Search NASA⌕ Search

SEARCH · Search NASA

Results for “state evolution”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Monte Carlo simulation to study the effect of molecular spin state on the spatio-temporal evolution of equilibrium magnetic properties of magnetic tunnel junction based molecular spintronics devices

With a variable spin state, paramagnetic molecules can affect the impact of magnetic exchange coupling strength between two ferromagnetic electrodes. Our magnetic tunnel junction based molecular spintronics devices (MTJMSD) were successful in connecting paramagnetic single molecular magnet (SMM) between two ferromagnetic electrodes. Isolated SMM exhibited a wide range of spin states. However, it was extremely challenging to identify the SMM spin state when connected to the ferromagnetic electrodes. Our prior experimental and Monte Carlo Simulations (MCS) studies showed that paramagnetic molecules produced unprecedented strong antiferromagnetic coupling between two ferromagnets at room temperature. The overall antiferromagnetic coupling occurred when a paramagnetic SMM made antiferromagnetic coupling to the first electrode and ferromagnetic coupling to the second ferromagnetic electrode. This paper studies the impact of variable molecular spin states of the SMMs, producing strong antiferromagnetic coupling between the ferromagnetic electrodes of MTJMSD. The MTJMSD used in this study was represented by an 11 x 50 x 50 Ising model, with 11 being the thickness of the MTJMSD and 5 x 10 x 50 being each electrode’s size. We employed a continuous MCS algorithm to investigate SMM’s spin state’s impact as a function of molecular exchange coupling strength and thermal energy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗
DOE OSTI2022

Laser-induced-fluorescence imaging of a spin-polarized ultracold neutral plasma in a magnetic field

In this work, we report Doppler-sensitive laser-induced-fluorescence (LIF) imaging of an ultracold neutral plasma in a magnetic field. Local values of ion density, hydrodynamic fluid velocity, temperature, and spin polarization are obtained using a fluorescence model based on velocity-resolved rate equations (REs) including the transfer of ions between states due to laser coupling and spontaneous emission. The RE approach captures optical pumping of ions into states that are not driven by the LIF excitation laser, and this is validated with experimental data. Combined molecular-dynamics and quantum-trajectories simulations verify that velocity-changing collisions have a negligible impact on the state population evolution for typical experimental conditions. Relative intensities of Zeeman components of the LIF spectra provide clear evidence that the ions are electron-spin-polarized when created by photoionization of magnetically trapped 88 Sr atoms. This probe opens many possibilities for studying thermal transport and the equilibration of neutral plasmas in overlapping regimes of strong coupling and magnetization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Probing nuclear structure with mean transverse momentum in relativistic isobar collisions

Transverse momentum (p⊥) generation in relativistic heavy-ion collisions is sensitive to the initial geometry and the final-state bulk evolution. We demonstrate with hydrodynamic calculations that the mean p⊥ ratio (R $\langle p⊥ \rangle$ ) between the highly similar isobar $^{96}_{44}$RU + $^{96}_{44}$RU and $^{96}_{44}$Zr + $^{96}_{44}$Zr collisions is insensitive to the bulk evolution and remains sensitive to the small difference in the initial nuclear structure (neutron skin and deformation) between the Ru and Zr nuclei. Here, we further find that nuclear deformation can produce an anticorrelation between R $\langle p⊥ \rangle$ and eccentricity (or elliptic flow) in central collisions. These findings suggest that the R $\langle p⊥ \rangle$ between the isobar systems can be used to measure the neutron skin thickness and deformation parameters, which can, in turn, constrain the nuclear symmetry energy slope parameter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

The iron spin transition of deep nitrogen-bearing mineral Fe3N1.2 at high pressure

Abstract Nitrogen is an essential element for life, one of the most abundant volatiles in the atmosphere, and an important component in the Earth’s interior, where iron nitride is an essential host of deep nitrogen. Here, we investigate the pressure-induced electronic spin-pairing transition of iron in siderazot (Fe3N1.2) at pressures up to 45.8 GPa at room temperature, using diamond-anvil cell techniques coupled with synchrotron X-ray emission spectroscopy. The integrated intensity of the satellite emission peak (K′β) decreases upon compression but remains unchanged at pressures greater than 30.5 GPa. In other words, the high-spin to low-spin transition of iron in Fe3N1.2 starts immediately at very low pressures and completes at ~30.5 GPa. The iron spin transition completion pressures increase with the nitrogen concentration of hexagonal close-packed iron nitrides (i.e., Fe3N1.2, Fe7N3, and Fe2N). Moreover, the identity and concentration of light elements in binary iron-rich compounds such as Fe3N, Fe3C, Fe3P, Fe3S, Fe7C3, and Fe7N3, together with their crystal structure, could affect the iron spin transition pressures. The spin transition of iron-rich alloys could alter the bonding nature and the physical properties, including the thermal and electrical conductivity, thereby influencing the thermal state and evolution of planetary interiors.

Geochemistry & Geophysics↗
DOE OSTI2024

2023 IEDO Peer Review Report

On behalf of the U.S. Department of Energy (DOE) Industrial Efficiency and Decarbonization Office (IEDO), we are pleased to share the report from our 2023 peer review. Peer review provides us with invaluable insight into our office strategy and program direction from a diverse group of external thought leaders. The findings and actionable recommendations from peer review inform our decision making and help us maintain a constant state of evolution and growth.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Comparison Study of Conventional and Adaptive Mesh Refinement in Organic Material Decomposition Models

This study compares conventional mesh refinement techniques, specifically Uniform Mesh Refinement (UMR), with a new Adaptive Mesh Refinement (AMR) method, applied to Organic Material Decomposition (OMD) models. The proposed benefit of AMR is that only areas that require refinement, based on minimizing a specific field gradient, are refined thus decreasing model wall time compared to conventional UMR methods. This work specifically focuses on comparing UMR and AMR methods on decomposing (both No-Flow and Porous-Flow material models) Polymeric Methylene Diisocyanate (PMDI) polyurethane foam. Throughout the work, the geometry increased in complexity to assess the refinement methods performance at varying levels geometric intricacy. While AMR has been shown to work well in a variety of applications, the UMR approach proved to be computationally faster, for many of the geometries and foam decomposition models, than AMR. However, it was observed that at higher levels of refinement, greater than 3 UMR, AMR begins to be computationally better. Additionally, the settings used to perform AMR greatly impact its performance, and lessons learned, in terms of OMD models, are shared. Due to physics involved in material decomposition, specifically the evolution of state variables, these problems don’t fully benefit from the advantages of AMR.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Correlations between azimuthal anisotropy and mean transverse momentum in pp, pPb, and peripheral PbPb collisions

Correlations between azimuthal anisotropy and mean transverse momentum of charged particles in proton-proton (pp), proton-lead (pPb), and peripheral lead-lead (PbPb) collisions are presented as a function of charged particle multiplicity. The pp, pPb and PbPb collision data were collected using the CMS detector at the LHC with a center-of-mass energy per nucleon pair of 13, 8.16 and 5.02 TeV, respectively. The two- and four-particle cumulants for the second- and third-order Fourier anisotropy harmonics are correlated with the mean transverse momentum of charged particles on an event-by-event basis. In pp and pPb systems, the observed correlation coefficients based on two-particle cumulants are found to change from negative to positive values as the charged particle multiplicity decreases. The sign changes disappear when the correlated particles are required to be further apart in pseudorapidity. Additionally, no sign changes in correlation coefficients are observed when employing four-particle cumulants. Models incorporating initial-state gluon saturation and final-state hydrodynamic evolutions are compared to pPb data and the predicted sign changes are not observed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Spin-selective evolution of the Zhang-Rice state in binary transition metal oxide MnO(001) film

Here, the Zhang-Rice (ZR) state is a strongly hybridized bound state formed by transition-metal and oxygen atoms. The spin fluctuations within the ZR state are known to play an important role in high-T c superconductivity in cuprates. Here, we employ a combination of angle-resolved photoemission spectroscopy (ARPES), x-ray photoemission spectroscopy (XPS), and ab initio embedded dynamical mean-field theory (eDMFT) to investigate the influence of magnetic ordering on the spectral characteristics of the valence band and Mn 2⁢p core-level in MnO (001) ultrathin films. Our results demonstrate that a complex spin-selective evolution of Mn 3⁢d-O2⁢p hybridization develops due to the long-range antiferromagnetic (AFM) ordering. This hybridization significantly alters the spectral shape and weight of the ZR state. Specifically, in the AFM phase, we observed the sharpening of the ZR state and band folding with the periodicity of the AFM unit cell of MnO(001). We also demonstrated a strong connection between the spectral evolution of the ZR state and the non-local screening channels of the photoexcited core holes. Further, our detailed temperature-dependent study reveals the presence of short-range antiferromagnetic correlations that exist at much higher temperatures than Neel temperature (T N ) and shows the evolution of the ZR state across the magnetic transitions and its implication to the core-hole screening in 3⁢d binary transition metal oxides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Collective neural network behavior in a dynamically driven disordered system of superconducting loops

Collective properties of complex systems composed of many interacting components such as neurons in our brain can be modeled by artificial networks based on disordered systems. We show that a disordered neural network of superconducting loops with Josephson junctions can exhibit computational properties like categorization and associative memory in the time evolution of its state in response to information from external excitations. Superconducting loops can trap multiples of fluxons in many discrete memory configurations defined by the local free energy minima in the configuration space of all possible states. A memory state can be updated by exciting the Josephson junctions to fire or allow the movement of fluxons through the network as the current through them surpasses their critical current thresholds. Simulations performed with a lumped element circuit model of a 4-loop network show that information written through excitations is translated into stable states of trapped flux and their time evolution. Experimental implementation on a high-Tc superconductor YBCO-based 4-loop network shows dynamically stable flux flow in each pathway characterized by the correlations between junction firing statistics. Neural network behavior is observed as energy barriers separating state categories in simulations in response to multiple excitations, and experimentally as junction responses characterizing different flux flow patterns in the network. The state categories that produce these patterns have different temporal stabilities relative to each other and the excitations. This provides strong evidence for time-dependent (short-to-long-term) memories, that are dependent on the geometrical and junction parameters of the loops, as described with a network model.

Josephson junctions↗
DOE OSTI2024

Stress interference in multilayer additive friction stir deposition of AA6061 aluminum

Due to the multilayer deposition nature of metal additive manufacturing processes, each layer being printed experiences the state of thermokinetic and thermomechanical stress that in turn interfere with the state of thermokinetics and thermomechanical stress of subsequently deposited layers. Especially, this multilayer interference significantly affects the resultant properties of the component fabricated using solid-state additive friction stir deposition due to evolution of asymmetric state of planar stress. Due to the lack of comprehensive and suitable in situ diagnosis technique, the complex interference of inter- and multi-layer stresses during additive friction stir deposition was studied in an integrated approach of numerical simulation of fluidic state and experimental probing of stress influenced ultrasonic elastography. The uni-directional and bi-directional layer deposition configurations adopted during additive friction stir deposition result in the generation of constructive and destructive interference of the interlayer stress and hence, asymmetric and symmetric dynamic elasticity distribution respectively within the subsequent layers. With subsequent deposition of additional layers, the odd and even numbers of deposited layers generate asymmetric and nearly symmetric dynamic elasticity distributions.

Yang, Teng↗
DOE OSTI2025

The classical equations of motion of quantized gauge theories, Part 2: Electromagnetism

In this and companion papers, we show that quantum field theories with gauge symmetries permit a broader class of classical dynamics than typically assumed. In this article, we show that the quantization of electromagnetism permits the existence of classical electric field states that do not obey Gauss’s law. These states are gauge invariant and their time evolution can be consistently described using the Schrödinger equation. The time evolution of these states is such that at the classical level, the full set of Maxwell’s equations would appear to hold, with the physical effects of these states being attributable to an auxiliary, static “shadow” charge density with no internal degrees of freedom. This density could affect the dynamics of charged particles in our universe and it may thus be of observational interest.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Hybrid quantum-classical approach for coupled-cluster Green's function theory

The three key elements of a quantum simulation are state preparation, time evolution, and measurement. While the complexity scaling of time evolution and measurements are well known, many state preparation methods are strongly system-dependent and require prior knowledge of the system's eigenvalue spectrum. Here, we report on a quantum-classical implementation of the coupled-cluster Green's function (CCGF) method, which replaces explicit ground state preparation with the task of applying unitary operators to a simple product state. While our approach is broadly applicable to many models, we demonstrate it here for the Anderson impurity model (AIM). The method requires a number of T gates that grows as O ( N 5 ) per time step to calculate the impurity Green's function in the time domain, where N is the total number of energy levels in the AIM. Since the number of T gates is analogous to the computational time complexity of a classical simulation, we achieve an order of magnitude improvement over a classical CCGF calculation of the same order, which requires O ( N 6 ) computational resources per time step.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

In Situ Characterization of Interface Evolution in Argyrodite‐Based All‐Solid‐State Li Batteries

Interfacial stability is one of the critical challenges in all-solid-state Li metal batteries. Multiple processes such as solid electrolyte (SE) decomposition and lithium dendrite growth take place at the solid interfaces during cycling, leading to the overall cell failure. To deconvolute these complex processes, in situ characterization is of paramount importance to elucidate the interfacial evolution on the SE upon Li plating/stripping. Herein, an all-solid-state asymmetric in situ cell is developed that allows the direct visualization of the highly localized Li plating/stripping processes under the optical microscope. Moreover, this cell configuration enables reliable post-mortem chemical and morphological analysis of the intact SE/Li interface. Using combined scanning electron microscopy and energy-dispersive X-ray spectroscopy, the study reveals that the evolution of the Li argyrodite interface is strongly influenced by the current density, particularly in terms of chemical distribution and Li plating morphology. More specifically, the solid interface is LiCl-rich with the formation of Li cubes at low current densities, while high currents result in more uniform elemental distribution and filament morphology. These findings elucidate the dynamic evolution mechanism at solid interfaces and offer valuable guidance for developing stable solid interfaces in all-solid-state Li metal batteries.

Huang, Di↗
DOE OSTI2025

Cheaper and more noise-resilient quantum state preparation using eigenvector continuation

Subspace methods are powerful, noise-resilient methods that can effectively prepare ground states on quantum computers. The challenge is to get a subspace with a small condition number that spans the states of interest using minimal quantum resources. In this work, we will use eigenvector continuation to build a subspace from the low-lying states of a set of Hamiltonians. The basis vectors are prepared using truncated versions of standard state preparation methods such as imaginary-time evolution (ITE), adiabatic state preparation (ASP), and variational quantum eigensolver. By using these truncated methods combined with eigenvector continuation, we can directly improve upon them, obtaining more accurate ground-state energies at a reduced cost. We use several spin systems to demonstrate convergence even when methods like ITE and ASP fail, such as ASP in the presence of level crossings and ITE with vanishing energy gaps. We also showcase the noise resilience of this approach beyond the gains already made by having shallower quantum circuits. Furthermore, our findings suggest that eigenvector continuation can be used to improve existing state preparation methods in the near term.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗