The Gompertz’s model for determination of the cumulative H2S emission kinetics was developed. Here, 12 mm HAP biochar treatment reduced the peak (1) by 42.5% (p = 0.125), reduced overall total emission (2) by 17.9% (p = 0.290), and significantly reduced the total emission during 3 min agitation (3) by 70.4%. Further, 6 mm HAP treatment reduced the peak (1) by 60.6%, and significantly reduced overall (2) and 3 min agitation’s (3) total emission by 64.4% and 66.6%, respectively. Moreover, 12 mm RO biochar treatment reduced the peak (1) by 23.6%, and significantly reduced overall (2) and 3 min total (3) emission by 39.3% and 62.4%, respectively. Finally, 6 mm RO treatment significantly reduced the peak (1) by 63%, overall total emission (2) by 84.7%, and total emission during 3 min agitation (3) by 67.4%. Biochar treatments have the potential to reduce the risk of inhalation exposure to H2S. Both 6 and 12 mm biochar treatments reduced the peak H2S concentrations below the General Industrial Peak Limit (OSHA PEL, 50 ppm). The 6 mm biochar treatments reduced the H2S concentrations below the General Industry Ceiling Limit (OSHA PEL, 20 ppm). Research scaling up to larger manure volumes and longer agitation is warranted.

Chen, Baitong (ORCID:0000000266071253)↗
DOE OSTI2025

Strong Local Passivity in Unconventional Scenarios: A New Protocol for Amplified Quantum Energy Teleportation

Quantum energy teleportation (QET) has been proposed to overcome the restrictions of strong local passivity (SLP) and to facilitate energy transfer in quantum systems. Traditionally, QET has only been considered under strict constraints, including the requirements that the initial state be the ground state of an interacting Hamiltonian, that Alice’s measurement commute with the interaction terms, and that entanglement be present. These constraints have significantly limited the broader applicability of QET protocols. In this work, we demonstrate that SLP can arise beyond these conventional constraints, establishing the necessity of QET in a wider range of scenarios for local energy extraction. This leads to a more flexible and generalized framework for QET. Furthermore, we introduce the concept of a “local effective Hamiltonian,” which eliminates the need for optimization techniques in determining Bob’s optimal energy extraction in QET protocols. As an additional advantage, the amount of energy that can be extracted using our new protocol is amplified to be 7.2 times higher than that of the original protocol. These advancements enhance our understanding of QET and extend its broader applications to quantum technologies. To support our findings, we implement the protocol on quantum hardware, confirming its theoretical validity and experimental feasibility.

amplified energy extraction↗
DOE OSTI2023

Understanding of Active Sites and Interconversion of Pd and PdO during CH 4 Oxidation

Pd-based catalysts are widely used in the oxidation of CH 4 and have a significant impact on global warming. However, understanding their active sites remains controversial, because interconversion between Pd and PdO occurs consecutively during the reaction. Understanding the intrinsic active sites under reaction conditions is critical for developing highly active and selective catalysts. In this study, we demonstrated that partially oxidized palladium (PdO x ) on the surface plays an important role for CH 4 oxidation. Regardless of whether the initial state of Pd corresponds to oxides or metallic clusters, the topmost surface is PdO x , which is formed during CH4 oxidation. A quantitative analysis using CO titration, diffuse reflectance infrared Fourier-transform spectroscopy, X-ray diffraction, and scanning transmission electron microscopy demonstrated that a surface PdO layer was formed on top of the metallic Pd clusters during the CH 4 oxidation reaction. Furthermore, the time-on-stream test of CH 4 oxidation revealed that the presence of the PdO layer on top of the metallic Pd clusters improves the catalytic activity. Our periodic density functional theory (DFT) calculations with a PdO x slab and nanoparticle models aided the elucidation of the structure of the experimental PdO particles, as well as the experimental C-O bands. The DFT results also revealed the formation of a PdO layer on the metallic Pd clusters. This study helps achieve a fundamental understanding of the active sites of Pd and PdO for CH 4 oxidation and provides insights into the development of active and durable Pd-based catalysts through molecular-level design.

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

Color Transparency and Light-Front Holographic QCD

Color transparency, the reduction of initial-state or final-state interactions in coherent nuclear processes, is a natural prediction of QCD (quantum chromodynamics) provided that small-sized or point-like configurations (PLCs) are formed in high-momentum transfer, high-energy, semi-exclusive processes. I use the Frankfurt-Miller-Strikman criteria for the existence of PLCs to show that the wave functions of light-front holographic QCD, as currently formulated, do not contain a PLC.

Miller, Gerald A. (ORCID:0000000324433639)↗
DOE OSTI2026

The Effects of Realistic Impact-processed Asteroid Topology on Atmospheric Airbursts

When small asteroids (∼10–200 m) enter Earth’s atmosphere they can break up before hitting the ground, releasing a considerable amount of energy in what is known as an atmospheric airburst. To date, numerous studies have examined how an asteroid’s strength, size, shape, and entry characteristics affect the breakup process; but few have assessed the effects of heterogenous internal topologies. We present a two-step high-fidelity simulation approach, which we use to model the atmospheric breakup of asteroids with realistic impact-processed internal topologies and their associated ground effects. In the first step, we model the asteroid as it is impacted to generate an “impact-processed” topology. We then map the resulting fractures (i.e., damage field) from that simulation to the initial state of an atmospheric breakup simulation. For both phases, we use the smoothed particle hydrodynamics code Spheral++. As a demonstrative example, we apply our new simulation pipeline to a Tunguska-scale impactor (50 m diameter, 20 km s −1 entry velocity, and 45° angle) in a case study comparing impact-processed and fully intact asteroids in both planar 2D and full 3D. For sufficiently strong asteroids, we find that impact processing generally causes the asteroid to break up at higher altitudes. We also observe that impact-processed asteroids break up into smaller fragments than objects with equivalent properties that have not been impact-processed.

Astronomy and AstroPhysics↗
DOE OSTI2020

ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century

Abstract. Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between −6.1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change

Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.

Burghardt, Jeffrey A.↗