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Results for “equilibrium potential”

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
NASA NTRS1992

Tropical boundary layer equilibrium in the last ice age

A radiative-convective boundary layer model is used to assess the effect of changing sea surface temperature, pressure, wind speed, and the energy export from the tropics on the boundary layer equilibrium equivalent potential temperature. It remains difficult to reconcile the observations that during the last glacial maximum (18,000 yr BP) the snowline on the tropical mountains fell 950 m, while the tropical sea surface temperatures fell only 1-2 K.

Betts, Alan K.↗
DOE OSTI2025

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗
DOE OSTI2025

Liquid–Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl 3 ) Enabled by Machine Learning Interatomic Potentials

Molten salts are promising candidates in numerous clean energy applications, where knowledge of thermophysical properties and vapor pressure across their operating temperature ranges is critical for safe operations. Due to challenges in evaluating these properties using experimental methods, fast and scalable molecular simulations are essential to complement the experimental data. In this study, we developed machine learning interatomic potentials (MLIP) to study the AlCl 3 molten salt across varied thermodynamic conditions (T = 473–613 K and P = 2.7–23.4 bar), which allowed us to predict temperature-surface tension correlations and liquid–vapor phase diagram from direct simulations of two-phase coexistence in this molten salt. Two MLIP architectures, a Kernel-based potential and neural network interatomic potential (NNIP), were considered to benchmark their performance for AlCl 3 molten salt using experimental structure and density values. The NNIP potential employed in two-phase equilibrium simulations yields the critical temperature and critical density of AlCl 3 that are within 10 K (∼3%) and 0.03 g/cm 3 (∼7%) of the reported experimental values. An accurate correlation between temperature and viscosities is obtained as well. In doing so, we report that the inclusion of low-density configurations in their training is critical to more accurately represent the AlCl 3 system across a wide phase-space. The MLIP trained using PBE-D3 functional in the ab initio molecular dynamics (AIMD) simulations (120 atoms) also showed close agreement with experimentally determined molten salt structure comprising Al 2 Cl 6 dimers, as validated using Raman spectra and neutron structure factor. Furthermore, the PBE-D3 as well as its trained MLIP showed better liquid density and temperature correlation for AlCl 3 system when compared to several other density functionals explored in this work. Overall, the demonstrated approach to predict temperature correlations for liquid and vapor densities in this study can be employed to screen nuclear reactors-relevant compositions, helping to mitigate safety concerns.

Ab initio molecular dynamics↗
DOE OSTI2023

Modernist materials synthesis: Finding thermodynamic shortcuts with hyperdimensional chemistry

Synthesis remains a challenge for advancing materials science. A key focus of this challenge is how to enable selective synthesis, particularly as it pertains to metastable materials. This perspective addresses the question: how can “spectator” elements, such as those found in double ion exchange (metathesis) reactions, enable selective materials synthesis? By observing reaction pathways as they happen (in situ) and calculating their energetics using modern computational thermodynamics, we observe transient, crystalline intermediates that suggest that many reactions attain a local thermodynamic equilibrium dictated by local chemical potentials far before achieving a global equilibrium set by the average composition. Furthermore, using this knowledge, one can thermodynamically “shortcut” unfavorable intermediates by including additional elements beyond those of the desired target, providing access to a greater number of intermediates with advantageous energetics and selective phase nucleation. Ultimately, data-driven modeling that unites first-principles approaches with experimental insights will refine the accuracy of emerging predictive retrosynthetic models for complex materials synthesis.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Analysis of Static Spacecraft Floating Potential at Low Earth Orbit (LEO)

Spacecraft floating potential is the charge on the external surfaces of orbiting spacecraft relative to the space. Charging is caused by unequal negative and positive currents to spacecraft surfaces. The charging process continues until the accelerated particles can be collected rapidly enough to balance the currents at which point the spacecraft has reached its equilibrium or floating potential. In low inclination. Low Earth Orbit (LEO), the collection of positive ion and negative electrons. in a particular direction. are typically not equal. The level of charging required for equilibrium to be established is influenced by the characteristics of the ambient plasma environment. by the spacecraft motion, and by the geometry of the spacecraft. Using the kinetic theory, a statistical approach for studying the interaction is developed. The approach used to study the spacecraft floating potential depends on which phenomena are being applied. and on the properties of the plasma. especially the density and temperature. The results from kinetic theory derivation are applied to determine the charging level and the electric potential distribution at an infinite flat plate perpendicular to a streaming plasma using finite-difference scheme.

Herr, Joel L.↗
NASA NTRS2019

An Analytic Model for Estimating the First Contact Resistance Needed to Avoid Damaging ESD During Spacecraft Docking in GEO

NASA’s Gateway program will involve spacecraft (s/c) docking in the outer radiation belt in order to transfer Gateway elements between s/c for transport to lunar orbit. The charging of these s/c to different potentials prior to docking raises the possibility of a damaging electrostatic discharge (ESD) at the time of first contact between the s/c. A proposed mitigation strategy is for first contact to occur prior to docking through a resistor with resistance R that would lower the potential difference at an optimal rate to a sufficiently low value to prevent ESD damage. The coupling of s/c by a resistor can be modeled by SPIS, but for realistic two s/c models SPIS can take hours to simulate the evolution of the s/c surface charges and potentials to an equilibrium state. Our objective is to develop a simpler model of s/c resistive coupling that runs orders of magnitude faster while providing useful first design estimates of the time variation of the s/c potentials, current through the resistor, and how these vary with R and s/c configuration This configuration is defined by the relative separation and orientation of the s/c, and their solar illumination. The configuration and geometry of the s/c determine their capacitive coupling. The s/c capacitances are computed using Nascap-2K. This poster presents the first version of such a model, and initial tests.

Goodman, Michael L.↗
NASA NTRS2019

An Analytic Model for Estimating the First Contact Resistance Needed to Avoid Damaging ESD During Spacecraft Docking in GEO

NASA’s Gateway program is to involve spacecraft (s/c) docking in the outer radiation belt in order to transfer Gateway elements between s/c for transport to lunar orbit. The charging of these s/c to different potentials prior to docking raises the possibility of a damaging electrostatic discharge (ESD) at the time of first contact between the s/c. A proposed mitigation strategy is for first contact to occur prior to docking through a resistor with resistance R that would lower the potential difference at an optimal rate to a sufficiently low value to prevent a damaging ESD. The coupling of s/c by a resistor can be modeled by SPIS (Spacecraft Plasma Interaction System), but for realistic two s/c models SPIS can take hours to simulate the evolution of the s/c surface charges and potentials to an equilibrium state. Our objective is to develop a simpler model of s/c resistive coupling that runs orders of magnitude faster while providing useful first design estimates of the time variation of the s/c potentials, current through the resistor, and how these vary with R and s/c configuration. This configuration is defined by the relative separation and orientation of the s/c, and their solar illumination. The configuration and geometry of the s/c determine their capacitive coupling. The s/c capacitances are computed using Nascap-2K. This abstract and the associated poster describe the first version of such a model, and initial tests.

Goodman, Michael L.↗
DOE OSTI2024

Open Circuit Potential of a Au Catalyst during Selective Oxidation of Glycerol

It has been of great interest to understand relationships between the potential of a metal catalyst and its thermochemical catalytic activity, especially in an aqueous phase environment. In the literature, there are correlations of open circuit potential with reaction rates or surface concentrations of reaction intermediates. In this study, we measured the open circuit potential (OCP) of a Au gauze during selective oxidation of glycerol to glyceric acid and hydrogen peroxide in a basic solution, as a function of hydroxide and alcoholate concentrations. It is found that applying a potential to the Au catalyst has no influence on the reaction rate. Although a rough correlation appears to exist between OCP and reaction rate, the data are better fit to an equation which assumes that the potential of the metal (i.e. the OCP) is in equilibrium with the electrochemical potential of the solution, which is defined by the thermodynamic activities of the oxidizing and reducing species. The equation: OCP = constant + Σ ox [(RT/FZ ox )ln[Ox]] - Σ red [(RT/FZ red )ln[Red]] implicitly assumes that the Au metal functions as a probing electrode. It is further found that this equation also applies to the Au-catalyzed H 2 O 2 oxidation/decomposition reaction in a basic medium, and possibly to formic acid dehydrogenation. Here, we postulate that the apparent correlation between OCP and reaction rate is due to the fact that the reaction rate is proportional to the concentrations of the reaction products and/or reactants that define the electrochemical potential of the solution.

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

Transient methods for understanding the properties of strongly oxidizing radicals

This review discusses the properties of strongly oxidizing radicals in organic and aqueous media and highlights the challenges in obtaining accurate values of their reduction potentials. Transient redox equilibrium methods based on the use of strong photooxidants or initiated by pulse radiolysis are shown to provide versatile approaches for decoupling electron transfer reactions from follow-up reactivity of unstable radical species, resulting in accurate values of reduction potentials of very positive couples, including some solvent radical cations. Here, we also show that correlations of reduction potentials with Hammett Σσ + p parameters, as well as gas phase ionization potentials, can be used to estimate the redox properties of unknown couples within a homologous series of compounds. The effects of ion pairing and hemicolligation on redox properties of organic and inorganic radicals are also discussed.

14 SOLAR ENERGY↗
DOE OSTI2024

Fuel‐Driven π‐Conjugated Superstructures to Form Transient Conductive Hydrogels

Despite advances in creating dissipative materials with transient properties, such as hydrogels and active droplets, their application remains confined to temporal changes in structural properties. Developing out-of-equilibrium materials whose electronic functions are parameterized by a chemical reaction cycle is challenging. Yet, this class of materials is required to construct biomimetic materials. In contrast to traditional chemical reaction cycles that exploit molecularly dissolved building blocks at thermodynamic equilibrium, we show that fiber structures derived from reactive naphthalene diimide (NDI) building blocks can be used as resting states to form far-from-equilibrium conductive hydrogels after the addition of chemical fuels. Upon fueling the NDI-derived fibers, a dual-component activation and deactivation pathway is deduced by kinetic analysis and is absent when using a molecularly dissolved resting state. Investigating the solid-state morphologies of the structures formed throughout the fuel-driven reaction cycle using cryo-EM reveals that the resting thermodynamic fibers evolve to transient thicker fibrils and layered superstructures. We show that the transient redox-active hydrogels exhibit a nearly threefold increase in electrical conductivity upon fuel consumption before reverting to their original value over hours. In conclusion, these far-from-equilibrium materials are potential candidates in applications such as programmable biorobotics and chemical computing.

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

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

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

Self-Induced Curvature in an Internally Loaded Peridynamic Fiber

A straight fiber with nonlocal forces that are independent of bond strain is considered. These internal loads can either stabilize or destabilize the straight configuration. Transverse waves with long wavelength have unstable dispersion properties for certain combinations of nonlocal kernels and internal loads. When these unstable waves occur, deformation of the straight fiber into a circular arc can lower its potential energy in equilibrium. The equilibrium value of the radius of curvature is computed explicitly.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predictive Tools for Customizing Heat Treatment of Additively Manufactured Aerospace Components

Laser-bed powder fusion (LBPF) additive manufacturing is increasingly being used to produce components of complex geometries using the Ni-base superalloy Inconel 718. The composition and the microstructure of the alloy are currently well optimized for wrought components made using conventional manufacturing processes such as rolling, forging, extrusion, etc. The attractive mechanical properties of the alloy result from the underlying austenitic matrix with fine equiaxed grains, and a high density and uniform distribution of the precipitation hardening phase, γ". Heat treatment steps such as homogenization, solutioning and aging are well documented for the wrought alloy. However, when the same wrought alloy compositions are used for the additive manufacturing (AM) processes, the asprocessed microstructure is significantly different, because of the different thermal history associated with LBPF, including rapid solidification and multiple temperature excursions that lead to multiple re-melting and reheating in the solid state. Rapid solidification introduces potential non-equilibrium effects at the moving solid-liquid interfaces that impact the extent of solute segregation, as well as the morphology of the dendritic grains that form. In order to recover the target mechanical properties, AM components have to undergo post-process heat treatments. However, such heat treatments have to be custom designed for the AM process and the component geometry because of the expected vast differences in the microstructure at various locations of a component with complex geometry. The homogenization and precipitation steps should be optimized for the component so that target mechanical properties can be obtained throughout the part. The objective of this research is to utilize High Performance Computing in phase field simulations of microstructure evolution during post-processing of AM components. The physics-based modeling will be beneficial in reducing the experimental effort required for heat treatment process selection, optimization, and certification, thus leading to a significant reduction in energy consumption for AM and post-processing heat treatment. The optimization study will help identify heat treatments steps that are critical for development of a final desired microstructure with the minimum energy input. This combined with shortening of the production cycle (time-to-market) by reducing the number of failed parts (property targets), and reduction in the number of iterations for process optimization, will enable 30-40% savings in the energy costs. Phase field simulations of the degree of homogenization and the effect of local matrix composition on the nucleation and growth of competing precipitating phases were performed using the Microstructure Evolution Using Massively Parallel Phase Field Simulations code developed in-house at the Oak Ridge National Laboratory. The simulations were able to successfully capture the kinetics of nucleation and growth, and morphologies of various precipitating phases as a function of local matrix compositions and composition gradients characteristic of local microstructures arising from location-dependent variations in the thermal conditions. Future work will involve extending the simulations to a length scale consisting of multiple dendrites, so that the effect of homogenization on the coarsening of the dendrites can be simulated and used as an additional input to the optimization of the heat treatment process.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Self-gravitating gas flow in barred spiral galaxies

A series of two-dimensional numerical experiments is performed in order to test the response of an isothermal, self-gravitating gas disk to a uniformly rotating, barlike gravitational potential. The barlike potential is an equilibrium stellar model from the n-body calculations of Miller and Smith (1979). In the bar-dominated, central regions of the disk, a gas bar whose phase depends primarily on the location of principal resonances in the disk is formed. This response can be understood in terms of orbit-crowding effects. In the gas-dominated outer regions of the disk, two-armed trailing spiral waves are formed. The local pitch angle of these waves increases with increasing fractional gas mass. These self-gravitating gas waves are not self-sustaining. They are driven from the ends of equilibrium stellar bars, and their phase does not depend on the location of resonances in the disk. The relevance of these self-gravitating waves to observations and models of barred spiral galaxies is discussed. It is concluded that these waves and their associated ringlike structures may be consistent with the morphological distribution of gas features in barred spiral galaxies.

Huntley, J. M.↗
NASA NTRS1982

Statics of wrinkling films

An analytical investigation of the equilibrium of wrinkling films is conducted. Zak (1979) has shown that wrinkling occurs in connection with the instability of a smooth film having no resistance to bending in the case of compression. The governing equation for the equilibrium of a film with possible regions of wrinkling is considered. The introduction of fictitious stress reduces the governing equation to a form which formally coincides with the governing equation for a string. Equilibrium conditions in the case of an absence of external forces are explored, taking into account the stretching of a semispherical film, the torsion of a convex film of revolution, and stress singularities. A study is conducted of the equilibrium under conditions in which external forces normal to the surface of a film are present. Attention is also given to the equilibrium in a potential field.

Zak, M.↗
NASA NTRS2000

Dynamic Modeling of Off-Nominal Operation in Advanced Life Support Systems

System failures, off-nominal operation, or unexpected interruptions in processing capability can cause unanticipated instabilities in Advanced Life Support (ALS) systems, even long after they are repaired. Much current modeling assumes ALS systems are static and linear, but ALS systems are actually dynamic and nonlinear, especially when failures and off nominal operation are considered. Modeling and simulation provide a way to study the stability and time behavior of nonlinear dynamic ALS systems under changed system configurations or operational scenarios. The dynamic behavior of a nonlinear system can be fully explored only by computer simulation over the full range of inputs and initial conditions. Previous simulations of BIO-Plex in SIMULINK, a toolbox of Matlab, were extended to model the off-nominal operation and long-term dynamics of partially closed physical/chemical and bioregenerative life support systems. System nonlinearity has many interesting potential consequences. Different equilibrium points may be reached for different initial conditions. The system stability can depend on the exact system inputs and initial conditions. The system may oscillate or even in rare cases behave chaotically. Temporary internal hardware failures or external perturbations in ALS systems can lead to dynamic instability and total ALS system failure. Appropriate control techniques can restore reliable operation and minimize the effects of dynamic instabilities due to anomalies or perturbations in a life support system.

Jones, Harry↗