Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Perovskite oxide”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

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

Dataset of theoretical multinary perovskite oxides

Perovskite oxides (ternary chemical formula ABO 3 ) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent (chemical formula $A_xA^{'}_{1-x}B_yB^{'}_{1-y}O_3$) chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed $A_xA^{'}_{1-x}B_yB^{'}_{1-y}O_3$ compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, 69,407 $A_{0.5}A^{'}_{0.5}B_{0.5}B^{'}_{0.5}O_3$ compositions were generated in the a - b + a - Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with density functional theory (DFT) using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔH f ) and decomposition enthalpies (ΔH d ) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated $A_{0.5}A^{'}_{0.5}B_{0.5}B^{'}_{0.5}O_3$ perovskite structures using MP-compatible DFT calculations.

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

Band gap predictions of double perovskite oxides using machine learning

Abstract The compositional and structural variety inherent to oxide perovskites spawn wide-ranging applications. In perovskites, the band gap E g , a key material parameter for these applications, can be optimally controlled by varying the composition. Here, we implement a hierarchical screening process in which two cross-validated and predictive machine learning models for band gap classification and regression, trained using exhaustive datasets that span 68 elements of the periodic table, are applied sequentially. The classification model separates wide band gap materials, with E g ≥ 0.5 eV, from materials which have zero or relatively small band gaps, namely E g < 0.5 eV, and the second regression model quantitatively predicts the gap value of the wide band gap compounds. The study down-selects 13,589 cubic oxide perovskite compositions that are predicted to be experimentally formable, thermodynamically stable, and have a wide band gap. Of these, a subset of 310 compounds, which are predicted to be stable and formable with a confidence greater than 90%, are identified for further investigation. Our models are methodically analyzed via performance metrics and inter-dependence of model features to gain physical insight into the band gap prediction problem. Design maps to identify the variation of band gap with substitution of different elements are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting band gaps and band-edge positions of oxide perovskites using density functional theory and machine learning

Density functional theory (DFT) within the local or semilocal density approximations, i.e., the local density approximation (LDA) or generalized gradient approximation (GGA), has become a workhorse in the electronic structure theory of solids, being extremely fast and reliable for energetics and structural properties, yet remaining highly inaccurate for predicting band gaps of semiconductors and insulators. The accurate prediction of band gaps using first-principles methods is time consuming, requiring hybrid functionals, quasiparticle GW, or quantum Monte Carlo methods. Efficiently correcting DFT-LDA/GGA band gaps and unveiling the main chemical and structural factors involved in this correction is desirable for discovering novel materials in high-throughput calculations. In this direction, we, in this study, use DFT and machine learning techniques to correct band gaps and band-edge positions of a representative subset of ABO 3 perovskite oxides. Relying on the results of HSE06 hybrid functional calculations as target values of band gaps, we find a systematic band-gap correction of ~1.5 eV for this class of materials, where ~1 eV comes from downward shifting the valence band and ~0.5 eV from uplifting the conduction band. The main chemical and structural factors determining the band-gap correction are determined through a feature selection procedure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Theoretical Multinary Perovskite Oxides Dataset

Perovskite oxides (ternary chemical formula ABO3) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, the AA'BB'O6 compositions were generated in the a-b+a- Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with DFT using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔHf) and decomposition enthalpies (ΔHd) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated AA'BB'O6 perovskite structures using MP-compatible DFT calculations

Bare, Zachary↗
DOE OSTI2026

Shifting Valencies and Magnetic Responses in La-Based High-Entropy Oxide Perovskite Thin Films with Variable Mn Presence

Chemical disorder in compositionally complex perovskite oxides generates a broad distribution of exchange pathways and spin states, but the microscopic origin and spatial homogeneity of the resulting magnetic phases remain debated. Here, we tune the Mn fraction (x = 0.2–0.6) in epitaxial La(Cr, Mn, Fe, Co, Ni)O3 thin films and resolve the coupled evolution of valence, spin state, and magnetism using element-specific x-ray absorption spectroscopy and x-ray magnetic circular dichroism (XMCD). Mn enrichment drives an internal redistribution of charge, in which Mn evolves toward a Mn3+-rich mixed valence, while Co converts from predominantly Co3+ to high-spin Co2+. This valence/spin-state coupling amplifies the Mn- and Co-derived ferromagnetic response by nearly an order of magnitude while increasing the magnetic onset temperature to at least 250 K, whereas Fe and Cr remain essentially trivalent with weak dichroism. Depth-resolved low-energy muon spin spectroscopy (LE-μSR) shows magnetic homogeneity through the film thickness, with a secondary relaxation maximum near 25 K indicating a low-temperature dynamical crossover consistent with frustrated magnetism in a strongly disordered spin lattice.

Miertschin, Duncan [Baylor University]↗
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 OSTI2025

Large enhancement of ferroelectric properties of perovskite oxides via nitrogen incorporation

Perovskite oxides have a wide variety of physical properties that make them promising candidates for versatile technological applications including nonvolatile memory and logic devices. Chemical tuning of those properties has been achieved, to the greatest extent, by cation-site substitution, while anion substitution is much less explored due to the difficulty in synthesizing high-quality, mixed-anion compounds. Here, nitrogen-incorporated BaTiO3 thin films have been synthesized by reactive pulsed-laser deposition in a nitrogen growth atmosphere. The enhanced hybridization between titanium and nitrogen induces a large ferroelectric polarization of 70 μC/cm2 and high Curie temperature of ~1213 K, which are ~2.8 times larger and ~810 K higher than in bulk BaTiO3, respectively. These results suggest great potential for anion-substituted perovskite oxides in producing emergent functionalities and device applications.

Wang, Tao↗
DOE OSTI2025

Impact of SO 2 on NiFe Nanoparticle Exsolution and Dissolution from LaFe 0.9 Ni 0.1 O 3 Perovskite Oxides

Ni-doped LaFeO 3 perovskite oxide is a promising cathode material for solid oxide electrolysis cells (SOECs) designed for CO 2 /H 2 O coelectrolysis. Here, the performance of LaFe 0.9 Ni 0.1 O 3 is being investigated under real-world conditions that include exposure to acid gases, such as SO 2 , relevant to SOEC operation. Experiments show that LaFe 0.9 Ni 0.1 O 3 exsolves NiFe nanoparticles, along with the formation of surface SO 4 2– and SO 3 2– after being exposed to 200 ppm of SO 2 . This suggests that the ionic diffusion of Ni 3+ and Fe 3+ between the bulk and the surface remains unaffected throughout the exsolution–dissolution–exsolution cycle. Thermochemical water splitting has been employed as a probe reaction to evaluate the catalytic properties of the exsolved NiFe nanoparticles. These nanoparticles demonstrated improved hydrogen production compared to bare perovskite oxide substrates. However, after exposure to SO 2 , the formation of Fe-rich NiFe nanoparticles led to poor thermocatalytic performance and rapid deactivation of the perovskite at elevated temperatures. Density functional theory (DFT) analysis was utilized to validate the experimental findings, indicating a significantly negative reaction energy for water splitting over exsolved Fe, as well as stronger binding of SO 2 to Fe than to Ni. Computational analysis further suggests that the presence of surface sulfate promotes the formation of Fe-rich NiFe nanoparticles, aligning with the experimental results. Overall, this study clarifies how SO 2 affects the structure of SOEC perovskite oxide candidate materials. Future engineering efforts should focus on enhancing nanoparticle exsolution and sulfur resistance, which is crucial for improving the hydrogen production capacity of La-based perovskite oxides for electro- and thermocatalytic water splitting in real environments containing acid gases.

Najimu, Musa [Univ. of Southern California, Los An↗
DOE OSTI2023

Manganese-based A-site high-entropy perovskite oxide for solar thermochemical hydrogen production

Non-stoichiometric perovskite oxides have been studied as a new family of redox oxides for solar thermochemical hydrogen (STCH) production owing to their favourable thermodynamic properties. However, conventional perovskite oxides suffer from limited phase stability and kinetic properties, and poor cyclability. Here, we report a strategy of introducing A-site multi-principal-component mixing to develop a high-entropy perovskite oxide, (La 1/6 Pr 1/6 Nd 1/6 Gd 1/6 Sr 1/6 Ba 1/6 )MnO 3 (LPNGSB_Mn), which shows desirable thermodynamic and kinetics properties as well as excellent phase stability and cycling durability. LPNGSB_Mn exhibits enhanced hydrogen production (~77.5 mmol mol oxide -1 ) compared to (La 2/3 Sr 1/3 )MnO 3 (~53.5 mmol mol oxide -1 ) in a short 1 hour redox duration and high STCH and phase stability for 50 cycles. LPNGSB_Mn possesses a moderate enthalpy of reduction (252.51–296.32 kJ (mol O) -1 ), a high entropy of reduction (126.95–168.85 J (mol O) -1 K -1 ), and fast surface oxygen exchange kinetics. All A-site cations do not show observable valence changes during the reduction and oxidation processes. In conclusion, this research preliminarily explores the use of one A-site high-entropy perovskite oxide for STCH.

08 HYDROGEN↗
DOE OSTI2023

Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides

The computational design of suitable multiferroic double perovskite oxides requires finding materials that exhibit sizable polarization, magnetization, and coupling between them. Oxides with the chemical formula of AA'BB'O 6 with building blocks of ABO 3 single perovskite oxides in centrosymmetric Pnma symmetry are strong candidates that have been reported to satisfy such criteria. The system lowers to noncentrosymmetric, polar P2 1 symmetry if A/A' layered and B/B' rocksalt cation orderings are imposed. A detailed compositional search over a variety of chemical spaces followed by evaluating their polarization may lead to the identification of more of these compounds with ferroelectric ordering. The standard density functional theory practices to estimate polarization within the Berry phase formalism require the systems to be perfectly insulating. The number of compounds that can be evaluated using this method is therefore limited. In this work, we introduce a predictive learning strategy based on importance sampling to build a series of machine learning models using results from first-principles simulations to predict polarization and the corresponding switching barrier. The geometry-driven features related to charge states and cationic radii play key roles in predicting the switching barrier with complementary contributions from the key structural mode-based order parameters. These modes become important to draw reasonable predictions of polarization components from machine learning models. In conclusion, our predictive models identify candidates with high polarizations and low switching barriers from a pool of double perovskite oxides, suitable for future investigation for their potential applications in spintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Combinatorial screening of crystal structure in Ba-Sr-Mn-Ce perovskite oxides with ABO 3 stoichiometry

ABO 3 oxides with the perovskite-related structures are attracting significant interest due to their promising physical and chemical properties for many applications requiring tunable chemistry, including fuel cells, catalysis, and electrochemical water splitting. Here we report on the crystal structure of the entire family of perovskite oxides with ABO 3 stoichiometry, where A and B are Ba, Sr, Mn, Ce. Given the vast size of this chemically complex material system, exploration for stable perovskite-related structures with respect to its constituent elements and annealing temperature is performed by combinatorial pulsed laser deposition and spatially-resolved characterization of composition and structure. As a result of this high-throughput experimental study, we identify hexagonal perovskite-related polytypic transformation as a function of composition in the Ba 1-x Sr x MnO 3 oxides after annealing at different temperatures. Furthermore, a hexagonal perovskite-related polytype is observed in a narrow composition-temperature range of the Ba 1-x Sr x MnO 3 oxides. In contrast, a tetragonally-distorted perovskite is observed across a wider range of compositions and annealing temperatures in the Sr 1-x Ce x MnO 3 oxides. This structure stability is further enhanced along the Ba 1-x Sr x MnO 3 - Sr 1-x Ce x MnO 3 pseudo-binary tie-line at x=0.25 by increasing Ba-incorporation and annealing temperature. These results indicate that the BaCe x Mn 1-x O 3 - Sr 1-x Ce x MnO 3 pseudo-binary oxide alloys (solid solutions) with tetragonal perovskite structure and broad composition-temperature range of stability are promising candidates for thermochemical water splitting applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Toward Superb Perovskite Oxide Electrocatalysts: Engineering of Coupled Nanocomposites

Abstract A significant issue that bedeviled the commercialization of renewable energy technologies, ranging from low‐temperature water electrolyzers to high‐temperature solid oxide cells, is the lack of high‐performance catalysts. Among various candidates that could tackle such a challenge, perovskite oxides are rising‐star materials because of their unique structural and compositional flexibility. However, single‐phase perovskite oxides are challenging to satisfy all the requirements of electrocatalysts concurrently for practical applications, such as high catalytic activity, excellent stability, good ionic and electronic conductivities, and superior chemical/thermo‐mechanical robustness. Impressively, perovskite oxides with coupled nanocomposites are emerging as a novel form offering multifunctionality due to their intrinsic features, including infinite interfaces with solid interaction, tunable compositions, flexible configurations, and maximum synergistic effects between assorted components. Considering this new configuration has attracted great attention owing to its promising performances in various energy‐related applications, this review timely summarizes the leading‐edge development of perovskite oxide‐based coupled nanocomposites. Their state‐of‐art synthetic strategies are surveyed and highlighted, their unique structural advantages are highlighted and illustrated through the typical oxygen reduction reaction and oxygen evolution reactions in both high and low‐temperature applications. Opinions on the current critical scientific issues and opportunities in this burgeoning research field are all provided.

08 HYDROGEN↗
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↗