Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Vacancy Formation Energy”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

LaMnO 3 Dopants for Efficient Thermochemical Water Splitting Identified by Density Functional Theory Calculations

While ceria is the standard material for two-step water splitting, perovskites are emerging as viable alternatives. In this work, based on the orthorhombic LaMnO 3 supercell, we substitute Li Na K Rb Mg Ca Sr Ba on the A-sites (La sites) and Al Ga In Mg Zn on the B-sites (Mn sites) at a concentration of 37.5%. The range of temperature and oxygen partial pressure at which each composition is stable is predicted. For compositions that are stable in relevant temperature and pressure ranges, the oxygen vacancy formation energies are determined for all of the oxygen vacancy site positions available in the computational supercell. Mg, Ca, Sr, and Ba A-site-substituted LaMnO 3 and Al and In B-site-substituted LaMnO 3 meet these two criteria for candidates in solar-thermal water splitting applications. Finally, oxygen vacancy formation energy can also be controlled by adjusting the doping strategy.

08 HYDROGEN↗
DOE OSTI2023

Can a deep-learning model make fast predictions of vacancy formation in diverse materials?

The presence of point defects, such as vacancies, plays an important role in materials design. Here, we explore the extrapolative power of a graph neural network (GNN) to predict vacancy formation energies. We show that a model trained only on perfect materials can also be used to predict vacancy formation energies (E vac ) of defect structures without the need for additional training data. Such GNN-based predictions are considerably faster than density functional theory (DFT) calculations and show potential as a quick pre-screening tool for defect systems. To test this strategy, we developed a DFT dataset of 530 E vac consisting of 3D elemental solids, alloys, oxides, semiconductors, and 2D monolayer materials. We analyzed and discussed the applicability of such direct and fast predictions. We applied the model to predict 192 494 E vac for 55 723 materials in the JARVIS-DFT database. Our work demonstrates how a GNN-model performs on unseen data.

2D materials↗
DOE OSTI2022

Engineering defect energy landscape of CoCrFeNi high-entropy alloys by the introduction of additional dopants

The concept of high-entropy alloys (HEAs) focusing on tuning the overall chemical complexity represents a novel alloy design strategy. In contrast, alloying of a metallic matrix with minor doping elements with limited and localized tunability has been a common practice to improve material performance. Combining the idea of globally engineering defect energy landscape in HEAs and the localized doping strategy in dilute alloys, in this work, we explore doping effects of minor elements in a HEA matrix to further enhance the overall and localized chemical tunability, aiming to improve its irradiation resistance. Specifically, we study the influence of minor Al, Cu, Ti, and Pd substitutional doping elements on defect energetics in a CoCrFeNi model HEA based on density-functional theory (DFT) calculations. The DFT results indicate that the formation and migration energies of vacancies can be strongly influenced when a dopant is introduced at the first nearest neighbor shells around a vacancy. On the other hand, interstitial energetics are only slightly affected. Among the four elements, Ti and Pd generally decrease vacancy formation energies and increase vacancy migration energies more significantly than Al and Cu. The doping effects become more pronounced when the concentration of the substitutional dopants increases. Based on the energy distributions obtained from DFT, we build a kinetic Monte Carlo (kMC) model to assess the impact of dopants on vacancy-mediated diffusivity in the doped HEAs. Our results suggest that Ti and Pd can lower the tracer diffusivity in the considered HEAs and act as trapping sites, whereas Cu may enhance the atomic transport. This work indicates that substitutional doping in HEAs is an effective strategy in metallurgy to further tune the defect and transport properties of complex alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1992

Energetics and structural properties of twist grain boundaries in Cu

Structural and energetics properties of atoms near a grain boundary are of great importance from theoretical and experimental standpoints. From various experimental work it is concluded that diffusion at low temperatures at polycrystalline materials take place near grain boundary. Experimental and theoretical results also indicate changes of up to 70 percent in physical properties near a grain boundary. The Embedded Atom Method (EAM) calculations on structural properties of Au twist grain boundaries are in quite good agreement with their experimental counterparts. The EAM is believed to predict reliable values for the single vacancy formation energy as well as migration energy. However, it is not clear whether the EAM functions which are fitted to the bulk properties of a perfect crystalline solid can produce reliable results on grain boundaries. One of the objectives of this work is to construct the EAM functions for Cu and use them in conjunction with the molecular static simulation to study structures and energetics of atoms near twist grain boundaries in Cu. This provides tests of the EAM functions near a grain boundary. In particular, we determine structure, single vacancy formation energy, migration energy, single vacancy activation energy, and interlayer spacing as a function of distance from grain boundary. Our results are compared with the available experimental and theoretical results from grain boundaries and bulk.

Karimi, Majid↗
DOE OSTI2026

Atomistic modeling of lanthanide diffusion in refractory body-centered cubic molybdenum

Lanthanide fission products can strongly interact with candidate cladding alloys, but their transport properties in refractory metals remain poorly understood. Here, in this work, we investigate the atomic-scale diffusion behavior of La, Ce, Pr, and Nd in body-centered cubic (bcc) molybdenum, a potential candidate for advanced nuclear cladding. Self-consistent mean-field transport modeling is performed to evaluate the fission product transport and vacancy mobility, informed by first-principles and nudged elastic band calculations of vacancy formation energies, migration barriers, and solute–vacancy binding characteristics. Compared with bcc Fe, lanthanide solutes in bcc Mo exhibit slower tracer diffusion due to higher vacancy formation and migration energies. Furthermore, the calculations reveal that the influence of fission products on migration barriers in bcc Mo are not as extensive in range compared to bcc Fe. Among the studied lanthanides, La exhibits the strongest vacancy binding while also being the fastest diffuser in Mo. These findings highlight how refractory bcc alloys can reduce fission product infiltration, offering valuable insight into the development of durable cladding systems for advanced reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Unusual aliovalent doping effects on oxygen non-stoichiometry in medium-entropy compositionally complex perovskite oxides

Aliovalent doping of perovskite oxides can tune the oxygen vacancy formation energy. This work discovers normal vs. abnormal aliovalent doping effects on redox behaviors in medium-entropy compositionally complex perovskite oxides (CCPOs) (La 1–x Sr x )(Mn 1/3 Fe 1/3 Ti 1/3 )O 3–δ (LS_MFT) vs. (La 1–x Sr x )(Mn 1/3 Fe 1/3 Cr 1/3 )O 3–δ (LS_MFC). In the LS_MFC series, the oxygen non-stoichiometry range Δδ (= δ red – δ ox ) linearly depends on the Sr molar ratio x, while the LS_MFT series shows a V-shape dependence of Δδ on x. This unusual observation is investigated and explained based on the analysis of the energy loss near edge structure (ELNES) in STEM electron energy loss spectroscopy, along with density functional theory (DFT) calculations. In LS_MFC, Cr–L 2,3 , Mn–L 2,3 and Fe–L 2,3 peaks have a similar linear shift to higher energy with increasing x, which indicates higher oxidation states of Cr, Mn, and Fe with lower oxygen vacancy formation energies. In LS_MFT, the V-shape of the Δδ vs. x curve is caused by the stable Ti 4+ state and a V-shape Mn/Fe valency dependence on x. Furthermore, this study suggests the possible existence of different (including unexpected) coupled aliovalent doping effects in CCPOs with multiple B-site redox active elements.

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

Machine learning pipeline to predict defect behavior in metallic alloy systems

The interaction between defect and solute atoms is critical to the thermodynamic and kinetic behavior of metallic alloys under exposure to high-energy radiation, causing irradiation damage in materials. Radiation can generate non-equilibrium concentrations of point defects such as vacancies and interstitials. The excess point defects not only accelerate diffusional processes such as precipitation that cause radiation embrittlement, but also change the pathway of phase transformations, including nucleation processes. Understanding these defect behaviors is complicated by the challenge and complexity of addressing each possible local and discrete distribution of environments and chemical interactions around targeted defects-solute or solute-solute complexes. To resolve the challenge, machine learning regression techniques have emerged as powerful tools that can train and construct an energy model to accurately describe the chemical interactions of solutes and defects. In Fiscal Year 2022, the work focused on the workflow development and demonstration using machine learning regression, density functional theory, cluster expansion, and Monte Carlo simulation to predict the effects of ternary solute elements (e.g., aluminum and molybdenum) and point defects on the Cr-rich $\alpha^{\prime}$ precipitation in multicomponent FeCr model alloys. The computational outcomes include the prediction of the ternary phase diagram, vacancy formation energy for different compositions, and the effect of vacancies on the nucleation of Cr-rich clusters. The simulations predict a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from $\alpha^{\prime}$ precipitates. Additionally, the simulations show the formation of Cr-vacancy clusters as the initial nuclei for stable nucleation and growth of $\alpha^{\prime}$ particles. The results demonstrate important outcomes and applications of using machine learning pipeline to study model or commercial alloys with multicomponent solute species and point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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↗
NASA NTRS2015

Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

Ytterbium disilicate is of interest as a potential environmental barrier coating for aerospace applications, notably for use in next generation jet turbine engines. In such applications, the transport of oxygen and water vapor through these coatings to the ceramic substrate is undesirable if high temperature oxidation is to be avoided. In an effort to understand the diffusion process in these materials, we have performed kinetic Monte Carlo simulations of vacancy-mediated and interstitial oxygen diffusion in Ytterbium disilicate. Oxygen vacancy and interstitial site energies, vacancy and interstitial formation energies, and migration barrier energies were computed using Density Functional Theory. We have found that, in the case of vacancy-mediated diffusion, many potential diffusion paths involve large barrier energies, but some paths have barrier energies smaller than one electron volt. However, computed vacancy formation energies suggest that the intrinsic vacancy concentration is small. In the case of interstitial diffusion, migration barrier energies are typically around one electron volt, but the interstitial defect formation energies are positive, with the result that the disilicate is unlikely to exhibit experience significant oxygen permeability except at very high temperature.

Coatings↗
DOE OSTI2023

Accurate prediction of oxygen vacancy concentration with disordered A-site cations in high-entropy perovskite oxides

Abstract Entropic stabilized ABO 3 perovskite oxides promise many applications, including the two-step solar thermochemical hydrogen (STCH) production. Using binary and quaternary A-site mixed {A}FeO 3 as a model system, we reveal that as more cation types, especially above four, are mixed on the A-site, the cell lattice becomes more cubic-like but the local Fe–O octahedrons are more distorted. By comparing four different Density Functional Theory-informed statistical models with experiments, we show that the oxygen vacancy formation energies ( $${E}_{V}^{f}$$ E V f ) distribution and the vacancy interactions must be considered to predict the oxygen non-stoichiometry ( δ ) accurately. For STCH applications, the $${E}_{V}^{f}$$ E V f distribution, including both the average and the spread, can be optimized jointly to improve Δ δ (difference of δ between the two-step conditions) in some hydrogen production levels. This model can be used to predict the range of water splitting that can be thermodynamically improved by mixing cations in {A}FeO 3 perovskites.

08 HYDROGEN↗
DOE OSTI2025

Efficient CO2 and Natural Gas Refinery for Ethylene Production - Catalyst Development for Oxidative Coupling of Methane (OCM)

We designed a new electro-catalyst for oxidative coupling of methane (OCM) reaction, the structure of the Sc doped La0.3Sr0.7TiO3-d (LaSrTi) Sc doping to LaSrTi leading to lattice expansion and more distorted lattice, Investigated the effect of doping on the oxygen vacancy formation energy DFT calculations shows that Sc doping facilitate oxygen vacancy formation. Quantifying the surface basicity of the sample before and after Sc doping Sc doped sample exhibits high surface basicity.

catalysis↗
DOE OSTI2025

Atomically Revealing Bulk Point Defect Dynamics in Hydrogen‐Driven γ‐Fe 2 O 3 → Fe 3 O 4 → FeO Transformation

Understanding how point defects in the bulk govern redox transformations is essential for advancing hydrogen-based metal production and designing high-performance oxide materials. This study reveals the atomic-scale mechanisms driving hydrogen-induced reduction of γ-Fe 2 O 3 to Fe 3 O 4 , focusing on how bulk vacancy dynamics dictate structural evolution and reaction kinetics. A key finding is the pronounced contrast in defect behavior between the two oxides: in γ-Fe 2 O 3 , intrinsic Fe vacancies promote oxygen vacancy clustering, destabilizing the local lattice and driving nanopore formation. In contrast, Fe 3 O 4 exhibits a higher oxygen vacancy formation energy and lacks intrinsic Fe vacancies, suppressing vacancy aggregation and maintaining a dense, pore-free structure. This divergence governs distinct reduction pathways—γ-Fe 2 O 3 undergoes an interface-reaction-limited transformation confined to the γ-Fe 2 O 3 /Fe 3 O 4 boundary, while Fe 3 O 4 supports a uniform increase in oxygen vacancy concentration, enabling bulk-phase reduction to lower-oxide FeO. Integrated in situ electron microscopy and density functional theory modeling uncover a vacancy-mediated mechanism, where synergistic cation-anion vacancy dynamics steer microstructure evolution and phase progression. These insights highlight the critical role of vacancy dynamics in controlling oxide reactivity and offer a pathway toward vacancy engineering to enhance reduction kinetics in hydrogen metallurgy and to tailor porosity, reactivity, and structural resilience in oxide-based catalysts and energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of local compositional and structural disorder on vacancy formation in entropy-stabilized oxides from first-principles

Entropic stabilization has evolved into a strategy to create new oxide materials and realize novel functional properties engineered through the alloy composition. Achieving an atomistic understanding of these properties to enable their design, however, has been challenging due to the local compositional and structural disorder that underlies their fundamental structure-property relationships. Here, we combine high-throughput atomistic calculations and linear regression algorithms to investigate the role of local configurational and structural disorder on the thermodynamics of vacancy formation in (MgCoNiCuZn)O-based entropy-stabilized oxides (ESOs) and their influence on the electrical properties. We find that the cation-vacancy formation energies decrease with increasing local tensile strain caused by the deviation of the bond lengths in ESOs from the equilibrium bond length in the binary oxides. The oxygen-vacancy formation strongly depends on structural distortions associated with the local configuration of chemical species. Vacancies in ESOs exhibit deep thermodynamic transition levels that inhibit electrical conduction. By applying the charge-neutrality condition, we determine that the equilibrium concentrations of both oxygen and cation vacancies increase with increasing Cu mole fraction. Our results demonstrate that tuning the local chemistry and associated structural distortions by varying alloy composition acts an engineering principle that enables controlled defect formation in multi-component alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effects of heteroatom doping on hydrogen uptake in tungsten oxide

Redox-active transition metal oxides (TMOs) that can undergo proton-insertion coupled electron transfer (PICET) are promising candidates for catalyzing molecular conversion reactions which require the transfer of hydrogen atoms (or the thermochemical equivalent, H + , e − ). Herein, we studied the effects of isovalent (Mo 6+ ) and aliovalent (V 5+ and Nb 5+ ) heteroatom doping on the electrochemical PICET behavior of monoclinic tungsten oxide (WO 3 ). Cyclic voltammetry in aqueous acidic electrolytes shows that the addition of redox-active heteroatoms (Mo 6+ and V 5+ ) leads to systematic shifts in redox couple half-wave potentials (E 1/2 ), broadening, and an overall decrease in the current response. Conversely, the non-redox active heteroatom (Nb 5+ ) only reduces the current response with no observable peak-current broadening. This broadening is attributed to changes in the proton binding affinities of oxygen in different chemical environments, i.e., bridging different pairs of redox-active transition metal cations. We determined the hydrogen bond dissociation free energy (H BDFE) values to elucidate the thermodynamic effect of heteroatom substitution. Density functional theory calculations reveal a differentiation in the hydrogen binding and oxygen vacancy formation energies between heteroatom doped structures. The PICET-induced structural phase transitions of the pristine and doped samples were further probed with operando electrochemical X-ray diffraction (EC-XRD) and with ex situ chemical reduction. The broadening of the potential-dependent current response with increased heteroatom doping manifests in the operando EC-XRD results as prolonged structural regions where multiple hydrogen bronze phases exist and the appearance of cubic bronze phases at lower degrees of reduction compared to pristine WO 3 .

Holzapfel, Noah P. [North Carolina State Universit↗
DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗
NASA NTRS1990

Application of the embedded atom method to Pb and Be

We have derived the embedding energy functional and two-body potential of the embedded atom method using decreasing exponentials for both the electron density and the two body potential. The embedding function was obtained from the equation of state given by Rose et al. (1984). Because of the form of the embedding function, the equilibrium lattice constant, cohesive energy, and bulk modulus are automatically satisfied. The two parameters phi(e) and gamma of the two-body potential were determined by fitting to shear modulus and the single vacancy formation energy. Contributions of up to the third nearest neighbors were included in the evaluation of the charge density rho and the two-body potential phi. The stability and anisotropy of each structure were estimated and compared with the available experimental data.

Karimi, M.↗
DOE OSTI2025

Ba 1−x Sr x FeO 3−δ as an improved oxygen storage material for chemical looping air separation: a computational and experimental study

Chemical looping air separation (CLAS) is a promising technology to generate oxygen-rich gas streams to enable efficient carbon dioxide capture during fossil fuel combustion or gasification. CLAS relies on the capture and release of oxygen from the atmosphere using the redox properties of an oxygen-selective solid oxide carrier. This study investigates the redox characteristics of Ba 1−x Sr x FeO 3−δ (0.0 ≤ x ≤ 0.417, 0.0 ≤ δ ≤ 0.5) using a combination of density functional theory (DFT) calculations and experimental verification using X-ray diffraction, thermogravimetric analysis, and oxygen-temperature-programmed desorption. The DFT computed energies of the Ba 1−x Sr x FeO 3−δ perovskites reveal a composition-dependent transition from hexagonal to cubic phases as the Sr-concentration or oxygen vacancy concentration increases. Oxygen vacancy formation energies of the cubic perovskites are found to be lower than those of their hexagonal counterparts. A low oxygen diffusion barrier of ∼1 eV combined with the thermodynamic preference of Ba 1−x Sr x FeO 3−δ compositions that form in a cubic phase suggests them as promising candidates for oxygen storage applications. The experimental results corroborate this finding by identifying Ba 0.75 Sr 0.25 FeO 3−δ in the cubic phase as an optimal composition offering low-temperature oxygen storage capacities comparable to that of the state-of-the-art Sr 0.75 Ca 0.25 FeO 3−δ perovskite oxygen storage material at 325 °C and 350 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Probing how Ti- and Nb-substitution affect the stability and improve the electrochemical performance of β- and ε-LiVOPO 4

LiVOPO 4 is a promising next-generation multi-electron cathode material, boasting a theoretical capacity of 305 mA h g -1 , significantly higher than any commercially used Li-ion battery cathode material. However, the material still faces several limitations, including the difficulty in attaining the full theoretical capacity at higher rates and capacity fade over several cycles. Here, in this paper, we show that Ti- and Nb-substitution can be used to improve the thermal stability and electrochemical performance of LiVOPO 4 . We show through in situ heating with XRD and a novel gradient heating technique that both Ti- and Nb-substitution cause β-LiVOPO 4 to be stabilized relative to ε-LiVOPO 4 . This is due to transition-metal substitution, which increases the O-vacancy formation energies, pushing the β → ε transition to higher temperatures. We show that it is still possible to synthesize pure-phase ε-LiVOPO 4 through the use of high temperatures to generate these O-vacancies. We show that even 1% of Ti- or Nb-substitution can improve the initial capacity and long term cycling capability of LiVOPO 4 by improving the high-voltage capacity and reducing the capacity fade in both the high- and low-voltage regions. This is due to the overall improved Li + ion diffusion which is caused by an improved charge-transfer resistance during cycling.

25 ENERGY STORAGE↗