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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 OSTI2021

Probing the exact form and doping preference of magnesium in ordinary Portland cement clinker phases: A study from experiments and DFT simulations

Highlights: • The doping behaviors of Mg in OPC clinker phases were systematically studied. • About 1.3 wt% MgO enter OPC clinker phases by forming substitutional solid solutions. • In the 4 composed minerals, C{sub 3}S, C{sub 3}A and C{sub 4}AF can host more Mg ions than C{sub 2}S. • Mg ions prefer to replace Ca in C{sub 3}S, C{sub 2}S and C{sub 3}A while replace Fe and Ca in C{sub 4}AF. • Both the large structure distortions and formation energies governs the low solubility. A systematic study was performed to learn the exact existence form and doping behaviors of magnesium in ordinary Portland cement (OPC) clinker. Our results show that about 1.3 wt% MgO incorporates into OPC clinker phases by forming substitutional solid solutions while excess Mg accumulate and exist as periclase. Results from Rietveld refinement present a substitution preference in C{sub 3}S and C{sub 3}A over C{sub 2}S. More in-depth analyses from density function theoretical simulations show that in C{sub 3}S, C{sub 2}S and C{sub 3}A, the substitution occurs by replacing Ca while in C{sub 4}AF, it probably occurs by substituting Fe and Ca ions. The large structure distortions and sharp increase in formation energies with increasing MgO determines its low solubility. This work provides a clear understanding of the existence states and the intrinsic mechanism governing doping behaviors of Mg, thus should be very important in guiding the synthesis of OPC clinker by utilizing high-Mg limestone.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 4a Raw Data

Calculated formation energy of (0001 ̅) c-plane GaN surfaces. The density-functional theory (DFT) calculations were performed with the generalized gradient approximation, using the plane-wave pseudopotential quantum-ESPRESSO package. Ultrasoft pseudopotentials were used to describe the interaction between valence electrons and ionic cores, where Ga 3d electrons were explicitly treated as valence electrons. The wave functions and electronic density were expanded in a plane-wave basis set truncated at a cutoff energy of 30 Ry and 240 Ry, respectively. The surface was modeled using a repeated slab geometry using a (2×2) unit cell with a thickness of seven GaN bilayers, where the Ga-terminated bottom side was passivated by pseudo-hydrogen with charge of 1.25e. In addition, the (1010) surface was modeled using 8 GaN atomic layers with a lateral dimension of 9.57 Å x 10.38 Å. A vacuum width of at least 15.0 Å was introduced between consecutive slabs, and a k-point mesh of 5x5x1 and 2x2x1 was used to sample the surface Brillouin zone for the polar and non-polar surfaces, respectively. Calculated formation energy of (0001 ̅) c-plane GaN surfaces with different oxygen configuration within the anion and cation-rich limits: ideal GaN surfaces of c-plane and m-plane; configurations with 100% replacement of nitrogen by oxygen on the surface c-plane and m-plane; 100% replacement of nitrogen by oxygen in the subsurface bilayer c-plane and m-plane; and configurations with 50% replacement of nitrogen of the surface and subsurface bilayers by oxygens c-plane and m-plane. In both cases, the ideal surface is chosen as the reference.

photocathode↗
DOE OSTI2021

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 4b Raw Data

Calculated formation energy of (1010 ̅) m-plane GaN surfaces. The density-functional theory (DFT) calculations were performed with the generalized gradient approximation, using the plane-wave pseudopotential quantum-ESPRESSO package. Ultrasoft pseudopotentials were used to describe the interaction between valence electrons and ionic cores, where Ga 3d electrons were explicitly treated as valence electrons. The wave functions and electronic density were expanded in a plane-wave basis set truncated at a cutoff energy of 30 Ry and 240 Ry, respectively. The surface was modeled using a repeated slab geometry using a (2×2) unit cell with a thickness of seven GaN bilayers, where the Ga-terminated bottom side was passivated by pseudo-hydrogen with charge of 1.25e. In addition, the (1010) surface was modeled using 8 GaN atomic layers with a lateral dimension of 9.57 Å x 10.38 Å. A vacuum width of at least 15.0 Å was introduced between consecutive slabs, and a k-point mesh of 5x5x1 and 2x2x1 was used to sample the surface Brillouin zone for the polar and non-polar surfaces, respectively. Calculated formation energy of (1010 ̅) m-plane GaN surfaces with different oxygen configuration within the anion and cation-rich limits: ideal GaN surfaces of c-plane and m-plane; configurations with 100% replacement of nitrogen by oxygen on the surface c-plane and m-plane; 100% replacement of nitrogen by oxygen in the subsurface bilayer c-plane and m-plane; and configurations with 50% replacement of nitrogen of the surface and subsurface bilayers by oxygens c-plane and m-plane. In both cases, the ideal surface is chosen as the reference.

photocathode↗
DOE OSTI2024

Assessment of uranium nitride interatomic potentials

Uranium mononitride (UN) is a promising nuclear fuel due to its high fissile density, high thermal conductivity, and suitability for reprocessing. In this study, two uranium nitride interatomic potentials are assessed: Tseplyaev and Starikov's angular-dependent potential and Kocevski et al.'s embedded atom model potential. Predictions of the thermophysical and elastic properties of UN, UN 2 , and α- and β-U 2 N 3 computed using both potentials are assessed and compared to available experimental data. Notably, the Tseplyaev potential performs better with the energetic aspects of UN, e.g., specific heat capacity and point defect formation energies, whereas the Kocevski potential performs better with the structural aspects of UN, e.g., thermal expansion as well as with the elastic properties. The reasons why the Kocevski potential underestimates the UN specific heat are explained by examining the UN phonon properties modeled using both potentials. The Kocevski potential shows better identification of the mechanical stability ranges of UN, UN 2 , and α- and β-U 2 N 3 , reasonably predicting the melting point of UN and predicting stable structures for UN 2 and α- and β-U 2 N 3 . On the other hand, the Tseplyaev potential predicts a premature phase change of both UN and UN 2 and cannot stabilize α- nor β-U 2 N 3 . However, the Kocevski potential cannot predict a stable α-U phase and is thus not suitable for the calculation of formation energies for non-stoichiometric point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Cation and anion topotactic transformations in cobaltite thin films leading to Ruddlesden-Popper phases.

Topotactic transformations involve structural changes between related crystal structures due to a loss or gain of material while retaining a crystallographic relationship. The perovskite oxide La0.7Sr0.3CoO3 (LSCO) is an ideal system for investigating phase transformations due to its high oxygen vacancy conductivity, relatively low oxygen vacancy formation energy, and strong coupling of the magnetic and electronic properties to the oxygen stoichiometry. While the transition between cobaltite perovskite and brownmillerite (BM) phases has been widely reported, further reduction beyond the BM phase lacks systematic studies. In this paper, we study the evolution of the physical properties of LSCO thin films upon exposure to highly reducing environments. We observe the rarely reported crystalline Ruddlesden-Popper phase, which involves the loss of both oxygen anions and cobalt cations upon annealing where the cobalt is found as isolated Co ions or Co nanoparticles. First-principles calculations confirm that the concurrent loss of oxygen and cobalt ions is thermodynamically possible through an intermediary BM phase. The strong correlation of the magnetic and electronic properties to the crystal structure highlights the potential of utilizing ion migration as a basis for emerging applications such as neuromorphic computing.

Chiu, I-Ting↗
DOE OSTI2025

Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks

Thermochemical water-splitting (TCH) based on 2-step thermal redox cycles in metal oxides is a promising approach to generating H 2 , but state-of-the-art (SOTA) CeO 2 has several practical limitations, which has motivated continued materials discovery efforts in this field. Here, in this study, we improve upon a SOTA defect graph neural network (dGNN) surrogate model's oxygen vacancy predictions and combine them with materials project phase diagrams to down-select and discover structurally diverse, experimentally known metal oxides whose TCH performance was previously unknown. Amongst twelve candidates selected based on our high-throughput screening and down-selection criteria, we achieved ∼80% accuracy in identifying materials with stable redox cycling and hydrogen production in stagnation flow reactor water-splitting experiments. Closer to 100% accuracy can be achieved if higher-accuracy, hybrid DFT-predicted vacancy formation energies were computed and used in lieu of the most uncertain dGNN-based screening predictions, as they correct false positives to true negatives. Notably, two discovered candidates, Sr 3 PrMn 2 O 8 and Ba 2 Fe 2 O 5 , display hydrogen yields greater than CeO 2 under specific redox conditions. In conclusion, these results demonstrate our ability to computationally predict and experimentally validate promising candidate TCH materials that have the potential to compete with CeO 2 .

08 HYDROGEN↗
DOE OSTI2025

A quality-agnostic combinatoric cost estimation model for large-format directed energy deposition metal additive manufacturing

Directed energy deposition (DED) additive manufacturing (AM) processes are amenable to synergistic combination into multi-process AM systems due to similar requirements for automation and energy sources. This work analyzes the economic performance of such DED AM systems from a quality-agnostic combinatoric standpoint with a model that calculates lowest-cost system combinations based on part geometry and process performance metrics. Common DED AM systems research focuses on a single process and does not consider the process, system, and application in the context of all possible system combinations (e.g., the combined set of process selection(s), motion system(s), and process hardware), leading to limited applicability of the resulting DED AM systems to cost-sensitive components such as those found in energy generation applications. The model developed herein incorporates the capital, material, and energy costs associated with DED AM system combinations into a predictive tool for estimating part and system cost, the output of which is intended to guide deployment of finite research and development resources towards DED AM system combinations with the lowest costs and greatest likelihood of economic impact. The DED AM systems identified by this framework may enable domestic production of the large conventionally cast and forged components necessary for energy generation.

Shanafield, Alexandra [ORNL]↗
DOE OSTI2023

Interplay between Facets and Defects during the Dissociative and Molecular Adsorption of Water on Metal Oxide Surfaces

Both surface terminations and defects play a central role in determining how water interacts with metal oxides, thereby setting important properties of the interface that govern reactivity such as the type and distribution of hydroxyl groups. However, the interconnections between facets and defects remain poorly understood, limiting the usefulness of conventional notions such as that hydroxylation is controlled by metal cation exposure at the surface. Here, using hematite (α-Fe 2 O 3 ) as a model system, we show how oxygen vacancies overwhelm surface cation-dependent hydroxylation behavior. Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy was used to monitor the adsorption of molecular water and its dissociation to form hydroxyl groups in situ on (001), (012), or (104) facet-engineered hematite nanoparticles. Supported by density functional theory calculations of the respective surface energies and oxygen vacancy formation energies, the findings show how oxygen vacancies are more prone to form on higher energy facets and induce surface hydroxylation at extremely low relative humidity values of 5 x10 - 5 %. Further, when these vacancies are eliminated, the extent of surface hydroxylation across the facets is as expected from the areal density of exposed iron cations at the surface. These findings help answer fundamental questions about the nature of reducible metal oxide-water interfaces in natural and technological settings and lay the groundwork for rational design of improved oxide-based catalysts.

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

Visualizing temperature-dependent phase stability in high entropy alloys

High entropy alloys (HEAs) contain near equimolar amounts of five or more elements and are a compelling space for materials design. In the design of HEAs, great emphasis is placed on identifying thermodynamic conditions for single-phase and multi-phase stability regions, but this process is hindered by the difficulty of navigating stability relationships in high-component spaces. Traditional phase diagrams use barycentric coordinates to represent composition axes, which require ( N – 1) spatial dimensions to represent an N -component system, meaning that HEA systems with N > 4 components cannot be readily visualized. Here, we propose forgoing barycentric composition axes in favor of two energy axes: a formation-energy axis and a ‘reaction energy’ axis. These Inverse Hull Webs offer an information-dense 2D representation that successfully captures complex phase stability relationships in N ≥ 5 component systems. We use our proposed diagrams to visualize the transition of HEA solid-solutions from high-temperature stability to metastability upon quenching, and identify important thermodynamic features that are correlated with the persistence or decomposition of metastable HEAs.

Chemistry↗
DOE OSTI2024

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗
DOE OSTI2023

An Efficient Reactive Force Field without Explicit Coordination Dependence for Studying Caustic Aluminum Chemistry

Reactive force fields (RFFs) are an expedient approach to sample chemical reaction paths in complex systems, relative to density functional theory. However, there is continued need to improve efficiencies, specifically in systems that have slow transverse degrees of freedom, as in highly viscous and superconcentrated solutions. Here, we present an RFF that is differentiated from current models (e.g., ReaxFF) by omitting explicit dependence on the atom coordination and employing a small parameter set based on Lennard-Jones, Gaussian, and Stillinger–Weber potentials. In this study, the model was parametrized from AIMD simulation data and is used to model aluminate reactivity in sodium hydroxide solutions with extensive validation against experimental radial distribution functions, computed free energy profiles for oligomerization, and formation energies. In conclusion, the model enables simulation of early stage Al(OH) 3 nucleation which has significant relevance to industrial processing of aluminum and has a computational cost that is reduced by 1 order of magnitude relative to ReaxFF.

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

Machine-Learning-Guided Insights into Solid-Electrolyte Interphase Conductivity: Are Amorphous Lithium Fluorophosphates the Key?

Despite decades of study, the identity of the dominant Li + -conducting phase within the inorganic SEI of Li-ion batteries remains unresolved. While the mosaic model describes LiF/Li 2 O/Li 2 CO 3 nanocrystallites within a disordered matrix, these crystalline phases inherently offer limited ionic conductivity. Growing evidence suggests that interfaces, grain boundaries, and amorphous phases may instead host the primary fast-ion pathways. Using diffusion-based generative structure prediction and machine-learning interatomic potentials (MLIPs), we investigate lithium difluorophosphate (LiPO 2 F 2 ), a key mixed-anion decomposition product of phosphorus- and fluorine-containing electrolytes. We identify a stable crystalline polymorph and demonstrate that the amorphous counterpart is conductive, with projected room-temperature σ ≈ 0.18 mS cm –1 and E a ≈ 0.40 eV. Here, this enhancement stems from structural disorder flattening the Li site-energy landscape and a low formation energy for Li-interstitial defects, which supplies additional mobile carriers. We propose amorphous mixed-anion Li-P-O-F phases as a promising conducting medium in the SEI, offering a specific target for engineering improved battery interfaces.

Zhong, Peichen [University of California, Berkeley↗
DOE OSTI2020

The role of ligands in atomically precise nanocluster-catalyzed CO2 electrochemical reduction

Ligand effects are of major interest in catalytic reactions owing to their potential critical role in determining the reaction activity and selectivity. Herein, we report ligand effects in the CO 2 electrochemical reduction reaction at the atomic level with three unique Au 25 nanoclusters comprising the same kernel but different protecting ligands (–XR, where X = S or Se, and R represents the carbon tail). It is observed that a change in the carbon tail shows no obvious impact on the catalytic selectivity and activity, but the anchoring atom (X = S or Se) strongly affects the electrocatalytic selectivity. Specifically, the S site acts as the active site and sustains CO selectivity, while the Se site shows a higher tendency of hydrogen evolution. Density functional theory (DFT) calculations reveal that the energy penalty associated with the *COOH formation is lower on the S site by 0.26 eV compared to that on the Se site. Additionally, the formation energy of the product (*CO) is lower on the sulfur-based Au nanocluster by 0.43 eV. Furthermore, we attribute these energetic differences to the higher electron density on the sulfur sites of the Au nanocluster, resulting in a modified bonding character of the reaction intermediates that reduce the energetic penalty for the *COOH and *CO formation. Overall, this work demonstrates that S/Se atoms at the metal–ligand interface can play an important role in determining the overall electrocatalytic performance of Au nanoclusters.

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

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2026

Optimization of Random Phase Approximation Calculations for Improved Energies of Molecules, Solids, and Surfaces

We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA through an optimized choice of reference orbitals and energy components, rather than a modification of the RPA correlation functional itself. The method employs an empirically constructed hybrid functional to generate DFT orbitals to evaluate the RPA correlation energy, which is then scaled by a constant. Comprehensive benchmarks across molecules, bulk solids, and surface systems demonstrate that optRPA26 consistently achieves high accuracy, with mean absolute errors of 0.05 eV for W4-11-RE reaction energies, 0.07 eV for cohesive energies, 0.09 eV for metal oxide formation energies, 0.11–0.12 eV for adsorption of small molecules on metals, and 0.06 eV for adsorption on oxides. In addition, optRPA26 correctly captures phase stability in metal oxides and magnetic metals. The optRPA26 approach can be run using standard RPA implementations, highlighting its potential as a general-purpose reference method that can accurately capture covalent, ionic, metallic, and van der Waals bonding in molecules, solids, and interfaces.

Adsorption↗
DOE OSTI2020

Density functional theory calculation of helium segregation and decohesion effect in W110/Ni111 interphase boundary

Density functional theory (DFT) is employed to study the preferential distribution and decohesion effect of He in a W-NiFe composite consisting of W particles embedded in an Ni-based solid solution matrix. A slab containing {110}<100>W//{111}<110>Ni interface is employed as a surrogate model for the W-NiFe system. Firstly, the fracture energy of the W/Ni interphase boundary (IB) (4.37 J/m 2 ) is higher than the cleavage energy of Ni{111} (3.82 J/m^2) and lower than the cleavage energy of W{110} (6.60 J/m 2 ). The comparison shows that the cohesion of the IB is stronger than the Ni{111} planes that are away from the IB. However, the cohesion between the Ni{111} planes adjacent to the IB is found to be the weakest in this system, with a cleavage energy of 3.11 J/m 2 . Subsequently, formation energy of He is calculated in the Ni slab, W slab, and various interstitial sites in the IB. The DFT calculations show that He is significantly more stable in Ni than in W, by about 1.75 eV. Interestingly, He does not prefer to segregate at the IB as compared to bulk Ni. Nevertheless, it prefers to segregate to the region between the Ni{111} planes adjacent to the IB, and decreases the cohesion of the already weakest region. Based on an estimated amount of He gas production in 5 years under first wall neutron irradiation (neutron flux of 1.04x10 15 n/cm 2 /s), the He will decrease the cleavage energy of the weakest region by 21.2%, 15.4%, and 12.2% at 800, 1000, and 1200 C, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Structural anisotropy in Sb thin films

Sb thin films have attracted wide interest due to their tunable band structure, topological phases, high electron mobility, and thermoelectric properties. We successfully grow epitaxial Sb thin films on a closely lattice-matched GaSb(001) surface by molecular beam epitaxy. We find a novel anisotropic directional dependence on their structural, morphological, and electronic properties. The origin of the anisotropic features is elucidated using first-principles density functional theory (DFT) calculations. The growth regime of crystalline and amorphous Sb thin films was determined by mapping the surface reconstruction phase diagram of the GaSb(001) surface under Sb 2 flux, with confirmation of structural characterizations. Crystalline Sb thin films show a rhombohedral crystal structure along the rhombohedral (211) surface orientation parallel to the cubic (001) surface orientation of the GaSb substrate. At this coherent interface, Sb atoms are aligned with the GaSb lattice along the [1̄10] crystallographic direction but are not aligned well along the [110] crystallographic direction, which results in anisotropic features in reflection of high-energy electron diffraction patterns, misfit dislocation formation, surface morphology, and transport properties. Our DFT calculations show that the preferential orientation of the rhombohedral Sb (211) plane may originate from the GaSb surface, where Sb atoms align with the Ga and Sb atoms on the reconstructed surface. The formation energy calculations confirm the stability of the experimentally observed structures. Our results provide optimal film growth conditions for further studies of novel properties of Bi 1-x Sb x thin films with similar lattice parameters and an identical crystal structure, as well as functional heterostructures of them with III–V semiconductor layers along the (001) surface orientation, supported by a theoretical understanding of the anisotropic film orientation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Highly Selective Electrocatalytic Reduction of CO 2 into Methane on Cu–Bi Nanoalloys

Methane (CH 4 ), the main component of natural gas, is one of the most valuable products facilitating energy storage via electricity conversion. However, the poor selectivity and high overpotential for CH 4 formation with metallic Cu catalysts prevent realistic applications. Introducing a second element to tune the electronic state of Cu has been widely used as an effective method to improve catalytic performance, but achieving high selectivity and activity toward CH 4 remains challenging. Here, we successfully synthesized Cu–Bi NPs, which exhibit a CH 4 Faradaic efficiency (FE) as high as 70.6% at -1.2 V versus reversible hydrogen electrode (RHE). The FE of Cu–Bi NPs has increased by approximately 25-fold compared with that of Cu NPs. DFT calculations showed that alloying Cu with Bi significantly decreases the formation energy of *COH formation, the rate-determining step, which explains the improved performance. Further analysis showed that Cu that has been partially oxidized because of electron withdrawal by Bi is the most possible active site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗