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At least 19 records
All sourcesNASA NTRSDOE OSTI
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 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 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 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 OSTI2023

Understanding the Degradation of La 1−x Sr x FeO 3−δ (0 ≤ x ≤ 1) Perovskite Oxides during the Oxygen Evolution Reaction in Alkaline Solution

Perovskite oxides are an emerging class of highly active catalysts for the oxygen evolution reaction (OER); however, their electrochemical stability remains poorly understood. Here, we report a systematic evaluation of the OER activity and stability of La 1−x Sr x FeO 3-δ perovskites in 1 M KOH. Their initial OER activity first increases with increasing Sr content (fromx= 0 to 0.8), and then decreases when the Sr content is increased to 1. Their stability evaluated by monitoring the element leaching from the electrodes show that La does not leach at a detectable rate, but Sr and Fe leach substantially. The leaching of Sr occurs at similar rates under open circuit potential (OCP) and OER potential, suggesting a nonelectrochemical dissolution process. The leaching of Fe is, however, strongly dependent on the electrode potential. More Fe leaching is observed under the OER potential than OCP. Additionally, the electrode with higher initial OER activity leaches more Fe. These results indicate that OER facilitates the dissolution of Fe from the electrode. The leaching of Fe, in turn, is considered responsible for the activity loss of La 1-x Sr x FeO 3−δ during OER. This study brings new insight into the degradation mechanism of La 1-x Sr x FeO 3−δ and their related perovskite oxides during electro-oxidation processes.

Electrochemistry↗
DOE OSTI2023

New High-Entropy Perovskite Oxides with Increased Reducibility and Stability for Thermochemical Hydrogen Generation

This project aims to design, synthesize, and test a transformative class of High-Entropy Perovskite Oxides (HEPOs) as redox oxides to enable thermochemical hydrogen generation with improved stability, kinetics, and efficiency. These developed HEPOs are expected to demonstrate improved kinetics with oxygen surface exchange coefficient ( k > 7.5×10 -4 cm/s) in Budget Period (BP) 1, retain its structural stability in a broad range of oxygen non-stoichiometry (Δδ > 0.15) at a low operating reduction temperature of T red < 1400°C in BP 2, and deliver a H 2 yield of over 400 µmol per gram of oxide and high stability with less than 20% degradation after at least 50 cycles in BP 3. This project is feasible due to the unique thermodynamic properties (simultaneously increased reducibility and phase stability) and kinetic characters (stability against particle coarsening and potentially enhanced oxygen transport and surface reaction kinetics) of such HEPOs, and it is enabled by a unique active learning computational design approach. Computational studies have been conducted to investigate the oxygen vacancy formation in complex perovskite systems. * Accurate prediction of V O .. concentration with disordered A-site cations in Fe-based high-entropy perovskite oxides * Combined MC/DFT computation elucidates the mechanism of Co preference on the redox due to the strain introduced by local distortion. In this project, we explored a large number (~150) of perovskite compositions, which are listed in Tables 2 – 4). * All perovskite specimens have been synthesized through a high-throughput high-energy ball milling process, followed by the conventional sintering process. * XRD, SEM/EDS and TGA were performed to confirm the crystal structure, phase homogeneity and oxygen non-stoichiometry for compositionally complex perovskite oxides (CCPOs). * 110 compositions show single-phase from XRD * Unusual aliovalent doping effects in medium-entropy perovskite compositions. * V-shape relation between Δδ vs. x (La 1-x Sr x )(Mn 1/3 Fe 1/3 Ti 1/3 )O 3 * The highest reported hydrogen production for the CCPOs made in this project ( T re = 1350 ºC 30 min, T Ox = 1100 ºC 30 min) * B-site mixing (La 0.8 Sr 0.2 )(Mn 0.2 Fe 0.2 Co 0.4 Al 0.2 )O 3 : 89.97 ± 2.73 mmol H2 /mol oxide (395 ± 10 μmol/g oxide ) (i) No phase transformation during reactions when Co molar ratio is less than 61% (ii) Balance between intrinsic kinetics (oxygen surface exchange) and thermodynamics (oxygen non-stoichiometry) (iii) Preference of Co identified by in-situ XPS * A-site mixing (La 1/6 Pr 1/6 Nd 1/6 Gd 1/6 Ba 1/6 Sr1/6)MnO 3 : 98.48 mmol H2 /mol oxid e (~415 μmol/g oxide )

08 HYDROGEN↗
DOE OSTI2024

Structural mode coupling in perovskite oxides using hypothesis-driven active learning

Abstract Finding the ground-state structure with minimum energy is paramount to designing any material. In ABO 3 -type perovskite oxides with Pnma symmetry, the lowest energy phase is driven by an inherent trilinear coupling between the two primary order parameters such as rotation and tilt with antiferroelectric displacement of the A-site cations as established via hybrid improper ferroelectric mechanism. Conventionally, finding the relevant mode coupling driving phase transition requires performing first-principles calculations which is computationally time-consuming as well as expensive. It involves following an intuitive iterative hit and trial method of (a) adding two or multiple mode vectors, followed by (b) evaluating which combination would lead to the ground-state energy. In this study, we show how a hypothesis-driven active learning framework can identify suitable mode couplings within the Landau free energy expansion with minimal information on amplitudes of modes for a series of double perovskite oxides with A-site layered, columnar and rocksalt ordering. This scheme is expected to be applicable universally for understanding atomistic mechanisms derived from various structural mode couplings behind functionalities, for e.g. polarization, magnetization and metal–insulator transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrochemical exsolution of metal nanoparticles from perovskite oxide upon electrolysis

Here, this study presents a comprehensive investigation into the electrochemical reduction of LSCF perovskite during electrolysis, aiming to understand the exsolution of metal nanoparticles. The exsolution of metal nanoparticles from perovskite electrodes can significantly enhance their electrochemical performance in electrolysis. By applying cathodic polarization to the perovskite oxide electrode, the exsolution process was shown to be electrochemically induced within a few minutes. Additionally, a user-designed X-ray absorption spectroscopy operando cell was employed to analyze the edge energy change of the B-site atoms during electrolysis. The electrochemical reduction of perovskite and the subsequent exsolution of the B-site metal nanoparticles were investigated by scanning the cell voltage, providing an understanding of the electrochemical behavior during electrolysis. The electrochemical switching point, characterized by a decrease in the incremental area-specific resistance, was identified. This study offers valuable insights into the electrochemical exsolution process of metal nanoparticles from perovskite oxide electrodes.

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

Machine learning informed rational design of high entropy double perovskite oxide universal air/steam electrodes for solid oxide electrochemical cells

Due to their high efficiency and versatility, solid oxide electrochemical cells (SOCs) are poised to play a significant role in future energy conversion and storage applications. In recent years, SOCs have bifurcated into two distinct categories: traditional oxygen-ion conducting SOCs that typically operate from ∼650—850 °C and the more recent proton-conducting ceramic (PCC) SOCs that typically operate from ∼400—650 °C. Current performance and lifetime of both oxygen-ion conducting SOCs and PCCs is primarily limited by the air/steam electrode, which facilitates the oxygen reduction reaction (ORR) during fuel cell operation and must also facilitate the oxygen evolution reaction (OER) during electrolysis operation. Here, we present a newly designed high-entropy double perovskite oxide suitable as a universal ORR/OER electrode for both oxygen-ion conducting SOCs and PCCs. Machine learning methods are applied to identify chemical descriptors for highly catalytic high-entropy double perovskite oxides (AA’B 2 O 6 ) across a large compositional space. Based on the machine-learning guidance, we ultimately converge on Ba 0.9 Cs 0.1 (Ca 0.2 Gd 0.2 La 0.2 Pr 0.2 Sr 0.2 )Co 1.5 Fe 0.5 O 6 (CsBaHEO) as a universal air/steam electrode. Structure stabilization is accomplished by an equimolar five-cation high-entropy composition on the A’-site, while cesium substitution on the A-site enhances the electrical conductivity and leads to a higher oxygen vacancy concentration. This material exhibits versatility and high performance in reversible oxygen-ion SOCs, reversible PCCs, and also large-scale tubular PCCs. For example, the CsBaHEO-based PCC reaches 1018 mW∙cm −2 at 600°C, while a large-scale tubular PCC using CsBaHEO for electrolysis achieves a hydrogen production rate of 21.314 ML∙min −1 at 600 °C.

Cell↗
DOE OSTI2025

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry↗
DOE OSTI2024

Visible Light Photolysis at Single Atom Sites in Semiconductor Perovskite Oxides

Designing catalysts with well-defined active sites with chemical functionality responsive to visible light has significant potential for overcoming scaling relations limiting chemical reactions over heterogeneous catalyst surfaces. Visible light can be leveraged to facilitate the removal of strongly bound species from well-defined single cationic sites (Rh) under mild conditions (323 K) when they are incorporated within a photoactive perovskite oxide (Rh-doped SrTiO 3 ). CO, a key intermediate in many chemistries, forms stable geminal dicarbonyl Rh complexes (Rh + (CO) 2 ), that could act as site blockers or poisons during a catalytic cycle. For the first time, we demonstrate that CO removal can occur at mild temperatures (323 K) under low-energy red light (635 nm) irradiation, which is not possible for supported isolated-site Rh catalysts (0.2 wt % Rh/γ-Al 2 O 3 ). Photolysis of supported Rh + (CO) 2 complexes (e.g., 0.2 wt % Rh/γ-Al 2 O 3 ) has been demonstrated but is limited to high energy UV photons. Rigorous kinetic experiments elucidate disparate mechanisms for CO photodepletion from Rh-doped SrTiO 3 and supported isolated site Rh/γ-Al 2 O 3 . CO photodepletion from supported isolated site Rh/γ-Al 2 O 3 involves a direct metal to ligand charge transfer mechanism, whereas Rh-doped SrTiO 3 is governed by electron–hole pair formation in the perovskite. In this work, we show that under visible, low-energy red light, surface Rh species in Rh-doped SrTiO 3 introduce midgap energy states above the valence band that facilitate electronic excitations leading to surface CO removal. Isolated Rh sites in Rh-doped SrTiO 3 also exhibit exceptional stability under multiple CO photodepletion cycles. Overall, incorporating single sites into photoactive perovskite oxides is an effective strategy to influence surface chemistries with visible light.

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

Compositionally complex perovskite oxides: Discovering a new class of solid electrolytes with interface-enabled conductivity improvements

Compositionally complex ceramics (CCCs), including high-entropy ceramics, offer a vast, unexplored compositional space for materials discovery. Herein, we propose and demonstrate strategies for tailoring CCCs via a combination of non-equimolar compositional designs and control of grain boundaries (GBs) and microstructures. Using oxide solid electrolytes for all-solid-state batteries as an example, we have discovered a class of compositionally complex perovskite oxides (CCPOs) with improved lithium ionic conductivities beyond the limit of conventional doping. For example, we demonstrate that the ionic conductivity can be improved by >60% in (Li 0.375 Sr 0.4375 )(Ta 0.375 Nb 0.375 Zr 0.125 Hf 0.125 )O 3-δ compared with the (Li 0.375 Sr 0.4375 )(Ta 0.75 Zr 0.25 )O 3-δ (LSTZ) baseline. Furthermore, the ionic conductivity can be improved by another >70% via quenching, achieving >270% of the LSTZ. Notably, we demonstrate GB-enabled conductivity improvements via both promoting grain growth and altering GB structures through compositional designs and processing. In a broader perspective, this work suggests new routes for discovering and tailoring CCCs for energy storage and many other applications.

36 MATERIALS SCIENCE↗