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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A mathematical model of solid-state dewetting of barium thin films on W (112)

Solid state dewetting occurs when a thin solid film is heated. The temperature of dewetting depends on the thickness of the film; dewetting can be observed in the range of 1/3 to 1/2 of the bulk melting temperature. While remaining solid, the film behaves in a manner similar to liquids dewetting and agglomerating to forming islands or droplets. One of the possible mechanisms is the conversion of a metastable thin film geometry into a more stable form. Heating the metastable film gives the film atoms higher mobility, and the films retract, dewetting the surface. This atomic motion can be restricted due to surface anisotropy. Herein we present in situ emission microscopy observations of barium thin films deposited onto W (112) by thermal evaporation. From the modeling viewpoint, the evolution of the film in this system could be divided in four stages: (i) the nucleation and growth of the thin film as a simply connected region; (ii) formation of droplets/islands/hillocks; (iii) nucleation of holes; (iv) evolution of the components of the disconnected film to their equilibrium state. We present a continuum model that is qualitatively consistent with the evolution of the film observed at the initial stage of the experiment and discuss the later stages of the evolution of surface structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of a neural network model for peeling–ballooning stability analysis in the KSTAR tokamak pedestals

The neural network model, MISHKA-NN is developed to mitigate the computational burden associated with the linear ideal magnetohydrodynamic (MHD) stability analysis of the pedestal based on the peeling–ballooning (P–B) model. By utilizing both 1D plasma profiles (current density, pressure gradient, and safety factor) and 0D parameters (plasma geometry, total current, and toroidal mode number), the model predicts linear growth rate of edge-localized ideal MHD instability in a given equilibrium state. By enabling the prediction of each instability within a second, the model reduces the time required for plotting a pedestal P–B stability diagram (j - α diagram) from approximately 100 CPU hours to a few CPU minutes. Notably, even with the utilization of parametric pressure and current profiles and plasma boundary shapes for the training dataset, the model shows a satisfactory level of performance in benchmarking the j - α diagram for the reconstructed equilibrium from a KSTAR tokamak experiment. We anticipate the model to serve as a versatile alternative to 2D linear MHD stability codes, alleviating numerical costs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Matrix Approach to Accelerate Spin-Up of CLM5

Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin-up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi-Analytical Spin-Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin-up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up on site and globally in comparison with other spin-up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Reduced-order modeling for efficient cross section library development in high-temperature gas reactor pebble-bed depletion analysis

Accurate modeling of running-in and equilibrium conditions in pebble-bed reactors (PBRs) requires precise microscopic multigroup neutron cross sections. In Griffin, deterministic neutronics calculations rely on multivariate interpolation over large cross section libraries, resulting in significant memory usage and performance bottlenecks. This work, together with a companion paper on Griffin integration, explores reduced-order models (ROMs) to replace interpolation with lightweight surrogates. Several ROM techniques are benchmarked, with deep neural networks (DNNs) demonstrating superior memory efficiency, scalability, and predictive accuracy. A total of 295 DNNs were trained to build a comprehensive isotope library, integrated into Griffin through a custom LibTorch interface for depletion analysis. Initial results demonstrate that DNN-based ROMs drastically reduce memory demands while preserving accuracy, enabling finer tabulations and additional state variables without overhead. In conclusion, the framework also supports online cross section generation and real-time DNN updates through transfer learning, improving fidelity by capturing self-shielding and evolving nuclide compositions during burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Nonlinear growth of magnetic islands by passing fast ions in NSTX

The growth of magnetic islands in NSTX is modeled successfully, with the consideration of passing fast ions. It is shown that a good quantitative agreement between simulation and experimental measurement can be achieved when the uncompensated cross-field current induced by passing fast ions is included in the island growth model. The fast ion parameters, along with other equilibrium parameters, are obtained self-consistently using the TRANSP code with the assumptions of the 'kick' model (Podestà et al 2017 Plasma Phys. Control. Fusion 59 095008). Overall, the results show that fast ions can contribute to overcoming the stabilizing effect of polarization current for magnetic island growth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Nonlinear growth of magnetic islands by passing fast ions in NSTX

The growth of magnetic islands in NSTX is modeled successfully, with the consideration of passing fast ions. It is shown that a good quantitative agreement between simulation and experimental measurement can be achieved when the uncompensated cross-field current induced by passing fast ions is included in the island growth model. The fast ion parameters, along with other equilibrium parameters, are obtained self-consistently using the TRANSP code with the assumptions of the ‘kick’ model (Podestà et al 2017 Plasma Phys. Control. Fusion 59 095008). The results show that fast ions can contribute to overcoming the stabilizing effect of polarization current for magnetic island growth.

Fast ions↗
DOE OSTI2024

Localization in Energy Materials (Final Project Report)

The last year of this award we have continued our research on using quantum machine learning to identify phase transitions. By combining quantum machine learning with quantum computing, we extended a hybrid classical-quantum algorithm to capture the metal-insulator quantum phase transition of the Hubbard model. We have also continued our studies of non-equilibrium dynamics of interacting disordered systems. In particular, we studied the non-equilibrium transient dynamics of a system described by the Anderson-Hubbard model following an interaction and disorder quench, and the effect of disorder on the out-of-time-order correlator on the Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Zavitsas’ hydration model for electrolytes only stable in the presence of another: NaAl(OH) 4 in aqueous NaOH solution

Many aqueous electrolytes are only stable in the presence of another electrolyte, such as electrolytes that are only soluble in strong acid or base. An example is sodium aluminate [NaAl(OH) 4 ], which is only stable in aqueous NaOH. This complicates developing thermodynamic parameters because it is difficult to separate the contributions of individual electrolytes in multicomponent solutions to measured bulk thermodynamic properties. The present study develops a method to determine the liquid phase parameters from solubility data for Zavitsas’ Hydration model, a model that incorporates hydration parameters into the activities of dissolved species. Furthermore, this study uses gibbsite [Al(OH) 3 ] solubility data in aqueous NaOH solution to develop Zavitsas' model parameters for NaAl(OH) 4 simultaneously with the equilibrium constants. A good fit of the solubility data was found, showing that Zavitsas’ model is effective for this system.

Bayer process↗
DOE OSTI2026

Asymmetric pathways for lithium extraction and recovery based on the two-phase equilibrium of layered oxides

Electrochemical intercalation offers a promising platform for Li + extraction. However, only limited types of electrode materials have been investigated. The challenge to broaden and tailor materials for electrochemical intercalation-based Li + extraction lies in the lack of understanding of material’s response upon co-intercalation of multiple ions, therefore, paired process design to enable reversible Li + extraction and recovery. Here, we showcase the design of asymmetric ion pathways for Li + extraction and recovery for host material with complex Li + and Na + interaction using layered cobalt oxide as a model material. The two-phase equilibrium of Na 0.48 CoO 2 and Li 0.94 CoO 2 governs Li + selectivity when a high depth of intercalation is achieved (low vacancy level). We show that the relative rate between ion exchange and intercalation is critical to determine the ion pathways. The relationship can be quantitatively compared using the average pseudo ion exchange rate (C pseudoIX ) and the intercalation rate (C inter ). The ion pathways at the three regimes with C pseudoIX > C inter , C pseudoIX ~ C inter , and C pseudoIX < C inter are constructed. By selecting the optimized ion pathway and particle size, we demonstrate 9.7×10 4 Li + selectivity with 99% purity Li + recovery from an initial 1:1000 Li: Na molar ratio solution using 115 mAh/g specific capacity.

electrochemistry↗
DOE OSTI2022

Programmable heating and quenching for efficient thermochemical synthesis

Conventional thermochemical syntheses by continuous heating under near-equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways. As an alternative, we present a non-equilibrium, continuous synthesis technique that uses pulsed heating and quenching (for example, 0.02 s on, 1.08 s off) using a programmable electric current to rapidly switch the reaction between high (for example, up to 2,400 K) and low temperatures. The rapid quenching ensures high selectivity and good catalyst stability, as well as lowers the average temperature to reduce the energy cost. Using CH4 pyrolysis as a model reaction, our programmable heating and quenching technique leads to high selectivity to value-added C2 products (>75% versus <35% by the conventional non-catalytic method and versus <60% by most conventional methods using optimized catalysts). Our technique can be extended to a range of thermochemical reactions, such as NH 3 synthesis, for which we achieve a stable and high synthesis rate of about 6,000 μmol g Fe –1 h –1 at ambient pressure for >100 h using a non-optimized catalyst. Furthermore, this study establishes a new model towards highly efficient non-equilibrium thermochemical synthesis.

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

Modelling the nonlinear plasma response to externally applied three-dimensional fields with the Stepped Pressure Equilibrium Code

Small-amplitude, symmetry-breaking magnetic field perturbations, including resonant magnetic perturbations (RMPs) and error fields, can profoundly impact plasma properties in both tokamaks and stellarators. In this work, we perform the first comparison between the Stepped Pressure Equilibrium Code (SPEC) (a comparatively fast and efficient equilibrium code based on energy-minimisation principles) and M3D-C 1 (a high-fidelity albeit computationally expensive initial-value extended-magnetohydro-dynamic (MHD) code) to assess the conditions under which SPEC can be used to model the nonlinear, non-ideal plasma response to an externally applied (m = 2,n = 1) RMP field in an experimentally relevant geometry. We find that SPEC is able to capture the plasma response in the weakly nonlinear regime – meaning perturbation amplitudes below the threshold for break up of the separatrix and onset of secondary magnetic island formation – when around half of the total toroidal flux is enclosed in the volume containing the q = 2 resonant surface. Further, the observed dependence of SPEC solutions on input parameters, including toroidal flux and the number of volumes into which the plasma is partitioned, indicates that additional exploration of the underlying Multi-Region Relaxed MHD physics model is needed to constrain the choice of parameters. Nonetheless, this work suggests promising applications of SPEC to optimisation and fusion plasma design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A Regularized Variance-Reduced Modified Extragradient Method for Stochastic Hierarchical Games

We consider an N -player hierarchical game in which the i th player’s objective comprises of an expectation-valued term, parametrized by rival decisions, and a hierarchical term. Such a framework allows for capturing a broad range of stochastic hierarchical optimization problems, Stackelberg equilibrium problems, and leader-follower games. We develop an iteratively regularized and smoothed variance-reduced modified extragradient framework for iteratively approaching hierarchical equilibria in a stochastic setting. We equip our analysis with rate statements, complexity guarantees, and almost-sure convergence results. We then extend these statements to settings where the lower-level problem is solved inexactly and provide the corresponding rate and complexity statements. Our model framework encompasses many game theoretic equilibrium problems studied in the context of power markets. We present a realistic application to the study of virtual power plants, emphasizing the role of hierarchical decision making and regularization. Preliminary numerics suggest that empirical behavior compares well with theoretical guarantees.

Tikhonov regularization↗
DOE OSTI2024

Reaction path model of the formation of abiotic immiscible hydrocarbon fluids in subducted carbonated serpentinites, Lanzo Massif (Western Italian Alps)

Fluids generated from subducted slabs participate in the cycling of deep carbon in the crust and upper mantle. In these fluids, aqueous carbon species vary in oxidation state between +IV and -IV depending on whether the fluids are oxidizing or reducing, respectively. Most studies of subduction-zone fluids have focused on oxidized carbon species. However, recent studies of natural samples have demonstrated the occurrence of deep, reducing fluids, generated in both subducted oceanic upper mantle and crustal rocks. CH 4 -H 2 -rich fluid inclusions in subducted carbonated serpentinites have demonstrated the existence of abiotic, immiscible, hydrocarbon fluids at upper mantle conditions. To investigate the formation of such immiscible hydrocarbon fluids during the evolution of subducted carbonated serpentinites, we used equilibrium constants from the Deep Earth Water model to carry out predictive chemical mass transfer modeling to simulate the alteration reactions. A novel feature of the models was the inclusion of an immiscible hydrocarbon fluid containing six components (CH 4,f , C 2 H 6,f , C 3 H 8,f , isoC 4 H 10,f , CO 2,f , H 2,f ). This feature enabled prediction of the formation of a separate immiscible fluid in equilibrium with aqueous species and minerals. We developed a predictive reaction path model of invasive H 2,f reacting with carbonated serpentinites and interstitial aqueous fluids for comparison with the natural samples from the Lanzo Massif, western Italian Alps. Over a range of temperatures and pressures, immiscible hydrocarbon fluids formed in association with altered mineral assemblages. Reaction progress caused the transformation of carbonated serpentinites and the formation of clinopyroxene, brucite, graphite, and hydrocarbon fluids, along with changes of pH, logfO 2 , and aqueous species. CH 4,f was the most abundant hydrocarbon species in all the models. The overall results at 2.0 GPa and 400 to 450 °C were consistent with the natural samples from the Lanzo Massif. Interestingly, large amounts of H 2 O formed due to oxidation of H 2 . More hydrocarbons and H 2 O formed in models with lower fluid/rock mass ratios or with more reactant H 2 . Models at different pressure and temperature conditions showed similar results with some variation in the relative stabilities of aragonite, graphite and olivine solid solution, and associated differences in mineral sequences, hydrocarbon fluids, values of aqueous species, and the final log fO 2 and pH. As a result, our models strongly support the laboratory and field evidence that reduction of carbonated serpentinites by infiltrating H 2 fluids can cause the formation of immiscible, abiotic hydrocarbon fluids in subduction zones.

58 GEOSCIENCES↗
DOE OSTI2024

Electrically Powered High-Salinity Brine Separation Using Dimethyl Ether

Dewatering highly saline aqueous streams, from mining and geothermal leachates to industrial wastewater, is essential for effective resource recovery and safe disposal. Membraneless water extraction (MWE) uses a low-polarity solvent to separate water from concentrated aqueous solutions. In this study, we design a new MWE that uses dimethyl ether (DME) to selectively extract water from high-salinity brines, leveraging the volatility of DME to achieve rapid solvent recovery. By separating water and dissolved salts at a liquid–liquid interface, MWE minimizes the deleterious effects of scaling on vulnerable membrane and heat exchanger surfaces, reducing the need for extensive pretreatment and expensive materials. We begin by developing a computational framework for a multistage counterflow liquid–liquid contactor, which extracts water into DME, coupled with a multistage solvent regenerator that uses vapor compression to efficiently separate the desalinated water from the DME extractant. Excess Gibbs free energy and equation of state frameworks are used to model fluid phase equilibria in water–DME–sodium chloride (NaCl) mixtures, with interaction parameters estimated from experimental data. Incorporating equilibrium calculations into a system-scale computational model, we examine the performance of MWE using DME for the first time. Our analysis demonstrates that MWE can concentrate seawater desalination brine (>1.0 mol NaCl kg –1 ) to zero-liquid discharge salinities, with an energy consumption of under 50 kW h per m 3 of water extracted with a solvent recovery ratio greater than 99.9%. We highlight the importance of staging the vapor compression process to simultaneously minimize energy consumption while enabling brine concentration and product water solvent contamination. Finally, the thermodynamic framework developed here allows for the robust evaluation of new MWE solvents and systems for critical brine concentration and fractional precipitation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Watch and learn—a generalized approach for transferrable learning in deep neural networks via physical principles

Transfer learning refers to the use of knowledge gained while solving a machine learning task and applying it to the solution of a closely related problem. Such an approach has enabled scientific breakthroughs in computer vision and natural language processing where the weights learned in state-of-the-art models can be used to initialize models for other tasks which dramatically improve their performance and save computational time. Here we demonstrate an unsupervised learning approach augmented with basic physical principles that achieves fully transferrable learning for problems in statistical physics across different physical regimes. By coupling a sequence model based on a recurrent neural network to an extensive deep neural network, we are able to learn the equilibrium probability distributions and inter-particle interaction models of classical statistical mechanical systems. Our approach, distribution-consistent learning, DCL, is a general strategy that works for a variety of canonical statistical mechanical models (Ising and Potts) as well as disordered interaction potentials. Using data collected from a single set of observation conditions, DCL successfully extrapolates across all temperatures, thermodynamic phases, and can be applied to different length-scales. This constitutes a fully transferrable physics-based learning in a generalizable approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Landau-Lifshitz-Bloch equation for ferrimagnets with higher-order interaction

In this work, we present a micromagnetic formulation for modeling the magnetization dynamics and thermal equilibrium in ferrimagnetic materials at low and elevated temperatures. The formulation is based on a mean-field approximation (MFA). In this formulation, the ferrimagnet is described micromagnetically by two coupled sublattices with corresponding interactions, including inter- and intrasublattice micromagnetic exchange as well as four-spin interactions described as an intersublattice molecular field with a cubic dependence of the magnetization. The MFA is used to derive a Landau-Lifshitz-Bloch type equation for ferrimagnetic material, including cases with a ferromagnetic-antiferromagnetic phase transitions. For validation, the results obtained via the presented model are compared with recent experimental data for phase transitions in FeRh.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗