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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗
DOE OSTI2022

Computational Prediction of Water Sorption in Facilitated Transport Membranes

Polymeric facilitated transport membranes (FTMs) have emerged as an innovative class of promising carbon capture technology. Studies have shown that the transport properties of an FTM are significantly influenced by its water uptake. In order to better quantify FTM performance, we herein explore the potential of computational techniques to predict the equilibrium water uptake values of FTMs. Two prediction approaches were examined. First, the water sorption was explicitly simulated by iteratively conducting grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. Second, the water sorption was predicted based on the chemical potential of the adsorbed water, which was calculated using the Widom insertion or continuous fractional component Monte Carlo (CFCMC) method. The chemical potential-based approach with CFCMC demonstrated good prediction of the equilibrium water uptake values of FTMs with poly(N-vinylformamide-co-vinylamine) as fixed-site carrier and 2-(1-piperazinyl)ethylamine sarcosinate as mobile carrier. The predicted water uptake values increased with increasing mobile carrier content and were in good agreement with the experimental values. Furthermore, the higher water uptake promoted the diffusion of CO 2 , N 2 , and mobile carrier as well as slightly stifled the sorption of N 2 . Such an approach significantly contributes to a more comprehensive theoretical evaluation of FTMs.

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

The imaginary part of the heavy-quark potential from real-time Yang-Mills dynamics

We extract the imaginary part of the heavy-quark potential using classical-statistical simulations of real-time Yang-Mills dynamics in classical thermal equilibrium. The r-dependence of the imaginary part of the potential is extracted by measuring the temporal decay of Wilson loops of spatial length r. We compare our results to continuum expressions obtained using hard thermal loop theory and to semi-analytic lattice perturbation theory calculations using the hard classical loop formalism. We find that, when plotted as a function of m D r, where m D is the hard classical loop Debye mass, the imaginary part of the heavy-quark potential shows little sensitivity to the lattice spacing at small m D r ≲ 1 and agrees well with the semi-analytic hard classical loop result. For large quark-antiquark separations, we quantify the magnitude of the non-perturbative long-range corrections to the imaginary part of the heavy-quark potential. We present our results for a wide range of temperatures, lattice spacings, and lattice volumes. This work sets the stage for extracting the imaginary part of the heavy-quark potential in an expanding non-equilibrium Yang Mills plasma.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Differentiating Ligand Tailoring and Cation Incorporation as Strategies for Tuning Heterobimetallic Cerium Complexes

Tuning of redox-active complexes featuring metals with high coordination numbers by incorporation of secondary redox-inactive cations has received far less attention than it deserves. Here, appending moderate steric bulk to a tripodal ligand framework has been tested for its influence on secondary-cation-driven structural and electrochemical tuning of cerium, a lanthanide that tends to adopt high coordination numbers. A quasi -C 3 -symmetric cerium(III) complex denoted [Ce] has been prepared that features pendant benzyloxy groups, and this work demonstrates that this species offers a site capable of binding single Na + or Ca 2+ ions. Electrochemical and UV-visible spectroscopic studies reveal equilibrium binding affinity of [Ce] for Na + in acetonitrile solvent, contrasting with tight binding of all cations in all other previously studied systems of this type. The modulated cation binding can be attributed to the bulky benzyloxy groups, which impact the thermodynamics of cation binding but do not impede the formation of cerium centers with coordination number 8 upon binding of either Na + or Ca2 + . Finally, the Ce(IV/III) reduction potential was found to be tunable under the equilibrium binding conditions, highlighting the potentially significant role that controlled structural changes can play in modulating the solution properties of heterobimetallic complexes.

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

Phase transformations, microstructural refinement and defect evolution mechanisms in Al-Si alloys under non-hydrostatic diamond anvil cell compression

Non-hydrostatic compression of materials using a diamond anvil cell (DAC) can transform equilibrium microstructure of an alloy to novel, potentially metastable states. In this study, in situ synchrotron X-ray diffraction (XRD) during compression up to 24 GPa and subsequent ex situ, high resolution analytical electron microscopy (AEM) after decompression of an Al-Si alloy provided insight into the crystallographic changes during the compression as well as microstructural refinement, and defect structures caused by such a high pressure compression-decompression process. Pressure resolved in-situ synchrotron XRD was used to detail the phase transformation pathway of the eutectic Si phase in Al-Si alloy, from Si-I → Si-XI → Si-V during compression, and a final transformation predominantly to Si-III after decompression. Using scanning and transmission electron microscopy (S/TEM), site specific analysis of the alloy immediately underneath the anvil contact surface demonstrated a highly complex microstructure. A narrow region of thick amorphous Al oxide interspersed with nanocrystalline grains was found at the top surface. Underneath this Al oxide, while the majority the eutectic Si was transformed into highly-deformed, polycrystalline (PC) Si-III, a complex intermediate layer was discovered at the interface between Al and Si, comprised of a small fraction of Al nanocrystals and a majority of nanocrystalline Si-I. This combination of pressure resolved in-situ synchrotron XRD coupled with subsequent high resolution, electron microscopy resolved the phase transformation as well as non-equilibrium microstructures in a metallic alloy induced by a non-hydrostatic high pressure compression followed by decompression.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization of Deformational Isomerization Potential and Interconversion Dynamics with Ultrafast X-ray Solution Scattering

Dimeric complexes composed of d 8 square planar metal centers and rigid bridging ligands provide model systems to understand the interplay between attractive dispersion forces and steric strain in order to assist the development of reliable methods to model metal dimer complexes more broadly. [Ir 2 (dimen) 4 ] 2+ (dimen = para-diisocyanomenthane) presents a unique case study for such phenomena, as distortions of the optimal structure of a ligand with limited conformational flexibility counteract the attractive dispersive forces from the metal and ligand to yield a complex with two ground state deformational isomers. Here, in this work, we use ultrafast X-ray solution scattering (XSS) and optical transient absorption spectroscopy (OTAS) to reveal the nature of the equilibrium distribution and the exchange rate between the deformational isomers. The two ground state isomers have spectrally distinct electronic excitations that enable the selective excitation of one isomer or the other using a femtosecond duration pulse of visible light. We then track the dynamics of the nonequilibrium depletion of the electronic ground state population—often termed the ground state hole—with ultrafast XSS and OTAS, revealing a restoration of the ground state equilibrium in 2.3 ps. This combined experimental and theoretical study provides a critical test of various density functional approximations in the description of bridged d 8 –d 8 metal complexes. The results show that density functional theory calculations can reproduce the primary experimental observations if dispersion interactions are added, and a hybrid functional, which includes exact exchange, is used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Estimating coil features from an equilibrium

We present an explicit theoretical framework for constructing artificial modular coils for vacuum stellarator fields based solely on equilibrium properties, achieved through the formulation of a current potential defined on flux surfaces. Contours of constant Boozer toroidal angle can be directly interpreted as proxy coils, and so we demonstrate that key measures of coil complexity—particularly coil non-planarity—are strongly governed by local magnetic-field properties. This approach shows promise as predictor for more realistic coil configurations, providing both a pathway toward deeper understanding of equilibrium–coil relationships and a potential practical proxy for coil design.

Rodríguez, Eduardo [Max Planck Institute for Plasm↗
DOE OSTI2020

Potential Control of Oxygen Non-Stoichiometry in Cerium Oxide and Phase Transition Away from Equilibrium

Cerium oxide (ceria, CeO 2 ) is a technologically important material for energy conversion applications. Its activities strongly depend on redox states and oxygen vacancy concentration. Understanding the functionality of chemical active species and behavior of oxygen vacancy during operation, especially in high-temperature solid-state electrochemical cells, is the key to advance future material design. Herein, the structure evolution of ceria is spatially resolved using bulk-sensitive operando X-ray diffraction and spectroscopy techniques. During water electrolysis, ceria undergoes reduction, and its oxygen non-stoichiometry shows a dependence on the electrochemical current. Cerium local bonding environments vary concurrently to accommodate oxygen vacancy formation, resulting in changes in Ce-O coordination number and Ce 3+ /Ce 4+ redox couple. When reduced enough, a crystallographic phase transition occurs from α to an α' phase with more oxygen vacancies. Nevertheless, the transition behavior is intriguingly different from the one predicted in the standard phase diagram of ceria. This work demonstrates a feasible means to control oxygen non-stoichiometry in ceria via electrochemical potential. It also sheds light on the mechanism of phase transitions induced by electrochemical potential. For electrochemical systems, effects from a large-scale electrical environment should be taken into consideration, besides effective oxygen partial pressure and temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MP-ALOE: an r2SCAN dataset for universal machine learning interatomic potentials

We present MP-ALOE, a dataset of nearly 1 million DFT calculations using the accurate r2SCAN meta-generalized gradient approximation. Covering 89 elements, MP-ALOE was created using active learning and primarily consists of off-equilibrium structures. We benchmark a machine learning interatomic potential trained on MP-ALOE, and evaluate its performance on a series of benchmarks, including predicting the thermochemical properties of equilibrium structures; predicting forces of far-from-equilibrium structures; maintaining physical soundness under static extreme deformations; and molecular dynamic stability under extreme temperatures and pressures. MP-ALOE shows strong performance on all of these benchmarks and is made public for the broader community to utilize.

Kuner, Matthew C↗
DOE OSTI2021

Plasma Muon Beam Cooling for HEP

Ionization cooling has the potential to shrink the phase space of a muon beam by a factor of 10⁶ within the muons’ short lifetime (2.2 µs) because the collision frequency in a cooling medium is extremely high compared to conventional beam cooling methods. It has been realized that ionization cooling inherently produces a plasma of free electrons inside the absorber material, and this plasma can have an important effect on the muon beam. In particular, under the right circumstances, it can both improve the rate of cooling and reduce the equilibrium emittance of the beam. This has the potential to improve the performance of muon facilities based on muon cooling; in particular a future muon collider. We describe how this project will integrate Plasma muon beam cooling into both the basic Helical Cooling Channel (HCC) and extreme Parametric-resonance Ionization Cooling (PIC) techniques. This potentially whole new approach to muon cooling has exciting prospects for significantly reduced muon beam emittance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

The Technical and Economic Potential of the H2@Scale Hydrogen Concept within the United States

The U.S. energy system is evolving as society and technologies change. Renewable electricity generation - especially from wind and solar - is growing rapidly, and alternative energy sources are being developed and implemented across the residential, commercial, transportation, and industrial sectors to take advantage of their cost, security, and health benefits. Systemic changes present numerous challenges to grid resiliency and energy affordability, creating a need for synergistic solutions that satisfy multiple applications while yielding system-wide cost and emissions benefits. One such solution is an integrated hydrogen energy system. This is the focus of H2@Scale - a U.S. Department of Energy (DOE) initiative led by the Office of Energy Efficiency and Renewable Energy’s Hydrogen and Fuel Technologies Office. H2@Scale brings together stakeholders to advance affordable hydrogen production, transport, storage, and utilization in multiple energy sectors. The H2@Scale concept involves hydrogen as an energy intermediate. Hydrogen can be produced from various conventional and renewable energy sources including as a responsive load on the electric grid. Hydrogen has many current applications and many more potential applications, such as energy for transportation - used directly in fuel cell electric vehicles (FCEVs), as a feedstock for synthetic fuels, and to upgrade oil and biomass - feedstock for industry (e.g., for ammonia production, metals refining, and other end uses), heat for industry and buildings, and electricity storage. Owing to its flexibility and fungibility, a hydrogen intermediate could link energy sources that have surplus availability to markets that require energy or chemical feedstocks, benefiting both. This document builds upon a growing body of analyses of hydrogen as an energy intermediate by reporting the results from our initial analysis of the potential impacts of the H2@Scale vision by the mid-21 st century for the 48 contiguous U.S. states. Previous estimates have been based on expert elicitation and focused on hydrogen demands. We build upon them, first, by estimating hydrogen’s serviceable consumption potential for possible hydrogen applications and the technical potential for producing hydrogen from various resources. We define the serviceable consumption potential as the quantity of hydrogen that would be consumed to serve the portion of the market that could be captured without considering economics (i.e., if the price of hydrogen were $0/kg over an extended period); thus, it can be considered an upper bound for the size of the market. We define the technical potential as the resource potential constrained by real-world geography and system performance, but not by economics. We then compare the cumulative serviceable consumption potential with the technical potential of a number of possible sources. Second, we estimate economic potential: the quantity of hydrogen at an equilibrium price at which suppliers are willing to sell and consumers are willing to buy the same quantity of hydrogen. We believe this method provides a deeper understanding than was available in the previous analyses. We develop economic potentials for multiple scenarios across various market and technology-advancement assumptions.

08 HYDROGEN↗
DOE OSTI2021

Towards chemical equilibrium in thermochemical water splitting. Part 1: Thermal reduction

The efficiency of many processes strongly depends on their thermodynamic reversibility, i.e., proximity to equilibrium throughout the process. In thermochemical cycles for water and/or carbon dioxide splitting, thermochemical air separation, and thermochemical energy storage, operating near equilibrium means that the oxygen chemical potential of the solid and gas phases must not differ significantly. Herein we show that approaching this ideal is possible in thermal reduction only if the reaction step occurs at a specific, reaction coordinate- and material-dependent temperature. The resulting thermal reduction temperature profile also depends on the ratio of gas and solid flows.

08 HYDROGEN↗
DOE OSTI2021

Active motion of multiphase oil droplets: emergent dynamics of squirmers with evolving internal structure

Synthetic soft matter systems, when driven beyond equilibrium by active processes, offer the potential to achieve dynamical states and functions of a complexity found in living matter. Emulsions offer the basis of a simple yet versatile system for identification of the physicochemical principles underlying active soft matter, but how multiple internal phases within emulsion droplets (e.g., Janus morphologies) organize to impact emergent dynamics is not understood. Here, we create multiphase oil droplets with ultralow interfacial tensions but distinct viscosities, and drive them into motion in aqueous micellar solutions. Preferential solubilization of select components of the oil both drives the droplet motion and yields a progression of internal phase morphological states with distinct symmetries. In this work, we find the active droplets to exhibit five dynamical states during morphogenesis. By quantifying microscopic flow fields, we show that it is possible to map the diverse droplet behaviors to squirmer models of spherical microswimmers in Stokes flow, thus showing that multiphase droplets offer the basis of a versatile platform with which to study and engineer the hydrodynamics of microswimmers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery

The solvation free energy of organic molecules is a critical parameter in determining emergent properties such as solubility, liquid-phase equilibrium constants, and pKa and redox potentials in an organic redox flow battery. In this work, we present a machine learning (ML) model that can learn and predict the aqueous solvation free energy of an organic molecule using Gaussian process regression method based on a new molecular graph kernel. To investigate the performance of the ML model on electrostatic interaction, the nonpolar interaction contribution of solvent and the conformational entropy of solute in solvation free energy, three data sets with implicit or explicit water solvent models, and contribution of conformational entropy of solute are tested. We demonstrate that our ML model can predict the solvation free energy of molecules at chemical accuracy with a mean absolute error of less than 1 kcal/mol for subsets of the QM9 dataset and the Freesolv database. To solve the general data scarcity problem for a graph-based ML model, we propose a dimension reduction algorithm based on the distance between molecular graphs, which can be used to examine the diversity of the molecular data set. It provides a promising way to build a minimum training set to improve prediction for certain test sets where the space of molecular structures is predetermined.

25 ENERGY STORAGE↗
DOE OSTI2024

Visualizing the SEI formation between lithium metal and solid-state electrolyte

The solid electrolyte interphase (SEI) is regarded as the most important factor affecting the durability of lithium-metal anode in all-solid-state batteries (ASSBs). Despite its significance, the nucleation and growth mechanism of SEI is not yet well understood. Here, we elucidate the thermodynamics and kinetics governing SEI formation at the Li|β-Li 3 PS 4 interface at the atomic scale via thermodynamic phase equilibrium analysis and machine-learning-potential-assisted molecular dynamics (MD) simulations. An accurate moment tensor potential using the machine-learning method is developed for a reactive model of Li|β-Li 3 PS 4 . This potential enabled us to perform large-scale MD simulations with the model size expanded to the experimental dimensions (~40 nm) while maintaining the same level of accuracy as density functional theory calculations. The results reveal a four-stage evolution process at the Li|β-Li 3 PS 4 interface, namely (i) fast ion diffusion, (ii) nucleation, (iii) Li 2 S growth, and (iv) stabilization. Notably, we demonstrate that the SEI can be categorized into crystalline and amorphous regions. The simulated SEI thickness, structure, and composition closely match experimental findings, validating the accuracy of the MD simulations. We further disclose the significant impact of ion diffusion kinetic limitations on the phase formation and crystallization of interfacial products. Furthermore, we shed light on the detailed potential energy (PE) distribution of lithium along the direction perpendicular to the interface. Finally, this information is crucial for better understanding interfacial ion mobility.

25 ENERGY STORAGE↗
DOE OSTI2025

Multi-scale computational screening and mechanistic insights of cyclic amines as solvents for improved lignocellulosic biomass processing

A computational screening workflow for the efficient deconstruction of cellulose, lignin and hemicellulose fractions of lignocellulosic biomass using cyclic amines as solvents. Lignocellulosic biomass is a promising feedstock for production of affordable fuels and chemicals from renewable resources. Effective solubilization and subsequent deconstruction of its cellulose, hemicellulose, and lignin fractions is essential for the viability of future biorefineries. This study used quantum chemistry-based equilibrium thermodynamics methods to evaluate the potential of 650 cyclic amines to solubilize cellulose, hemicellulose, and lignin. The activity coefficients of solvent - biopolymer interactions were predicted using the COSMO-RS (COnductor-like Screening MOdel for Real Solvents) method and used to identify cyclic amines that can efficiently dissolve and extract selective fractions of biopolymers during biomass pretreatment. Among the 650 cyclic amines, 1-piperazineethanmaine was predicted to be an effective solvent for extracting all three polymers and was experimentally shown to achieve the highest lignin removal (97.1%). Non-covalent interaction, reduced density gradient and quantum chemical calculations were performed to elucidate the dissolution mechanism of lignin, cellulose and hemicellulose and gain further molecular level insights into the interactions between the cyclic amines and biomass polymers that promote efficient solubilization and extraction. These analyses indicated that 1-piperazineethanmaine and 1-methylimidazole make noncovalent van der Waals, electrostatic interactions and hydrogen bonding with lignin, leading to enhanced lignin removal, while the strong intramolecular hydrogen bonding interactions in cellulose and hemicellulose result in weaker solvent-biopolymer interactions. Overall, the computational approach provided an efficient method for identifying cyclic amines tailored for optimal biomass pretreatment and resulted in the identification of a potential new class of solvents for effective biomass pretreatment.

Kumar, Nikhil↗
DOE OSTI2022

Transferability of data-driven, many-body models for CO 2 simulations in the vapor and liquid phases

Here, extending on the previous work by Riera et al. [J. Chem. Theory Comput. 16, 2246–2257 (2020)], we introduce a second generation family of data-driven many-body MB-nrg models for CO 2 and systematically assess how the strength and anisotropy of the CO 2 –CO 2 interactions affect the models’ ability to predict vapor, liquid, and vapor–liquid equilibrium properties. Building upon the many-body expansion formalism, we construct a series of MB-nrg models by fitting one-body and two-body reference energies calculated at the coupled cluster level of theory for large monomer and dimer training sets. Advancing from the first generation models, we employ the charge model 5 scheme to determine the atomic charges and systematically scale the two-body energies to obtain more accurate descriptions of vapor, liquid, and vapor–liquid equilibrium properties. Challenges in model construction arise due to the anisotropic nature and small magnitude of the interaction energies in CO 2 , calling for the necessity of highly accurate descriptions of the multidimensional energy landscape of liquid CO 2 . These findings emphasize the key role played by the training set quality in the development of transferable, data-driven models, which, accurately representing high-dimensional many-body effects, can enable predictive computer simulations of molecular fluids across the entire phase diagram.

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

Perturbative approaches in relativistic kinetic theory and the emergence of first-order hydrodynamics

Hydrodynamics can be formulated in terms of a perturbative series in derivatives of the temperature, chemical potential, and flow velocity around an equilibrium state. Different formulations for this series have been proposed over the years, which consequently led to the development of various hydrodynamic theories. In this work, we discuss the relativistic generalizations of the perturbative expansions put forward by Chapman and Enskog, and Hilbert, using general matching conditions in kinetic theory. This allows us to describe, in a comprehensive way, how different out-of-equilibrium definitions for the hydrodynamic fields affect the development of the hydrodynamic perturbative series. We provide a perturbative method for systematically deriving the hydrodynamic formulation recently proposed by Bemfica, Disconzi, Noronha, and Kovtun (BDNK) from relativistic kinetic theory. The various transport coefficients that appear in BDNK (at first-order) are explicitly computed using a new formulation of the relaxation time approximation for the Boltzmann equation. Assuming Bjorken flow, we also determine the hydrodynamic attractors of BDNK theory and compare the overall hydrodynamic evolution obtained using this formulation with that generated by the Israel-Stewart equations of motion and also kinetic theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗