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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Broadband Ultrafast Dynamics of Refractory Metals: TiN and ZrN

Transition metal nitrides have recently gained attention in the fields of plasmonics, plasmon-enhanced photocatalysis, photothermal applications, and nonlinear optics because of their suitable optical properties, refractory nature, and large laser damage thresholds. Here we report comparative studies of the transient response of films of titanium nitride (TiN), zirconium nitride (ZrN), and gold (Au) under femtosecond excitation. Broadband transient optical characterization helps to adjudicate earlier, somewhat inconsistent reports regarding hot electron lifetimes based upon single wavelength measurements. These pump–probe experiments show sub-picosecond transient dynamics only within the epsilon-near-zero window of the refractory metals. The dynamics are dominated by photoinduced interband transitions resulting from ultrafast electron energy redistribution. The enhanced reflection modulation in the epsilon-near-zero window makes it possible to observe the ultrafast optical response of these films at low pump fluences. These results indicate that electron–phonon coupling in TiN and ZrN is 25–100 times greater than in Au. Strong electron–phonon coupling drives the sub-picosecond optical response and facilitates greater lattice heating compared to Au, making TiN and ZrN promising for photothermal applications. The spectral response and dynamics of TiN and ZrN are only weakly sensitive to pump fluence and pump excitation energy. However, the magnitude of the response is much greater at higher pump photon energies and higher fluences, reaching peak observed values of 15% in TiN and 50% in ZrN in the epsilon-near-zero window.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The effects of electrically exploding gold bridgewires into inert and explosive powder beds

Abstract The particle velocity created in beds of both low-density inert sugar and explosive PETN as a function of distance from an exploding bridgewire was measured using optical velocimetry and a silvered PMMA window. As expected, more violent bridge-bursts (from a greater-stored-energy capacitive discharge unit) resulted in greater particle velocities and a better supported compaction wave in sugar. In all cases, ramp waves, not shocks, were observed in the inert sugar. Large window velocities were observed for very powerful bursts (up to 270 m/s), but bursts required for stochastic detonator operation conditions resulted in sugar/PMMA window velocities of only 8–10 m/s 0.85 mm from the bridge location. In contrast, after a distance of only 0.65 mm, a building shock wave was observed in PETN under both threshold and reliable firing conditions. Subsequently a hot-spot-driven shock-to-detonation (SDT) process was observed prior to full detonation. The measured buildup process accounts for $$\approx $$ ≈ 66% of the so-called excess transit time (ETT) between the observed and theoretical total function time for the particular exploding-bridge-wire (EBW) detonator studied. The remainder must occur in the powerful output pellet region. In contrast to a common understanding, the ETT is found to be a weak function of the discharge energy. Thus, the operation of the detonator after a bridge-burst energy-to-powder reaction transition process is found to be hot-spot-driven SDT in both the low- and high-density pellets.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Chemical preintercalation synthesis approach for the formation of new layered tungsten oxides

Tungsten oxide, WO 3 ·nH 2 O, is a unique layered oxide material that offers enhanced performance in electrochromic and energy storage applications. Herein, we report the formation of a new, never previously synthesized, Na-containing layered tungsten oxide phase, Na 0.20 WO 3 ·0.81H 2 O, using a chemical preintercalation approach. The structure and composition of this novel phase were investigated via microscopy, spectroscopy, and diffraction methods. Electrochemical cycling of Na 0.20 WO 3 ·0.81H 2 O electrodes revealed initial discharge capacities of 37.43 mAh g -1 , 480.8 mAh g -1 , and 253.2 mAh g -1 in aqueous H 2 SO 4 cells (potential window of - 0.2–0.8 V vs. Ag/AgCl), non-aqueous Li-ion cells (potential window of 0.1–4.0 V vs. Li/Li + ), and non-aqueous Na-ion cells (potential window of 0.1–4.0 V vs. Na/Na + ), respectively. Additionally, a reversible, pressure-induced color change from pale yellow to dark brown/black was observed for the Na 0.20 WO 3 ·0.81H 2 O sample when it was placed under pressures of 1000 psi or higher. Our results demonstrate the viability of chemical preintercalation synthesis approach to produce new oxide phases with interesting functional properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electron beam irradiation effects on bulk metals: a comparative study of polycrystalline versus single-crystalline structures

This study investigates the effects of electron beam (e-beam) irradiation on the mechanical and structural properties of eight bulk metallic samples, comprising both polycrystalline (PC) and single-crystalline (SC) forms of Ni, Cr, V, and Ti. These metals were evaluated as potential candidates for beam exit windows in high-power (MW-class) particle accelerators. The primary objective is to identify metals capable of withstanding the conditions of high-power/MW-class e-beam accelerators and serve effectively as exit windows. Selection criteria were based on each metal’s intrinsic properties, power dissipation capability, and irradiation-induced changes in mechanical behavior, including hardness, elastic modulus, and defect density. Comprehensive characterization was conducted using field-emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDS), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), and nanoindentation, performed both before and after exposure to a ~¿66 kGy dose from a 10 MeV e-beam accelerator. Results revealed that e-beam irradiation induced hardening in PC Ni, whereas PC Ti, commonly used in beam exit windows, exhibited softening. The observed softening in PC Ti is attributed to grain coarsening, elongation, and the formation of twins and twin boundaries, in contrast to the smaller, compressed grains in the pristine (Pr) PC Ti samples, consistent with the Hall–Petch relationship. The stresses due to twinning are small and insignificant in influencing the overall hardening of the PC Ti irradiated sample when compared to the stresses due to the dislocation density. Conversely, SC Ti samples exhibited irradiation-induced hardening. The SC Ti irradiated samples developed additional irradiation-induced modifications in crystallographic texture of (100), (101), (110), (200), (112), (004), and (211) as evidenced from the XRD results, which could probably explain the hardening effect that is caused by irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Seasonal Disorder in Urban Traffic Patterns: A Low Rank Analysis

This article proposes several advances to sparse nonnegative matrix factorization (SNMF) as a way to identify large-scale patterns in urban traffic data. The input to our model is traffic counts organized by time and location. Nonnegative matrix factorization additively decomposes this information, organized as a matrix, into a linear sum of temporal signatures. Penalty terms encourage this factorization to concentrate on only a few temporal signatures, with weights which are not too large. Our interest here is to quantify and compare the regularity of traffic behavior, particularly across different broad temporal windows. In addition to the rank and error, we adapt a measure introduced by Hoyer to quantify sparsity in the representation. Combining these, we construct several curves which quantify error as a function of rank (the number of possible signatures) and sparsity; as rank goes up and sparsity goes down, the approximation can be better and the error should decreases. Plots of several such curves corresponding to different time windows leads to a way to compare disorder/order at different time scalewindows. In this paper, we apply our algorithms and procedures to study a taxi traffic dataset from New York City. In this dataset, we find weekly periodicity in the signatures, which allows us an extra framework for identifying outliers as significant deviations from weekly medians. We then apply our seasonal disorder analysis to the New York City traffic data and seasonal (spring, summer, winter, fall) time windows. We do find seasonal differences in traffic order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Model of Grain Boundary Complexion Transitions and Grain Growth in Yttria-Doped Alumina

In this work, we present a physically-parameterized microstructure evolution model for the Yttria-doped alumina system. Yttria-doped alumina is a well-known ceramic system which undergoes first-order phase-like transitions at grain boundaries, which can radically alter interface properties. The change in interfacial properties in turn can radically change microstructure outcomes during processing, including the induction of abnormal grain growth modes. In this work, we develop a simulation that evolves alumina microstructure as a function of yttria concentration and temperature. In the window studied, we achieve strong agreement with reviewed experimental results in identifying the windows for large grains, small grains, abnormal grain growth, and complexion transition kinetics. We then apply the model to study and demonstrate how the possible inclusion of second-phase particles or uneven solute distribution profiles will impact microstructure evolution. It is found that particles do not significantly affect abnormal grain growth in the window studied (but do lead to reduced grain size through pinning effects). It is found that even modest amounts of solute inhomogeneity will result in substantial changes in microstructure outcomes, frequently leading to clusters of abnormal grains. This model largely corroborates the expectations and hypotheses made from recent experimental studies in oxide-doped alumina systems. Further, it is found that there exists a peak transition fraction for the system at which abnormal grain size tends to be maximized.

Grain Growth, Grain Boundary Complexion, abnormal ↗
DOE OSTI2022

National energy savings potential of cellular shades: A measurement and simulation study

Windows are major contributors to energy demand in residential homes because of their inferior thermal resistance compared with the opaque envelope, and sometimes from unwanted solar heat gain. Window attachments can help mitigate the energy demand by controlling the solar heat gains and enhancing window thermal resistance. Cellular shades have the potential of superior thermal performance compared with generic shades because of its honeycomb structure. Here, in this study, the team analyzed the energy savings potential of cellular shades in residential homes via experimental testing for two heating seasons and energy simulations. Five shading devices—three single-cell and two double cellular/cell-in-cell shades—were used to compare the performance with generic horizontal venetian blinds using two nearly identical side-by-side rooms in a residential home. The experimental testing showed daily heating energy savings in the range of 17%–36% compared with the case without shades. The experimental testing data also exhibited improvements in thermal comfort when using cellular shades. Additionally, energy simulations were performed to evaluate the energy savings potential of the cellular shades using a residential prototype home, which demonstrated energy savings up to 9 kWh/m2/year in cold climates. The total site energy savings for heating and cooling from cellular shades was up to ~9% for the home with a heat pump and up to ~15% for a home with a gas furnace compared with cases without any shading devices. The energy savings at a national scale were up to 14.6 TWh assuming a 20% penetration rate in residential homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Divide and conquer: Learning chaotic dynamical systems with multistep penalty neural ordinary differential equations

Forecasting high-dimensional dynamical systems is a fundamental challenge in various fields, such as geosciences and engineering. Neural Ordinary Differential Equations (NODEs), which combine the power of neural networks and numerical solvers, have emerged as a promising algorithm for forecasting complex nonlinear dynamical systems. However, classical techniques used for NODE training are ineffective for learning chaotic dynamical systems. In this work, we propose a novel NODE-training approach that allows for robust learning of chaotic dynamical systems. Here, our method addresses the challenges of non-convexity and exploding gradients associated with underlying chaotic dynamics. Training data trajectories from such systems are split into multiple, non-overlapping time windows. In addition to the deviation from the training data, the optimization loss term further penalizes the discontinuities of the predicted trajectory between the time windows. The window size is selected based on the fastest Lyapunov time scale of the system. Multi-step penalty(MP) method is first demonstrated on Lorenz equation, to illustrate how it improves the loss landscape and thereby accelerates the optimization convergence. MP method can optimize chaotic systems in a manner similar to least-squares shadowing with significantly lower computational costs. Our proposed algorithm, denoted the Multistep Penalty NODE, is applied to chaotic systems such as the Kuramoto-Sivashinsky equation, the two-dimensional Kolmogorov flow, and ERA5 reanalysis data for the atmosphere. It is observed that MP-NODE provide viable performance for such chaotic systems, not only for short-term trajectory predictions but also for invariant statistics that are hallmarks of the chaotic nature of these dynamics.

Chaotic dynamical systems↗
DOE OSTI2026

Local reduced-order modeling for electrostatic plasmas by physics-informed solution manifold decomposition

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. Here, in this work, we develop data-driven reduced-order models (ROMs) for collisionless electrostatic plasma dynamics, based on the kinetic Vlasov-Poisson equation. Our ROM approach projects the equation onto a linear subspace defined by the proper orthogonal decomposition (POD) modes. We introduce an efficient tensorial method to update the nonlinear term using a precomputed third-order tensor. We capture multiscale behavior with a minimal number of POD modes by decomposing the solution manifold into multiple time windows and creating temporally local ROMs. We consider two strategies for decomposition: one based on the physical time and the other based on the electric field energy. Applied to the 1D1V Vlasov–Poisson simulations, that is, prescribed E-field, Landau damping, and two-stream instability, we demonstrate that our ROMs accurately capture the total energy of the system both for parametric and time extrapolation cases. The temporally local ROMs are more efficient and accurate than the single ROM. In addition, in the two-stream instability case, we show that the energy-windowing reduced-order model (EW-ROM) is more efficient and accurate than the time-windowing reduced-order model (TW-ROM). With the tensorial approach, EW-ROM solves the equation approximately 90 times faster than Eulerian simulations while maintaining a maximum relative error of 7.5% for the training data and 11% for the testing data.

Electrostatic plasmas↗
DOE OSTI2022

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Insights into radiation resistance of titanium alloys from displacement cascade simulations

Radiation damage in beam window materials limits the use of high power proton beams in high energy physics research. The alloy Ti-6Al-4V is presently used as a beam window material but a prospective alternative, Ti-15V-3Cr-3Sn-3Al has been proposed. Since both these alloys contain dual phases at room temperature, we compare the radiation damage in the α and ß-phases of these two materials via primary knock-on atom (PKA) cascade simulations in the 10-40keV energy range. At PKA energies 30 and 40keV, the number of Frenkel pairs in the ballistic stage is higher in the ß-phase of Ti-6Al-4V than that in the ß-phase of Ti-15V-3Cr-3Sn-3Al almost by a factor of 2. The α-phase, of both these alloys, by far outperforms the ß-phases of the two alloys, both in terms of damage during the ballistic stage and in terms of the surviving defects. The average displacement threshold energy (E d ) in the α-phase of both alloys was found to be 66eV while that in the ß-phase of Ti-15-3 was 55 eV and in the ß-phase of Ti-6-4 was 46. Further, while the number of surviving defects is almost equal in both alloys, the vacancy and interstitial clustering mechanisms differ notably, which can impact the degree of radiation hardening and loss of ductility. Our simulations show larger vacancy and interstitial clusters form in Ti-6Al-4V as compared to that in Ti-15-3-3-3 alloy. These results indicate that Ti-15-3-3-3 alloys may be a promising candidate for next generation beam window material with a higher radiation tolerance than the existing Ti-6-4 alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Energy savings and life cycle cost analysis of advanced double skin facade system applied to old apartments in South Korea

South Korea is one of the most densely populated countries in the world, and the population density in urban areas is much higher among others. Apartments are the most common form of residential buildings due to their high population density. More than 60% of domestic residential buildings are apartments, with more than 10 million households. The high population density is a problem that has long plagued South Korea because more than 45% of apartments are old apartments that are more than 20 years old. Old apartment buildings have low thermal performance that results in lots of energy consumption. Balconies, which worked as a thermal buffer, are also being removed by residents to expand indoor space. According to the green remodeling project supported by the Korean government, the typical retrofitting method is replacing external windows with the high-efficiency window in old apartments in South Korea. Here, this paper proposes a retrofitting method using an extended double-skin façade (DSF) system that replaces exterior windows and acts as a thermal buffer. The simulation model is developed with the EnergyPlus simulation program to conduct energy performance analyses. The simulation model has been calibrated using actual experimental data collected between October 1, 2019, and January 15, 2020. Results show that the cooling, heating, and lighting energy can be reduced up to 44.1% by fully utilizing electric energy generated by solar PV panels integrated with the DSF system. The payback period is about 15 years based on the energy price provided by the utility company. Although the payback period is long, it has great potential of energy savings and CO 2 emission reductions. The DSF system should be considered as a way of renovation, considering other factors such as increased real estate values and energy cost increases in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Using dynamic mode decomposition to predict the dynamics of a two-time non-equilibrium Green’s function

Computing the numerical solution of the Kadanoff–Baym equations, a set of nonlinear integral differential equations satisfied by the two-time Green's functions derived from many-body perturbation theory for a quantum many-body system away from equilibrium, is a challenging task. Recently, we have successfully applied dynamic mode decomposition (DMD) to construct a data driven reduced order model that can be used to extrapolate the time-diagonal of a two-time Green's function from numerical solutions of the KBE within a small time window. In this paper, we extend the previous work and use DMD to predict off-diagonal elements of the two-time Green's function. We partition the two-time Green's function into a number of one-time functions along the diagonal and subdiagonals of the two-time window as well as in horizontal and vertical directions. We use DMD to construct separate reduced order models to predict the dynamics of these one-time functions in a two-step procedure. We extrapolate along diagonal and several subdiagonals within a subdiagonal band of a two-time window in the first step. In the second step, we use DMD to extrapolate the Green's function outside of the sub-diagonal band. In conclusion, we demonstrate the efficiency and accuracy of this approach by applying it to a two-band Hubbard model problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Design of enhanced porous organic cage solubility in Type 2 porous liquids

Decreasing cost of technologies for direct air capture of carbon can be achieved through the design of new materials with high CO 2 selectivity that can be incorporated into existing industrial processes. An emerging class of materials for these applications are porous liquids (PLs). PLs are mixtures of porous hosts and solvents with intrinsic porosity due to steric exclusion of solvent from inside the porous host. It is currently unknown how solvent -porous host interactions affect porous host solubility in the bulk solvent. Here, in this study, density functional theory simulations were used to investigate interactions between nine solvents and a CC13 porous organic cage (POC). Calculations identified that solvent molecules were the most stable when placed either inside the CC13 POC or in the pore window compared to interfacial binding sites. Structural changes to the CC13 POC correlated with reported experimental solubilities, including expansion of the CC13 POC with solvent molecule infiltration and expansion or contraction of the pore window. Based on these results, new PL design guidelines should include compositions with (1) high concentrations of POCs with flexible cage structures that can expand when solvated and (2) solvent molecule-POC combinations that contract the pore window during solvent molecule-host binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Critical role of solvation on CC13 porous organic cages for design of porous liquids

Efficient carbon capture requires the design of new materials with high CO 2 selectivity and gas adsorption capacity that can be incorporated into existing industrial processes. Porous liquids (PLs) are promising candidate materials that consist of a nanoporous host and a solvent forming a liquid with permanent porosity based on exclusion of the solvent from the interior of the nanoporous host. Stable PLs are based on solvent-nanoporous host interactions, which can be evaluated through molecular simulations. Here, time- and temperature-dependent density functional theory simulations were performed between four solvents, 2-bromophenol, 4-methylphenol, 2,4-dimethylphenol, and cyclohexanone and the CC13 porous organic cage (POC) as a prototypical PL composition. Overall, minimal reactions occurred in the PL including no changes in the POC structure. Additionally, POC-solvent coordination occurred through interactions of neighboring functional groups such as methyl/bromide and hydroxyl on the solvent molecules with the POC surface. Therefore, the location rather than the number of functional groups on the solvent molecule controls the POC-solvent interactions. Additionally, the POC pore window contracted or expanded up to 8% during solvation, which correlates with the experimental solubility and static solvent-POC binding, where solvents that caused less contraction of the POC pore window increased POC solubility. Finally, these results allow for the design of optimized POC-based PL compositions based on solvent-nanoporous host binding and variation in the pore window during solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

High-throughput experimentation for microstructural design in additively manufactured 316L stainless steel

In the present study, a combination of high-throughput (HT) and low-throughput (LT) techniques was used to rapidly determine the processing window and generate processing maps for Selective Laser Melting (SLM) of 316L stainless steel. The HT method includes the fabrication of hundreds of hex nut-shaped specimens, each processed with a unique combination of laser power, scanning speed, and hatch spacing. An easily removable scaffolding permitted rapid sample extraction from the base plate, thus saving machining cost and time. Hardness and immersion density measurements were used for HT characterization to identify a processing window for maximum strength and density. Within the defined processing window, a low-throughput (LT) microstructural interrogation of specimens were performed. The microstructural analysis included quantification at various length scales (i.e., grains size and morphology, texture, primary dendrite arm spacing, and melt pool geometry analysis). Microstructure-based processing maps as a function of volumetric energy density were generated. The combination of HT and LT methods produced a predictive relationship between hardness and primary dendrite arm spacing using a Hall-Petch relationship. A model is proposed to explain the dependence of microstructure on the melt pool geometry. Here, the HT method can be applied for the microstructural design of SLM-fabricated components in other alloys.

316L stainless steel↗
DOE OSTI2020

Experimental demonstration and performance evaluation of a complex fenestration system for daylighting and thermal harvesting

Two significant design strategies for mitigating building energy consumption are daylight redirection and solar energy harvesting. Effective daylighting implementation enhances the amount of useful natural light within a space and offsets the need for electric lighting. Solar energy harvesting systems can mitigate energy costs from mechanical systems by managing incoming thermal loads or capturing solar energy that can be used to supplement thermal systems in the building. While there are many available façade-based technologies that can perform daylighting or solar thermal energy harvesting, there remains a limitation in available systems that can perform both of them simultaneously. This paper, describes the design and experimental demonstration of a Liquid Filled Prismatic Louver (LFPL) system, which combines both energy-saving strategies. The LFPL system was installed in a south-facing room in New York City and evaluated for indoor daylight penetration and potential for thermal energy harvesting. Daylight redirection is achieved through the prismatic louver geometry and proper orientation, whereas thermal energy harvesting is achieved through IR absorption from the liquid (e.g., water) within the prisms. Daylighting performance was evaluated by illuminance measurements at key locations within the space, whereas thermal harvesting performance was evaluated through temperature measurements and thermal imaging analysis. We show that the LFPL system, with all prismatic elements oriented at the same angle, achieve a 2-fold and 8-fold enhancement in daylight redirection to the ceiling, for prism orientations of 10° and 20°, respectively. We also demonstrate the system’s capability to adjust to specific lighting needs, within the space, through the dynamic individual orientation of prismatic elements; thus, achieving a concentrated ceiling illuminance enhancement of ~100 times and ~200 times at 2.5 and 4.3 m away from the window sill, providing workplane illuminance enhancement of 6 and 2 times more than in the case of the control room with regular windows. Furthermore, we illustrate a reduction of potential heating loads at locations close to the window from the combination of infrared absorption in the water volume and the redirection of the incoming solar radiation, leading to a reduction of the workplane temperature by an average of 7–10 °C.

14 SOLAR ENERGY↗
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↗