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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 OSTI2019

Impact of solutes on the lattice parameters and elastic stiffness coefficients of hcp Fe from first-principles calculations

The hexagonal close-packed (hcp) -martensite phase in steels nucleates from the -austenite parent phase and can undergo further transformation to the -martensite phase or exist as a metastable phase depending on temperature, mechanical loading, and alloy chemistry. The solute-dependent lattice parameters and elastic stiffness coefficients of hcp Fe influence the mechanical properties of steels containing the -martensite phase, as well as the martensitic transformations between the phases. We use density functional theory to calculate the lattice parameters and of single-crystal hcp Fe as functions of solute concentration in the dilute limit for the substitutional solutes Al, B, Cu, Mn, and Si, and the octahedral interstitial solutes C and N. Our computationally efficient methodology separates the solute dependence of the into lattice strain and chemical bonding contributions. The computed data can be used to estimate the effect of solutes on polycrystalline elastic moduli and the strain energy associated with martensitic transformations. The data can also serve as inputs to microstructure-based models of multiphase steels containing the -martensite phase.

Fellinger, Michael R.↗
DOE OSTI2020

A First–Principles–Based Sub–Lattice Formalism for Predicting Off–Stoichiometry in Materials for Solar Thermochemical Applications: The Example of Ceria

Theoretical models that reliably can predict off-stoichiometry in materials via accurate descriptions of underlying thermodynamics are crucial for energy applications. For example, transition-metal and rare-earth oxides that can tolerate a large number of oxygen vacancies, such as CeO 2 and doped CeO 2 , can split water and carbon dioxide via a two-step, oxide-based solar thermochemical (STC) cycle. The search for new STC materials with a performance superior to that of state-of-the-art CeO 2 can benefit from predictions accurately describing the thermodynamics of oxygen vacancies. The sub-lattice formalism, a common tool used to fit experimental data and build temperature-composition phase diagrams, can be useful in this context. Here, sub-lattice models are derived solely from zero-temperature quantum mechanics calculations to estimate fairly accurate temperature- and oxygen-partial-pressure-dependent off-stoichiometries in CeO 2 and Zr-doped CeO 2 . Physical motivations for deriving some of the “excess” sub-lattice model parameters directly from quantum mechanical calculations, instead of fitting to minimize deviations from experimental and/or theoretical data, are identified. As a result, important limitations and approximations of the approach used are specified and extensions to multi-cation oxides are also suggested to help identify novel candidates for water and carbon dioxide splitting and related applications.

08 HYDROGEN↗
DOE OSTI2019

Benchmarking the accuracy of coverage-dependent models: adsorption and desorption of benzene on Pt (111) and Pt 3 Sn (111) from first principles

Bimetallic catalysts have demonstrated properties favorable for upgrading biofuel through catalytic hydrodeoxygenation. However, the design and optimization of such bimetallic catalysts requires the ability to construct accurate, predictive models of these systems. To generate a model that predicts the kinetic behavior of benzene adsorbed on Pt (111) and a Pt 3 Sn (111) surface alloy (Pt 3 Sn (111)), the adsorption of benzene was studied for a wide range of benzene coverages on both surfaces using density functional theory (DFT) calculations. The adsorption energy of benzene was found to correlate linearly with benzene coverage on Pt (111) and Pt 3 Sn (111); both surfaces exhibited net repulsive lateral interactions. Through an analysis of the d-band properties of the metal surface, it was determined that the coverage dependence is a consequence of the electronic interactions between benzene and the surface. The linear coverage dependence of the adsorption energy allowed us to quantify the influence of the lateral interactions on the heat of adsorption and temperature programmed desorption (TPD) spectra using a mean-field model. A comparison of our simulated TPD to experiment showed that this mean-field model adequately reproduces the desorption behavior of benzene on Pt (111) and Pt 3 Sn (111). In particular, the TPD correctly exhibits a broadening desorption peak as the initial coverage of benzene increases on Pt (111) as well as and a low temperature desorption peak on Pt 3 Sn (111). Furthermore, due to the sensitivity of the TPD peak temperature to the desorption energy, precise alignment of experimental and theoretical TPD spectra demands an accurate calculation of the adsorption energy. Therefore, an analysis of the effect of the exchange-correlation functional on TPD modeling is presented. Through this work, we show the necessity of incorporating lateral interactions into theoretical models in order to correctly predict experimental behavior.

09 BIOMASS FUELS↗
DOE OSTI2019

Effect of Fe and Ti Substitution Doping on Magnetic Property of Monolayer CrSi{sub 2}: a First-Principle Investigation

First-principle calculations based on spin-polarized density functional theory were performed to investigate the effect of Fe and Ti substitution doping on magnetic property of monolayer CrSi{sub 2}. The electronic structures, binding energy, magnetic property, total and partial density of states, and spin density of monolayer CrSi{sub 2} are scientifically studied. Calculated binding energy reveals that Fe-doped monolayer CrSi{sub 2} is more stable than Ti-doped monolayer CrSi{sub 2}. The local magnetic moment of Fe and Ti atom all decrease compared with atomic moment in free gas phase due to variation of bond interaction and charge transfer. The density of states and spin-density results indicated that local magnetic moment of Fe atom is larger than Ti atom, leading to total magnetic moment of Fe-doped monolayer CrSi{sub 2} is bigger than Ti-doped monolayer CrSi{sub 2}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Phase Stability in U-6Nb Alloy Doped with Ti from the First Principles Theory

First-principles calculations within the density-functional-theory (DFT) approach are conducted in order to explore and explain the effect of small amounts of titanium on phase stability in the U-6Nb alloy. During rapid quenching from high to room temperature, metastable phases α' (orthorhombic), α" (monoclinic), and γ 0 (tetragonal) can form, depending on Nb concentration. Important mechanical properties depend on the crystal structure and, therefore, an understanding of the effect of impurities on phase stability is essential. Insights on this issue are obtained from quantum-mechanical DFT calculations. The DFT framework does not rely on any material-specific assumptions and is therefore ideal for an unbiased investigation of the U-Nb system.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian prior construction for uncertainty quantification in first-principles statistical mechanics

First-principles statistical mechanics enables the prediction of thermodynamic and kinetic properties of materials, but is computationally expensive. Many approaches require surrogate models to calculate energies within Monte Carlo or molecular dynamics simulations. Inexpensive surrogates such as cluster expansions enable otherwise intractable calculations by interpolating data from higher accuracy methods, such as Density Functional Theory (DFT). Surrogate models introduce uncertainty into downstream calculations, in addition to any uncertainty inherent to DFT calculations. Bayesian frameworks address this by quantifying uncertainty and incorporating expert knowledge through priors. However, constructing effective priors remains challenging. This work introduces and describes practical strategies for building Bayesian cluster expansions, focusing on basis truncation, hyperparameter selection, and ground state replication. We analyze multiple basis truncation schemes, compare cross-validation to the evidence-approximation for hyperparameter optimization, and provide methods to find and enforce ground-state-preserving models through priors. Additionally, we compare the uncertainties between different approximations to DFT (LDA, PBE, SCAN) against the uncertainty introduced with the use of cluster expansion surrogate models. These approaches are demonstrated on the BCC Li x Mg 1-x and Li x Al 1-x alloys, which are both of interest for solid-state Li batteries. Our results provide guidelines for constructing and utilizing Bayesian cluster expansions, thereby improving the transparency of materials modeling. Furthermore, the approaches and insights developed in this work can be transferred to a wide range of cluster expansion surrogate models, including the atomic cluster expansion and related machine-learned interatomic potential architectures.

Alloy theory↗
DOE OSTI2025

Optical properties of vacancies in aluminum oxide (𝛼−Al 2 ⁢O 3 ) from first principles

We employ first-principles calculations based on hybrid density functional theory to investigate the structural and optical properties of the oxygen vacancy (𝑉 O ) and aluminum vacancy (𝑉 Al ) in 𝛼−Al 2 ⁢O 3 , the most stable (corundum) phase of alumina. Our calculations facilitate the identification of experimental excitation and luminescence spectra with specific electronic transitions at the vacancy sites. The absorption line shape for excitation of an electron at 𝑉$^0_O$ to the conduction-band minimum (CBM) is in excellent agreement with the 6.1 eV band detected by optical absorption spectroscopy, and we find that the 5.9 eV absorption band is generated by an internal electron transition at 𝑉$^0_O$. We confirm that the slowly decaying 3.0 eV emission band of the 𝐹 center is due to a triplet-singlet transition at 𝑉$^0_O$. Our calculations also reveal that the 4.8 eV/5.4 eV absorption and 3.8 eV emission bands assigned to the 𝐹 + center are generated by internal transitions at 𝑉$^{+1}_O$. The line shape for the excitation of an electron from 𝑉$^{+1}_O$ to the CBM agrees well with an absorption band at 6.4 eV, while the recombination of an electron with 𝑉$^{+2}_O$ also produces luminescence around 3.8 eV, but with a considerably broader line shape. For Al vacancies, we confirm that the most prevalent configuration in 𝛼−Al 2 ⁢O 3 is a split-vacancy configuration 𝑉 Al,s , and we calculate migration barriers for different directions in the corundum crystal. We predict absorption and emission spectra for the excitation and recombination of an electron localized at 𝑉$^{−3}_{Al}$ and 𝑉$^{−3}_{Al,s}$ sites with the CBM. The line shapes of the two 𝑉 Al configurations overlap and are considerably broader than the spectra corresponding to 𝑉 O .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effects of cluster expansion on the locations of phase transition boundary as a first step to quantify uncertainty in first principles statistical mechanics framework

Predicting phase diagrams from first principle calculations eliminates the need of tedious experimental trials and errors. Fully automating first principle phase diagram calculations without any sort of human intervention has been a long daunting task and troubling scientific communities for decades. This grand problem remains not fully resolved, largely due to the vastly high-dimensional parameter space associated with density functional theory, cluster expansion, lattice Monte Carlo, and the substantial uncertainty propagating through a set of complex simulations. As a first step to tackle this grand problem, we reported a first demonstration of how sensitive phase boundary locations can be to various cluster expansion fittings and input DFT training data. To the best knowledge of the authors, this study reported the first ever attempt to quantify uncertainty in first principles statistical mechanics framework. In addition, a semi-automated phase transition detection algorithm has been devised in this paper to deal with the associated statistical errors and uncertainties from Monte Carlo method and its predecessor DFT calculations and cluster expansions. This algorithm has been applied in a classical cluster expansion Mg-Cd binary alloy system to detect phase transitions at various locations of phase diagram using different cluster expansions to demonstrate its predictive power and quantify uncertainties. The results suggested that using Chebyshev basis function shifted the transition locations toward the dilute solid solution phase and expanded the phase stability of concentrated ordered phases to wider composition range. The addition of perturbed defect configurations into training data set lowered the order-disorder transition temperature to be away from true transition temperature, suggesting the transition nature is indeed configurational disorder dominated rather than defect assisted. Finally, we found that the weighting has negligible effect on the transition locations, except for the case of using Chebyshev basis function to fit all non-weighted configurations that can be susceptible to Monte Carlo sampling hysteresis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Importance of charge self-consistency in first-principles description of strongly correlated systems

First-principles approaches have been successful in solving many-body Hamiltonians for real materials to an extent when correlations are weak or moderate. As the electronic correlations become stronger often embedding methods based on first-principles approaches are used to better treat the correlations by solving a suitably chosen many-body Hamiltonian with a higher level theory. The success of such embedding theories, often referred to as second-principles, is commonly measured by the quality of self-energy Σ which is either a function of energy or momentum or both. However, Σ should, in principle, also modify the electronic eigenfunctions and thus change the real space charge distribution. While such practices are not prevalent, some works that use embedding techniques do take into account these effects. In such cases, choice of partitioning, of the parameters defining the correlated Hamiltonian, of double-counting corrections, and the adequacy of low-level Hamiltonian hosting the correlated subspace hinder a systematic and unambiguous understanding of such effects. Further, for a large variety of correlated systems, strong correlations are largely confined to the charge sector. Then an adequate nonlocal low-order theory is important, and the high-order local correlations embedding contributes become redundant. Here we study the impact of charge self-consistency within two example cases, TiSe 2 and CrBr 3 , and show how real space charge re-distribution due to correlation effects taken into account within a first-principles Green’s function-based many-body perturbative approach is key in driving qualitative changes to the final electronic structure of these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetotransport in semiconductors and two-dimensional materials from first principles

Here we demonstrate a first-principles method to study magnetotransport in materials by solving the Boltzmann transport equation (BTE) in the presence of an external magnetic field. Our approach employs ab initio electron-phonon interactions and takes spin-orbit coupling into account. We apply our method to various semiconductors (Si and GaAs) and two-dimensional (2D) materials (graphene) as representative case studies. The magnetoresistance, Hall mobility, and Hall factor in Si and GaAs are in very good agreement with experiments. In graphene, our method predicts a large magnetoresistance, consistent with experiments. Analysis of the steady-state electron occupations in graphene shows the dominant role of optical phonon scattering and the breaking of the relaxation time approximation. Our paper provides a detailed understanding of the microscopic mechanisms governing magnetotransport coefficients, establishing the BTE in a magnetic field as a broadly applicable first-principles tool to investigate transport in semiconductors and 2D materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Ferroelectricity in [111]-oriented epitaxially strained SrTiO 3 from first principles

We use first-principles density-functional theory calculations to investigate the effect of biaxial strain in the low-temperature structural and ferroelectric properties of [111]-oriented SrTiO 3 . In this work we find that [111] biaxial strain, achievable by coherent epitaxial growth along the [111] direction, induces structural distortions in SrTiO 3 that are not present in either bulk or [001]-oriented SrTiO 3 . Under [111] biaxial strain, SrTiO 3 displays ferroelectricity at tensile strain, and paraelectricity at compressive strain. We compute the phonon spectrum and macroscopic polarization of SrTiO 3 as a function of [111] biaxial strain, and relate our results to the predictions of the free-energy phenomenological model of Pertsev, Tagantsev, and Setter

36 MATERIALS SCIENCE↗
DOE OSTI2022

CASM — A software package for first-principles based study of multicomponent crystalline solids

CASM is a software package that enables first-principles based studies of crystalline materials. It has been designed to treat coupled chemical, mechanical, vibrational, and magnetic degrees of freedom to determine ground state and finite temperature properties of crystals. The symmetry of the underlying parent crystal structure is used to enumerate perturbations of the parent crystal structure and generate derivative structures which can be input to first-principles calculations in order to explore the ground state energy landscape. CASM algorithmically constructs cluster expansions that fully couple discrete and continuous degrees of freedom, and generates highly efficient code to evaluate the cluster expansion basis functions. Widely used machine learning methods are integrated for fitting expansion coefficients to first-principle calculations. The fully parameterized cluster expansions can be combined with (kinetic) Monte Carlo methods to calculate finite temperature thermodynamic and kinetic properties. CASM Alloy Manager identifies distinct parent crystal structures in an alloy system, creating individual projects for each, and integrating the results. The integrated infrastructure facilitates the linkage between first-principles statistical mechanics predictions with higher length scale computational methods, such as phase field simulations. In conclusion, CASM projects are designed to be easy to share in repositories, to re-use, and to extend to include additional chemical species or types of degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Application of First-Principles-Based Artificial Neural Network Potentials to Multiscale-Shock Dynamics Simulations on Solid Materials

The use of artificial neural network (ANN) potentials trained with first-principles calculations has emerged as a promising approach for molecular dynamics (MD) simulations encompassing large space and time scales while retaining first-principles accuracy. To date, however, the application of ANN-MD has been limited to near-equilibrium processes. Here we combine first-principles-trained ANN-MD with multiscale shock theory (MSST) to successfully describe far-from-equilibrium shock phenomena. Overall, our ANN-MSST-MD approach describes shock-wave propagation in solids with first-principles accuracy but a 5000 times shorter computing time. Accordingly, ANN-MD-MSST was able to resolve fine, long-time elastic deformation at low shock speed, which was impossible with first-principles MD because of the high computational cost. This work thus lays a foundation of ANN-MD simulation to study a wide range of far-from-equilibrium processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

First-Principles Cost Analysis of Advanced High-Temperature Nuclear Plants

Due to the vast number of recent nuclear reactor innovations, particularly those pertaining to generation IV reactor types like high-temperature gas cooled reactors (HTGRs) and sodium-cooled fast reactors (SFRs), and the newer deployment strategies envisioned, such as use of small modular reactors (SMRs) or even microreactors, reliable, detailed, and complete costs of these nuclear innovations are needed in wide availability. The types of models that generally achieve these objectives are those incorporating the fundamental nature of the real-world systems they aspire to predict, such as first-principles models. Furthermore, first principles models typically offer predictiveness that is not attained by most other types of individual-models. However, detailed, first-principles cost modeling of nuclear reactors and entire nuclear plants is relatively limited. To address this limitation in the availability of detailed, predictive models based on fundamentals, we recently developed a range of cost models, mostly based on first-principles methodologies, to project full lifecycle costs (LCCs) of nuclear power plants (NPPs) based on multiple parallel SM-HTG-pebble bed reactors (PBRs) and SM-SFRs.

Prosser, Jacob H. [Strategic Analysis, Inc., Arlin↗
DOE OSTI2025

First-Principles Cost Analysis of Advanced High-Temperature Nuclear Plants

Due to the vast number of recent nuclear reactor innovations, particularly those pertaining to generation IV reactor types like high-temperature gas cooled reactors (HTGRs) and sodium-cooled fast reactors (SFRs), and the newer deployment strategies envisioned, such as use of small modular reactors (SMRs) or even microreactors, reliable, detailed, and complete costs of these nuclear innovations are needed in wide availability. The types of models that generally achieve these objectives are those incorporating the fundamental nature of the real-world systems they aspire to predict, such as first-principles models. Furthermore, first principles models typically offer predictiveness that is not attained by most other types of individual-models. However, detailed, first-principles cost modeling of nuclear reactors and entire nuclear plants is relatively limited. To address this limitation in the availability of detailed, predictive models based on fundamentals, we recently developed a range of cost models, mostly based on first-principles methodologies, to project full lifecycle costs (LCCs) of nuclear power plants (NPPs) based on multiple parallel SM-HTG-pebble bed reactors (PBRs) and SM-SFRs.

Prosser, Jacob H. [Strategic Analysis, Inc., Arlin↗
DOE OSTI2020

Charge-transfer satellites and chemical bonding in photoemission and x-ray absorption of SrTi O 3 and rutile Ti O 2 : Experiment and first-principles theory with general application to spectroscopic analysis

First-principles, real-time-cumulant, and Bethe-Salpeter-equation calculations fully capture the detailed satellite structure that occurs in response to the sudden creation of the core hole in both photoemission and x-ray absorption spectra of the transition-metal compounds SrTi O 3 and rutile Ti O 2 . Analysis of the excited-state, real-space charge-density fluctuations betrays the physical nature of these many electron excitations that are shown to reflect the materials’ solid-state electronic structure and chemical bonding. This first-principles development of the cumulant-based core hole spectral function is generally applicable to other systems and should become a standard tool for all similar spectroscopic analysis going beyond the quasiparticle physics of the photoelectric effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗