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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modeling Equilibrium Solid–Liquid Interfaces under Effective Constant Chemical Potential Using Machine Learning Interatomic Potentials

The chemical potential (μ) of species in solution is essential for understanding various chemical processes at interfaces. Molecular dynamics (MD) simulations, constrained by fixed compositions, cannot maintain constant chemical potential with reference to a targeted concentration or chemical potential under nonequilibrium or dynamic conditions, as solute species can migrate to the interface and deplete (or enrich) the bulk due to solute-interface interactions. In this study, we introduce a simple and computationally efficient approach named iterative quasi-constant chemical potential molecular dynamics (iqCμMD) simulation, which helps simulate targeted molar concentrations of species in solution. iqCμMD overcomes the limitations of conventional MD by adjusting the number of species in the solution to reach a target bulk concentration (chemical potential), which allows simulation of the interface under the bulk conditions comparable to experiment. We demonstrate our approach using machine learning interatomic potential (MLIP)-based MD simulations of the Na 2 SO 4,aq –graphene interface, and to show the transferability of our approach, we also perform classical force field-based MD simulations of NaCl aq –air and NaCl aq –graphite interfaces, which produce comparable results to previous CμMD simulations. Our results also show that the iqCμMD approach efficiently achieves the desired bulk ion concentration within two iterations, and by utilizing MLIPs, we can achieve converged results using relatively small-scale simulations compared to previous CμMD simulations. By combining iqCμMD with MLIP-driven simulations, solid–liquid interfaces can be modeled under an effective constant chemical potential with DFT-level accuracy. Here, we show that iqCμMD offers a robust and simple computational framework for constant chemical potential simulations, as its only requirement is to be able to converge interfacial simulations with a measurable bulk region.

Chemical structure↗
DOE OSTI2020

Potential-pH diagrams considering complex oxide solution phases for understanding aqueous corrosion of multi-principal element alloys

The potential-pH diagram, a graphical representation of the thermodynamically predominant reaction products in aqueous corrosion, is originally proposed for the corrosion of pure metals. The original approach only leads to stoichiometric oxides and hydroxides as the oxidation products. However, numerous experiments show that non-stoichiometric oxide scales are prevalent in the aqueous corrosion of alloys. In the present study, a room temperature potential-pH diagram considering oxide solid solutions, as a generalization of the traditional potential-pH diagram with stoichiometric oxides, is constructed for an FCC single-phase multi-principal element alloy (MPEA) based on the CALculation of PHAse Diagram method. The predominant reaction products, the ions in aqueous solution, and the cation distribution in oxides are predicted. The oxide solid solution is stabilized by the mixing free energy (or mixing entropy) and the stabilizing effect becomes more significant as the temperature increases. Consequently, solid solution oxides are stable in large regions of the potential-pH diagram and the mixing free energy mostly affects the equilibrium composition of the stable oxides, while the shape of stable regions for oxides is mostly determined by the structure of the stable oxides. Agreements are found for Ni 2+ , Fe 2+ , and Mn 2+ between the atomic emission spectroelectrochemistry measurements and thermodynamic calculations, while deviations exist for Cr 3+ and Co 2+ possibly due to surface complexation with species such as Cl - and the oxide dissolution. By incorporating the solution models of oxides, the current work presents a general and more accurate way to analyze the reaction products during aqueous corrosion of MPEAs.

Materials Science↗
DOE OSTI2019

Potential model for nuclear astrophysical fusion reactions with a square-well potential

The potential model for nuclear astrophysical reactions requires a considerably shallow nuclear potential when a square-well potential is employed to fit experimental data. Here, we discuss the origin of this apparently different behavior from that obtained with a smooth Woods-Saxon potential, for which a deep potential is often employed. We argue that due to the sharp change of the potential at the boundary the radius parameter tends to be large in the square-well model, which results in a large absorption radius. The wave function then needs to be suppressed in the absorption region, which can eventually be achieved by using a shallow potential. We thus clarify the reason why the square-well potential has been able to reproduce a large amount of fusion data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Molecular simulation of fluids with non-identical intermolecular potentials: Thermodynamic properties of 10-5 + 12-6 Mie potential binary mixtures

General methods for combining interactions between particles characterised by non-identical intermolecular potentials are investigated. The combination methods are tested by performing molecular dynamics simulations to determine the pressure, energy, isochoric and isobaric heat capacities, thermal expansion coefficient, isothermal compressibility, Joule-Thomson coefficient, and speed of sound of 10-5 + 12-6 Mie potential binary mixtures. In addition to the two non-identical Mie potentials, mixtures are also studied with non-identical intermolecular parameters. The combination methods are compared with results obtained by simply averaging the Mie exponents. When either the energy or size parameters are non-identical, very significant differences emerge in the thermodynamic properties predicted by the alternative combination methods. The isobaric heat capacity is the thermodynamic property that is most affected by the relative magnitude of the intermolecular potential parameters and the method for combining non-identical potentials. Either the arithmetic or geometric combination of potentials provides a simple and effective way of performing simulations involving mixtures of components characterised by non-identical intermolecular potentials, which is independent of their functional form.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Derivative discontinuity with localized Hartree-Fock potential

The localized Hartree-Fock potential has proven to be a computationally efficient alternative to the optimized effective potential, preserving the numerical accuracy of the latter and respecting the exact properties of being self-interaction free and having the correct −1/r asymptotics. In this paper we extend the localized Hartree-Fock potential to fractional particle numbers and observe that it yields derivative discontinuities in the energy as required by the exact theory. The discontinuities are numerically close to those of the computationally more demanding Hartree-Fock method. Our potential enjoys a “direct-energy” property, whereby the energy of the system is given by the sum of the single-particle eigenvalues multiplied by the corresponding occupation numbers. The discontinuities c{sub ↑} and c{sub ↓} of the spin-components of the potential at integer particle numbers N{sub ↑} and N{sub ↓} satisfy the condition c{sub ↑}N{sub ↑} + c{sub ↓}N{sub ↓} = 0. Thus, joining the family of effective potentials which support a derivative discontinuity, but being considerably easier to implement, the localized Hartree-Fock potential becomes a powerful tool in the broad area of applications in which the fundamental gap is an issue.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Interface properties and built-in potential profile of a LaCr O 3 / SrTi O 3 superlattice determined by standing-wave excited photoemission spectroscopy

LaCrO 3 (LCO)/SrTiO 3 (STO) heterojunctions are intriguing due to a polar discontinuity along [001], exhibiting two distinct and controllable charged interface structures [(LaO) + /(TiO 2 ) 0 and (SrO) 0 /(CrO 2 ) - ] with induced polarization, and a resulting depth-dependent potential. In this study, we have used soft- and hard-x-ray standing-wave excited photoemission spectroscopy (SW-XPS) to quantitatively determine the elemental depth profile, interface properties, and depth distribution of the polarization-induced built-in potentials. We observe an alternating charged interface configuration: a positively charged (LaO) + /(TiO 2 ) 0 intermediate layer at the LCO top /STO bottom interface and a negatively charged (SrO) 0 /(CrO 2 ) - intermediate layer at the STO top /LCO bottom interface. Using core-level SW data, we have determined the depth distribution of species, including through the interfaces, and these results are in excellent agreement with scanning transmission electron microscopy and electron energy-loss spectroscopy mapping of local structure and composition. SW-XPS also enabled deconvolution of the LCO and STO contributions to the valence-band (VB) spectra. Using a two-step analytical approach involving first SW-induced core-level binding-energy shifts and then VB modeling, the variation in potential across the complete superlattice is determined in detail. As a result, this potential is in excellent agreement with density functional theory models, confirming this method as a generally useful tool for interface studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

First-principles calculations of oxidation potentials of electrolytes in lithium–sulfur batteries and their variations with changes in environment

In this work, oxidation potentials of electrolyte molecules in Li–sulfur (Li/S) batteries and their variations in various solvent environments are investigated using first-principles calculations in order to understand oxidative decomposition reactions of electrolytes for cathode passivation. Electrolyte solvents, Li salts, and various additives in Li/S batteries along with some Li-ion battery additives are studied. Oxidation potentials of isolated electrolyte molecules are found to be out of the operating range of typical Li/S batteries. The complexation of electrolyte molecules with Li + , salt anion, salt, S8, and pyrene alters oxidation potentials compared to those of the isolated systems. The salt anion lowers oxidation potentials of electrolyte molecules by at least 4.7% while the complexes with Li + have higher oxidation potentials than the isolated molecules by at least 10.4%. S8 and pyrene, used as model compounds for sulfur and sulfur/ carbon composite cathode materials, also affect oxidation potentials of electrolyte molecules, but their influence is negligible and the oxidation trends differ from those of the Li + and salt anion. Although complexations change the oxidation potentials of electrolyte molecules, they are still higher than the operating voltage range of Li/S batteries, which indicates that oxidation of the studied electrolytes in Li/S batteries is not expected under ambient conditions.

25 ENERGY STORAGE↗
DOE OSTI2023

Hydropower Potential at Non-Powered Dams: A Multi-Criteria Decision Analysis Tool based on Grid, Community, Industry, and Environmental Impacts

Non-powered dams (NPDs) are dams that do not include hydraulic turbine (hydropower) equipment. Currently, there are more than 80,000 such dams in the United States, which provide a variety of non-energy benefits, including flood control, water supply, navigation, and recreation. Approximately 500 of these NPDs are identified as having the potential to add hydropower generation (totaling up to a capacity of more than 8200 MW). A large share of investment costs and environmental impacts of dam construction have already been incurred at these NPDs. Hence, adding power to the existing dam structure is hypothesized to be achieved at a lower cost, with less risk, and a shorter timeframe than the development required for new dam construction. The abundance of NPDs, the associated environmental favorability, and cost advantages, combined with the reliability, predictability, and dispatchability of hydropower, make NPDs a strong candidate in the nation’s renewable energy portfolio. To assess the NPD to hydropower conversion potential, in this study, we developed a GIS-based multi-criterial decision analysis tool, which allows users to rank these NPDs based on the grid, community, industry, and environmental impacts (i.e., GCIE impacts). This web-based interactive tool (developed using open-source Python and JavaScript) lets the user choose from a wide range of features to define each of the GCIE impact scores through a user-friendly graphical user interface. These features are related to dam operation, hydropower generation opportunity, power market economy, social vulnerability and risk, proximity to critical infrastructure and energy generating facilities, environmental concerns (air, water, and critical habitat), and exposure to natural hazards. The overall priority score of NPDs is calculated based on user-defined weights for each of the GCIE impact scores. Besides ranking NPDs, the tool can also be used to estimate the energy-storage feasibility (battery, hydrogen, and pump-storage hydropower) at each of the potential sites.

13 HYDRO ENERGY↗
DOE OSTI2015

Generalized gradient approximation exchange energy functional with correct asymptotic behavior of the corresponding potential

A new non-empirical exchange energy functional of the generalized gradient approximation (GGA) type, which gives an exchange potential with the correct asymptotic behavior, is developed and explored. In combination with the Perdew-Burke-Ernzerhof (PBE) correlation energy functional, the new CAP-PBE (CAP stands for correct asymptotic potential) exchange-correlation functional gives heats of formation, ionization potentials, electron affinities, proton affinities, binding energies of weakly interacting systems, barrier heights for hydrogen and non-hydrogen transfer reactions, bond distances, and harmonic frequencies on standard test sets that are fully competitive with those obtained from other GGA-type functionals that do not have the correct asymptotic exchange potential behavior. Distinct from them, the new functional provides important improvements in quantities dependent upon response functions, e.g., static and dynamic polarizabilities and hyperpolarizabilities. CAP combined with the Lee-Yang-Parr correlation functional gives roughly equivalent results. Consideration of the computed dynamical polarizabilities in the context of the broad spectrum of other properties considered tips the balance to the non-empirical CAP-PBE combination. Intriguingly, these improvements arise primarily from improvements in the highest occupied and lowest unoccupied molecular orbitals, and not from shifts in the associated eigenvalues. Those eigenvalues do not change dramatically with respect to eigenvalues from other GGA-type functionals that do not provide the correct asymptotic behavior of the potential. Unexpected behavior of the potential at intermediate distances from the nucleus explains this unexpected result and indicates a clear route for improvement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Beneficial effect of post-deposition treatment in high-efficiency Cu(In,Ga)Se{sub 2} solar cells through reduced potential fluctuations

World-record power conversion efficiencies for Cu(In,Ga)Se{sub 2} (CIGS) solar cells have been achieved via a post-deposition treatment with alkaline metals, which increases the open-circuit voltage and fill factor. We explore the role of the potassium fluoride (KF) post-deposition treatment in CIGS by employing energy- and time-resolved photoluminescence spectroscopy and electrical characterization combined with numerical modeling. The bulk carrier lifetime is found to increase with post-deposition treatment from 255 ns to 388 ns, which is the longest charge carrier lifetime reported for CIGS, and within ∼40% of the radiative limit. We find evidence that the post-deposition treatment causes a decrease in the electronic potential fluctuations. These potential fluctuations have previously been shown to reduce the open-circuit voltage and the device efficiency in CIGS. Additionally, numerical simulations based on the measured carrier lifetimes and mobilities show a diffusion length of ∼10 μm, which is ∼4 times larger than the film thickness. Thus, carrier collection in the bulk is not a limiting factor for device efficiency. By considering differences in doping, bandgap, and potential fluctuations, we present a possible explanation for the voltage difference between KF-treated and untreated samples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Local random potentials of high differentiability to model the Landscape

We generate random functions locally via a novel generalization of Dyson Brownian motion, such that the functions are in a desired differentiability class C{sup k}, while ensuring that the Hessian is a member of the Gaussian orthogonal ensemble (other ensembles might be chosen if desired). Potentials in such higher differentiability classes (k≥2) are required/desirable to model string theoretical landscapes, for instance to compute cosmological perturbations (e.g., k=2 for the power-spectrum) or to search for minima (e.g., suitable de Sitter vacua for our universe). Since potentials are created locally, numerical studies become feasible even if the dimension of field space is large (D∼100). In addition to the theoretical prescription, we provide some numerical examples to highlight properties of such potentials; concrete cosmological applications will be discussed in companion publications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗
DOE OSTI2019

Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data

The ever-increasing power of modern super-computers, along with the availability of highly scalable atomistic simulation codes, has begun to revolutionize predictive modeling of materials. In particular, molecular dynamics (MD) has led to breakthrough advances in diverse fields, including tribology, catalysis, sensing, and nanoparticle self-assembly. Furthermore, recent integration of MD simulations with X-ray characterization has demonstrated promise in real-time 3-D characterization of materials on the atomic scale. The popularity of MD is driven by its applicability at disparate length/time scales, ranging from ab initio MD (hundreds of atoms and tens of picoseconds) to all-atom classical MD (millions of atoms over microseconds), and coarse-grained (CG) models (micrometers and tens of microseconds). Nevertheless, a substantial gap persists between AIMD, which is highly accurate but restricted to extremely small sizes, and those based on classical force fields (atomistic and CG) with limited accuracy but access to larger length/time scales. The accuracy and predictive power of classical MD simulations is dictated by the empirical force fields, and their capability to capture the relevant physics. Here, we discuss some of our recent work on the use of machine learning (ML) to combine the accuracy and flexibility of electronic structure calculations with the speed of classical potentials. Our ML framework attempts to bridge the significant gulf that exists between the handful of research groups that develop new interatomic potential models (often requiring several years of effort), and the increasingly large user community from academia and industry that applies these models. Our data-driven approach represents significant departure from the status quo and involves several steps including generation and manipulation of extensive training data sets through electronic structure calculations, defining novel potential functional forms, employing state-of-the-art ML algorithms to formulate highly optimized training procedures, and subsequently developing user-friendly workflow tools integrating these algorithms on high-performance computers (HPCs). Our ML approach shows marked success in developing force fields for a wide range of materials from metals, oxides, nitrides, and heterointerfaces to two-dimensional (2D) materials.

Chan, Henry↗
DOE OSTI2021

A Comparison of Exact and Model Exchange–Correlation Potentials for Molecules

Accurate exchange–correlation (XC) potentials for three-dimensional systems–via solution of the inverse density functional theory (DFT) problem–are now available to test the quality of DFT approximations. Herein, the exact XC potential for seven molecules–dihydrogen at four different bond-lengths, lithium hydride, water, and ortho-benzyne–are computed from full configuration interaction reference densities. These are compared to model XC potentials from nonlocal (B3LYP, HSE06, SCAN0, and M08-HX) and semilocal/local (SCAN, PBE, and PW92) XC functionals. Whereas for most systems, relative errors in the ground-state densities are O(10 –3 –10 –2 ) , the model XC potentials have much higher errors of O(10 –1 –10 0 ) . Among the model XC functionals, SCAN0 offers the best agreement with the exact XC potential, underlining the significance of satisfying exact conditions as well as including nonlocal effects in XC functionals. This work indicates that tests against the exact XC potential will provide a promising new direction for building more accurate XC functionals for DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗