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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Adsorptive recovery of volatile fatty acids from wastewater fermentation broth

This work developed an adsorptive separation and recovery process for anaerobically generated volatile fatty acids (VFAs) from swine wastewater fermentation. Batch adsorption studies were conducted using several weak anion exchange resins and synthetic adsorbent resins to identify a suitable candidate. Relite RAM2 with a tertiary amine functional group showed the highest adsorption (over 98%) of hexanoic acid. Under the different pH values (1.8–7.5) and extraction temperatures (30–50 ↑C), the highest adsorption was observed at a pH of 3.2, which is below the pKa of hexanoic acid, at all the evaluated temperatures. A full factorial design was used to optimize the resin and VFA concentrations, wherein over 99% adsorption could be achieved when the ratio of VFA to resin was below 0.23 (g/g) for model solution (VFAs in water). The adsorption equilibrium could be achieved within 30 min of contact time and 0.5% w/v NaOH was identified as a suitable desorption agent. Under the optimal conditions, 65–72% of VFAs present in fermentation broth was adsorbed, which was increased to 72–76% by using fresh resins. The VFAs adsorption and recovery efficiency were maintained for 9 successive cycles without requiring extensive resin washing and regeneration for both model solution and fermentation broth. Altogether, the work presents a comprehensive study for resin adsorption to recover VFAs and provides a potential industrial-relevant process to recover VFAs from fermentation broth.

09 BIOMASS FUELS↗
DOE OSTI2020

Planning green infrastructure placement based on projected precipitation data

Continued urbanization has led to tremendous changes on the landscape. These changes have exacerbated the effects of extreme climatic events such as flooding because of constrained water infiltration and increased surface flow. Typical runoff control measures involve sophisticated gray infrastructure that guide excess surface flow into storage and disposal sites. In a dynamic climate system, these measures are not sustainable since they cannot be easily modified to accommodate large volumes of runoff. Green Infrastructure (GI) is an adaptable technique that can be used to minimize runoff, in addition to offering an array of additional benefits (urban heat regulation, aesthetics, improved air quality etc.). Strategic placement of GI is key to achieving maximum utility. While physical site characteristics play a major role in determining suitable GI placement sites, knowledge of future precipitation patterns is crucial to ensure successful flood mitigation. Here, suitable GI sites within the city of Knoxville, Tennessee, were determined based on potential impact of an extreme flood event as indicated by site characteristics. Then, the relative potential likelihood of a flood event was determined based on projected precipitation data and knowledge of existing flood zones. By combining potential impact with likelihood information, low, medium, and high priority GI implementation sites were established. Results indicate that high priority sites are in the central parts of the city with priority decreasing outward. The GI prioritization scheme presented here, offers valuable guidance to city planners and policy makers who wish to exploit the GI approach for flood mitigation.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2022

Macrovoid resolved simulations of transport through HPRO relevant membrane geometries

Modeling the transport properties such as diffusivity and permeability of high pressure reverse osmosis (HPRO) membranes is critical for the selection and manufacture of membranes suitable for operation under high pressure. These properties can be significantly affected by the changes in heterogeneous pore structures due to compaction. Here, the modeling platform presented in this work resolves the two scale porosity in HPRO relevant membranes. A synthetic membrane geometry is constructed based on available experimental visualizations of pore structures. The simulations directly capture the flow channeling that results from a combination of material properties and geometric features of the macrovoids. A parametric study is presented to account for the transition of flow characteristics from a material governed regime to a macrovoid governed regime. Permeability of the membrane is evaluated using the simulation data and compared with an existing model that scales with the square of tortuosity over a range of material properties. The model is found to perform well under a narrow range of tortuosity while deviating from the calculated permeabilities at extreme conditions. The effective permeability of the membrane is found to vary by at least two orders of magnitude between the two flow regimes. It is also observed that tortuosity is a bounded property with its upper limit determined by the macrovoid geometry. Consequently, the tortuosity based correlations fail near a flow regime that is mainly governed by the macrovoids. The modeled permeability can be more than an order of magnitude smaller than the simulation result. A new model based on flux-weighted porosity of a membrane is introduced and its correlation with tortuosity is studied. The model agrees with the simulated data as, in addition to tortuosity, it also accounts for the flux partition within and outside the flow channels. Such correlations enable extending the existing understanding of flow characteristics to enhance predictability of porous media models.

42 ENGINEERING↗
DOE OSTI2022

The Dynamics of Ions on Phased Radio-frequency Carpets in High Pressure Gases and Application for Barium Tagging in Xenon Gas Time Projection Chambers

Radio-frequency (RF) carpets with ultra-fine pitches are examined for ion transport in gases at atmospheric pressures and above. We develop new analytic and computational methods for modeling RF ion transport at densities where dynamics are strongly influenced by buffer gas collisions. An analytic description of levitating and sweeping forces from phased arrays is obtained, then thermodynamic and kinetic principles are used to calculate ion loss rates in the presence of collisions. This methodology is validated against detailed microscopic SIMION simulations. We then explore a parameter space of special interest for neutrinoless double beta decay experiments: transport of barium ions in xenon at pressures from 1 to 10 bar. Our computations account for molecular ion formation and pressure dependent mobility as well as finite temperature effects. We discuss the challenges associated with achieving suitable operating conditions, which lie beyond the capabilities of existing devices, using presently available or near-future manufacturing techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Uranium measurements in the field using high-resolution cadmium zinc telluride detectors

A new generation of cadmium zinc telluride (CZT) detectors has become available and is being evaluated by the International Atomic Energy Agency (IAEA) for safeguards verifications in the field. The new CZT detector, model M400, is a room temperature spectrometer manufactured by H3D, Inc. The M400 demonstrates superior energy resolution, effective isotope identification capabilities, and convenient usability features when tested in a controlled laboratory environment. These characteristics define the M400 as a potential platform for IAEA field detection applications, which could become suitable for nuclear material characterization (e.g., enrichment verification) and nuclear safeguards missions. The capabilities of gamma spectrometry codes including Fixed energy, Response function Analysis with Multiple efficiencies (FRAM) from Los Alamos National Laboratory, CZT for Uranium (CZTU) from Lawrence Livermore National Laboratory, and Gamma Detector Response and Analysis Software (GADRAS) from Sandia National Laboratories were adapted for M400 spectra, and the performance of the codes has been validated. This was reported in a prior work. To further validate the performance of the high-energy resolution CZT detector and the isotopic analysis codes, a field measurement campaign consisting of uranium hexafluoride (UF 6 ) cylinder measurements was conducted at a fuel fabrication facility. A total of 34 Type 30B cylinders containing UF6 were measured using three different M400 CZT detectors. Each detector was outfitted with a custom rectangular collimator and shield made out T-Flex®, a tungsten-impregnated polymer. Measurements were performed at three different locations of the cylinder, ensuring that the measurement geometry satisfied the infinite thickness criterion. The spectra from the M400 CZT were analyzed using the code General Enrichment Meter (GEM). For analyzing the gamma-ray spectra from UF 6 cylinder, the GEM code is the appropriate tool since it relies only on the gamma-ray emissions from 235 U and not from other isotopes. Results from the spectral analysis were compared with the known abundance of 235 U in the cylinders, as well as with the International Target Values 2020 (ITV2020). The suitability of the different underlying techniques used by the various codes for UF 6 analysis is discussed. The challenges of measuring UF 6 contained in cylinders and mitigation strategies are highlighted.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

The total neutron cross section of liquid and solid ammonia

Ammonia is a material of interest for future neutron moderators at high-power sources due to its high hydrogen density, low melting point, and resistance to polymerization in an intense radiation field. Its performance in such applications cannot currently be calculated due to the absence of suitable computer models for the interaction of neutrons with ammonia under relevant conditions. In an effort to develop suitable scattering kernels for computer simulations of moderator performance, we have conducted a series of Density Functional Theory and Molecular Dynamics calculations of the molecular-level thermal properties of ammonia at various temperatures within both the solid and liquid phases. In this paper, we compare computer calculations for the energy-dependent total neutron cross section of ammonia, based on these models, to experimental measurements of those cross sections at temperatures of 221 K, 180 K, and 35 K. The experimental data were collected over an energy range from 0.1 meV to 10 eV using time-of-flight techniques at the Low Energy Neutron Source (LENS) facility at Indiana University. This comparison provides a first validation in the development of thermal scattering libraries for Monte Carlo source design simulations based on liquid and solid ammonia. In conclusion, we also provide some insights into where additional development of tools for creating such models may be needed.

Ammonia↗
DOE OSTI2020

Radioarsenic: A promising theragnostic candidate for nuclear medicine

Molecular imaging is a non-invasive process that enable the visualization, characterization, and quantitation of biological processes at the molecular and cellular level. With the emergence of theragnostic agents to diagnose and treat disease for personalized medicine there is a growing need for matched pairs of isotopes. Matched pairs offer the unique opportunity to obtain patient specific information from SPECT or PET diagnostic studies to quantitate in vivo function or receptor density to inform and tailor therapeutic treatment. There are several isotopes of arsenic that have emissions suitable for either or both diagnostic imaging and radiotherapy. Their half-lives are long enough to pair them with peptides and antibodies which take longer to reach maximum uptake to facilitate improved patient pharmacokinetics and dosimetry then can be obtained with shorter lived radionuclides. Arsenic-72 even offers availability from a generator that can be shipped to remote sites and thus enhances availability. Arsenic has a long history as a diagnostic agent, but until recently has suffered from limited availability, lack of suitable chelators, and concerns about toxicity have inhibited its use in nuclear medicine. However, new production methods and novel chelators are coming online and the use of radioarsenic in the pico and nanomolar scale is well below the limits associated with toxicity. This manuscript will review the production routes, separation chemistry, radiolabeling techniques and in vitro/in vivo studies of three medically relevant isotopes of arsenic (arsenic-74, arsenic-72, and arsenic-77).

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Land-based resources for engineered carbon dioxide removal in the United States exceed the expected needs

Gigatonne-scale atmospheric carbon dioxide removal (CDR), alongside deep emission cuts, is critical to stabilizing the climate. However, some of the most scalable CDR technologies are also the most land intensive. Here, we examine whether adequate land resources exist in the contiguous United States to meet CDR targets when prioritizing grid emissions reduction, food production, and the protection of sensitive ecosystems. We focus on biomass carbon removal and storage (BiCRS) and direct air capture and storage (DACS) and show that suitable lands exceed the expected needs: 37.6 million hectares of land are available for BiCRS, resulting in 0.26 GtCO 2 of CDR/year, and 34 million hectares are suitable for wind- and solar-powered DACS, resulting in 4.8 GtCO 2 of CDR/year if facilities are co-located with geologic CO 2 storage. We identify biomass and energy supply hotspots to meet CDR targets while ensuring land protection and minimizing land competition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating adaptive and predictive power management strategies for optimizing visualization performance on supercomputers

Power is becoming an increasingly scarce resource on the next generation of supercomputers, and should be used wisely to improve overall performance. One strategy for improving power usage is hardware overprovisioning, i.e., systems with more nodes than can be run at full power simultaneously without exceeding the system-wide power limit. With this study, we compare two strategies for allocating power throughout an overprovisioned system – adaptation and prediction – in the context of visualization workloads. While adaptation has been suitable for workloads with more regular execution behaviors, it may not be as suitable on visualization workloads, since they can have variable execution behaviors. This study considers a total of 104 experiments, which vary the rendering workload, power budget, allocation strategy, and node concurrency, including tests processing data sets up to 1 billion cells and using up to 18,432 cores across 512 nodes. Overall, we find that prediction is a superior strategy for this use case, improving performance up to 27% compared to an adaptive strategy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

3D printed polymer gaskets for custom-form batteries

Additive manufacturing (AM) processes, like 3D printing, help to facilitate complex and customizable battery geometries which can provide design freedom and enhance volumetric energy density within electronic devices. AM materials must have the thermal and mechanical properties that enable printability, and when used in batteries, AM materials must also be chemically and electrochemically compatible with the battery chemistry. The compatibility between AM materials and the battery is of particular importance for the cell packaging materials which must be inert and are often overlooked. This study systematically studies AM-compatible polymeric materials for use as gaskets in lithium-ion cells. The materials investigated include three thermoplastics suitable for material extrusion printing: polylactic acid (PLA), polycarbonate, and polypropylene/polyethylene copolymer (PPPEC); and two photoresins suitable for vat photopolymerization (VPP) printing: an acrylate-based photoresin and a polyethylene glycol diacrylate photoresin. The AM gasket materials were tested in comparison to a conventional commercial polypropylene gasket. Mechanical testing (swell measurements and material stiffness) and electrochemical testing (linear sweep voltammetry and galvanostatic cycling of full cells) demonstrated that PLA and the VPP polymers were the least compatible with the lithium-ion battery chemistry, despite their prevalent use in studies of AM batteries, and that PPPEC was the most compatible.

3D printing↗
DOE OSTI2020

Synthesis and magnetic performance of gadolinium powder produced with rotating disk atomization

Spherical powder is key for achieving good heat transfer and maintaining low pressure drop for heat transfer fluid in magnetocaloric regenerator. Obtaining relatively large spherical powder of rare earth metals that are extremely sensitive to oxygen is challenging. Comparing to gas atomization and plasma rotating electrode methods, rotating disk atomization (RDA) method is more robust for obtaining a small amount of powder with a short turn-around time, thereby, more suitable for research and development of new magnetocaloric materials. In this work, commercially bulk gadolinium was successfully atomized to produce spherical powder in the targeted 150–250 μm range. The obtained powder exhibited the expected magnetocaloric performance with a maximum change of magnetic entropy of 12.1 J/kg K and a maximum adiabatic temperature change of 12.8 K with an applied magnetic field of 7 T.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Computational modelling and experimental tank testing of the multi float WaveSub under regular wave forcing

A submerged wave device generates energy from the relative motion of floating bodies. In WaveSub, three floats are joined to a reactor; each connected to a spring and generator. Electricity generated damps the orbital movements of the floats. The forces are non-linear and each float interacts with the others. Tuning to the wave climate is achieved by changing the line lengths, so there is a need to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design. to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

E-scooter safety: How attitudinal factors influence risky behavior among shared e-scooter riders

In recent years, e-scooter usage for short-distance trips has grown rapidly. This surge in e-scooter use, combined with the high exposure of e-scooter riders to accident risk, has sparked concerns regarding e-scooter safety. Despite some studies focusing on e-scooter safety, little is known about how attitudinal factors lead e-scooter riders to engage in risky riding behaviors. In this paper, we developed a survey-based empirical model to identify the attitudinal factors influencing engagement in risky behaviors among e-scooter users. We used survey data collected from 420 shared e-scooter users in Chicago in 2022. The survey showed that 47.7% of respondents had experienced at least one collision or fall-off while riding e-scooters. We employed the Partial Least Squares Structural Equation Model (PLS-SEM) to examine the relationships between latent attitudinal factors and risky behavior engagement. Moreover, we conducted Permutation Multi-group Analysis (PMGA) to assess the moderating effect of socio-demographic factors within the estimated model. The findings suggest that riders’ unsafe riding attitude and riding confidence are the most influential factors shaping their risky behavior engagement. In addition, accident experience, infrastructure suitability, perceived enjoyment, traffic risk perception, and operational risk perception are among the other significant predictors. Among socio-demographic factors, gender, age, education, and car use frequency significantly influence riders’ engagement in risky behaviors. The results highlight the importance of infrastructure suitability and accident experience in analyzing e-scooter users’ riding behavior. The developed model advances our understanding of factors contributing to e-scooter riders’ risky behavior engagement. The findings offer valuable insights for policymakers and e-scooter vendors aiming to mitigate e-scooter users’ accident risk. Specifically, we recommend three safety countermeasures: (1) safety training programs to encourage a safer attitude, (2) practice-based initiatives to enhance riding confidence, and (3) infrastructure improvements, especially the expansion of bike lanes.

E-scooter↗
DOE OSTI2022

H 2 BZmacropa-NCS: A Bifunctional Chelator for Actinium-225 Targeted Alpha Therapy

Actinium-225 ( 225 Ac) is one of the most promising radionuclides for targeted alpha therapy (TAT). With a half-life of 9.92 days and a decay chain that emits four high-energy α particles, 225 Ac is well-suited for TAT when conjugated to macromolecular targeting vectors that exhibit extended in vivo circulation times. The implementation of 225 Ac in these targeted constructs, however, requires a suitable chelator that can bind and retain this radionuclide in vivo. Previous work has demonstrated the suitability of a diaza-18-crown-6 macrocyclic chelator H 2 macropa for this application. Building upon these prior efforts, in this study, two rigid variants of H 2 macropa, which contain either one (H 2 BZmacropa) or two (H 2 BZ 2 macropa) benzene rings within the macrocyclic core, were synthesized and investigated for their potential use for 225 Ac TAT. The coordination chemistry of these ligands with La 3+ , used as a nonradioactive model for Ac 3+ , was carried out. Both NMR spectroscopic and X-ray crystallographic studies of the La 3+ complexes of these ligands revealed similar structural features to those found for the related complex of H 2 macropa. Thermodynamic stability constants of the La 3+ complexes, however, were found to be 1 and 2 orders of magnitude lower than those of H 2 macropa for H 2 BZmacropa and H 2 BZ 2 macropa, respectively. The decrease in thermodynamic stability was rationalized via the use of density functional theory calculations. 225 Ac radiolabeling and serum stability studies with H 2 BZmacropa showed that this chelator compares favorably with H 2 macropa. Based on these promising results, a bifunctional version of this chelator, H 2 BZmacropa-NCS, was synthesized and conjugated to the antibody codrituzumab (GC33), which targets the liver cancer biomarker glypican-3 (GPC3). The resulting GC33-BZmacropa conjugate and an analogous GC33-macropa conjugate were evaluated for their 225 Ac radiolabeling efficiencies, antigen-binding affinities, and in vivo biodistribution in HepG2 liver cancer tumor-bearing mice. Although both conjugates were comparably effective in their radiolabeling efficiencies, [ 225 Ac]Ac-GC33-BZmacropa showed slightly poorer serum stability and biodistribution than [ 225 Ac]Ac-GC33-macropa. Altogether, these results establish H2BZmacropa-NCS as a new bifunctional chelator for the preparation of 225 Ac radiopharmaceuticals.

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

Redox Defect Thermochemistry of FeAl 2 O 4 Hercynite in Water Splitting from First-Principles Methods

Solar thermochemical hydrogen (STCH) production is a promising route to produce fuels from sunlight via high-temperature water splitting. However, efficient and technologically viable implementations of this process only allow a narrow window of thermodynamic boundary conditions that can be used to cycle the system, thus limiting the design space for suitable metal oxide redox mediators. An oxygen defect redox mechanism can contribute a favorable reduction entropy to expand this window, and computational evaluation of materials with high oxygen defect entropies could play a pivotal role in guiding the discovery and design of suitable oxides. This study employs first-principles calculations to investigate the redox mediating defect mechanism of the STCH candidate material, hercynite (FeAl 2 O 4 ). We compare the results of total energy calculations from density functional theory (DFT) with beyond-DFT approaches, including hybrid functionals and the random phase approximation, which are among the most advanced methods currently feasible for supercell defect calculations. Using the predicted formation energies, we perform thermodynamic modeling of FeAl2O4 reduction and oxidation via free energy minimization that incorporates ideal gas, configurational, and vibrational entropy contributions evaluated within the quasi-harmonic approximation. Special attention is devoted to understanding interactions among co-existing defects, such as the association of pairs and complexes of O vacancies and cation antisite defects, and the effect of mutually compensating defect charges. Our results corroborate the notion that the details of defect interactions can be decisive for the viability of hydrogen production within the desirable STCH process window.

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