SEARCH · Engineering Papers

Results for “thermodynamics of computing”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,693 records · Page 94

All sources NASA NTRS DOE OSTI

NASA NTRS1985

Statistical mechanics of light elements at high pressure. VII - A perturbative free energy for arbitrary mixtures of H and He

A model free energy is presented which accurately represents results from 45 high-precision Monte Carlo calculations of the thermodynamics of hydrogen-helium mixtures at pressures of astrophysical and planetophysical interest. The free energy is calculated using free-electron perturbation theory (dielectric function theory), and is an extension of the expression given in an earlier paper in this series. However, it fits the Monte Carlo results more accurately, and is valid for the full range of compositions from pure hydrogen to pure helium. Using the new free energy, the phase diagram of mixtures of liquid metallic hydrogen and helium is calculated and compared with earlier results. Sample results for mixing volumes are also presented, and the new free energy expression is used to compute a theoretical Jovian adiabat and compare the adiabat with results from three-dimensional Thomas-Fermi-Dirac theory. The present theory gives slightly higher densities at pressures of about 10 megabars.

Hubbard, W. B.↗

DOE OSTI2022

Flexocaloric effect in superelastic materials

We present a combined theoretical–experimental study of flexocaloric effects in superelastic materials exhibiting structural transitions. We study a Ginzburg–Landau model combined with a vibrational model for a beam near a ferroelastic transition loaded with a three-point bending setup. We also perform experiments on a Cu–Al–Ni single crystal undergoing a martensitic transition. We measure bent beam profiles, vertical force vs vertical deflection during a slow isothermal process, time evolution of the bending and unbending amplitudes, and the evolution of temperature profiles. We also compute the evolution of heat source and heat sink profiles. Finally, we study the location of acoustic emission events during the bending/unbending experiment. Our observations are consistent with the model predictions and allow us to identify the main physical parameters relevant for flexocaloric applications.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Melting curves of ice polymorphs in the vicinity of the liquid–liquid critical point

The possible existence of a liquid–liquid critical point in deeply supercooled water has been a subject of debate due to the challenges associated with providing definitive experimental evidence. The pioneering work by Mishima and Stanley [Nature 392, 164–168 (1998)] sought to shed light on this problem by studying the melting curves of different ice polymorphs and their metastable continuation in the vicinity of the expected liquid–liquid transition and its associated critical point. Based on the continuous or discontinuous changes in the slope of the melting curves, Mishima [Phys. Rev. Lett. 85, 334 (2000)] suggested that the liquid–liquid critical point lies between the melting curves of ice III and ice V. Herein we explore this conjecture using molecular dynamics simulations with a machine learning model based on ab initio quantum-mechanical calculations. We study the melting curves of ices III, IV, V, VI, and XIII and find that all of them are supercritical and do not intersect the liquid–liquid transition locus. We also find a pronounced, yet continuous, change in the slope of the melting lines upon crossing of the liquid locus of maximum compressibility. Finally, we analyze the literature in light of our findings and conclude that the scenario in which the melting curves are supercritical is favored by the most recent computational and experimental evidence. Although the preponderance of evidence is consistent with the existence of a second critical point in water, the behavior of ice polymorph melting lines does not provide strong evidence in support of this viewpoint, according to our calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A combined experimental and machine learning exploration of Ti 2-x Zr x MnCrFeNi high entropy Laves hydrides

A series of high entropy AB 2 -type Ti 2-x Zr x MnCrFeNi alloys (x = 0.6, 0.7, 0.8, 0.9, 1.0, 1.1 and 1.2) were synthesized to investigate their potential for hydrogen storage and chemical compression. The influence of the Ti/Zr ratio was explored in terms of structural, microstructural and thermodynamic properties. The storage capacity together with the reaction enthalpy and entropy changes of the synthesized high entropy alloys were compared to predictions from Machine Learning (ML) to investigate changes in these properties across the explored composition space. The results revealed that a decreasing Zr content consistently lowered the hydride formation enthalpy and increased the plateau pressure from 8 to >90 bar H 2 at 25 °C, in good agreement with ML predictions. Selected compositions (x = 1.0 and 1.2) demonstrated reversible hydrogen storage capability over 150 cycles, with capacities of 1.34–1.40 wt % H 2 and remarkable reaction kinetics (<4 min) at ambient temperature. These experimental and computational findings highlight the potential of this Laves-HEA system as tuneable, stable, and cost-effective materials suitable for long-term operations in stationary hydrogen storage and compression applications.

36 MATERIALS SCIENCE↗

NASA NTRS2001

Simplified Analysis of Pulse Detonation Rocket Engine B1owdown Gasdynamics and Performance

Pulsed detonation rocket engines (PDREs) have generated considerable research interest in recent years as a chemical propulsion system potentially offering improved performance and reduced complexity compared to conventional rocket engines. The detonative mode of combustion employed by these devices offers a thermodynamic advantage over the constant-pressure deflagrative combustion mode used in conventional rocket engines and gas turbines. However, while this theoretical advantage has spurred a great deal of interest in building PDRE devices, the unsteady blowdown process intrinsic to the PDRE has made realistic estimates of the actual propulsive performance problematic. The recent review article by Kailasanath highlights some of the difficulties in comparing the available experimental measurements with numerical models. The goal of this paper is to improve understanding of PDRE blowdown gasdynamics and performance issues through use of a simplified model that captures the essential features of the unsteady blowdown process, and yet remains computationally inexpensive. The PDRE system studied here is highly idealized, consisting of a constant-area detonation tube with one end closed and the other end open to the environment. The tube is prefilled with a gaseous propellant mixture with no initial velocity or outflow to the environment. The detonation is initiated instantaneously at the closed end of the device. Chapman-Jouguet (C-J) post-detonation gas conditions are calculated using the CET89 version of the NASA thermochemical code. The I-D, unsteady method of characteristics is used to calculate the flowfield following the detonation front. See the compressible flow texts by Thompson and Zucrow and Hoffman for details of this method. Parametric studies of the effect of mixture stoichiometry, fill temperature, and blowdown pressure ratio on performance are reported. A comparison of the performance of an idealized straight-tube PDRE with a conventional steady-state rocket engine is provided. The effect of constant-gamma and equilibrium chemistry assumptions is also examined. Additionally, in order to form an assessment of the accuracy of the model, the flowfield time history is compared to experimental data from Stanford University.

Morris, Christopher I.↗

DOE OSTI2023

REYNO: A Reactive Hydrodynamics Modeling Suite

REYNO is a Python library that is primarily designed as a platform for the agile development and testing of novel reactive flow models. Equations of state and multi-step rate laws can be implemented using the provided class hierarchy with different thermodynamic closure conditions. The library includes a one-dimensional Lagrangian hydrodynamic solver to simulate multi-material reactive or inert problems in planar, cylindrical, or spherical coordinates. Custom time-dependent boundary conditions are also available for problems such as ramp compression. This document describes the different numerical methods and algorithms that are included in REYNO.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2003

Microelectromechanical System (MEMS) Device Being Developed for Active Cooling and Temperature Control

High-capacity cooling options remain limited for many small-scale applications such as microelectronic components, miniature sensors, and microsystems. A microelectromechanical system (MEMS) using a Stirling thermodynamic cycle to provide cooling or heating directly to a thermally loaded surface is being developed at the NASA Glenn Research Center to meet this need. The device can be used strictly in the cooling mode or can be switched between cooling and heating modes in milliseconds for precise temperature control. Fabrication and assembly employ techniques routinely used in the semiconductor processing industry. Benefits of the MEMS cooler include scalability to fractions of a millimeter, modularity for increased capacity and staging to low temperatures, simple interfaces, limited failure modes, and minimal induced vibration. The MEMS cooler has potential applications across a broad range of industries such as the biomedical, computer, automotive, and aerospace industries. The basic capabilities it provides can be categorized into four key areas: 1) Extended environmental temperature range in harsh environments; 2) Lower operating temperatures for electronics and other components; 3) Precision spatial and temporal thermal control for temperature-sensitive devices; and 4) The enabling of microsystem devices that require active cooling and/or temperature control. The rapidly expanding capabilities of semiconductor processing in general, and microsystems packaging in particular, present a new opportunity to extend Stirling-cycle cooling to the MEMS domain. The comparatively high capacity and efficiency possible with a MEMS Stirling cooler provides a level of active cooling that is impossible at the microscale with current state-of-the-art techniques. The MEMS cooler technology builds on decades of research at Glenn on Stirling-cycle machines, and capitalizes on Glenn s emerging microsystems capabilities.

Beach, Duane E.↗

DOE OSTI2025

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗

NASA NTRS1996

Coupled thermal/chemical/mechanical modeling of energetic materials in ALE3D

We must improve our ability to model the response of energetic materials to thermal stimuli and the processes involved in the energetic response. We have developed and used a time step option to efficiently and accurately compute the hours that the energetic material can take to react. Since on these longer film scales, materials can be expected to have significant motion, it is even more important to provide high-order advection for all components, including the chemical species. We show an example cook-off problem to illustrate these capabilities.

WEAPONS↗

DOE OSTI2022

Reversible Ligand Protonation in Noninnocent Constrained-Geometry-Like Group 4 Complexes

The proligands C 5 H 5 CMe 2 CHPhOx R (R = Me 2 , CHMe 2 , and CMe 3 ) react with M(NMe 2 ) 4 (M = Ti, Zr, and Hf) to give monodeprotonated (Ox R CHPhCMe 2 C 5 H 4 )M(NMe 2 ) 3 , doubly deprotonated (C 5 H 4 CMe 2 CPhOx R )M(NMe 2 ) 2 , or a mixture of both. The observed products depend on reaction conditions, the oxazoline substituent, and the metal center, with 4-t-butyl-oxazoline or Ti giving only the monodeprotonated (Ox R CHPhCMe 2 C 5 H 4 )M(NMe 2 ) 3 . Amine elimination from (Ox R CHPhCMe 2 C 5 H 4 )M(NMe 2 ) 3 to give (C 5 H 4 CMe 2 CPhOx R )M(NMe 2 ) 2 is reversible for 4,4-dimethyl- and 4-isopropyl-oxazoline-based ligands in Zr or Hf complexes. Temperature-dependent kinetic studies of the equilibration of (C 5 H 4 CMe 2 CPhOx Me2 )Zr(NMe 2 ) 2 , HNMe 2 and (Ox Me2 CHPhCMe 2 C 5 H 4 )Zr(NMe 2 ) 3 provide the experimental thermodynamic parameters ΔS° = -17.4 ± 2.6 cal·mol –1 K –1 and ΔH° = -6.8 ± 0.8 kcal·mol –1 . An Eyring plot of the rate constants, determined from the system as it approaches equilibrium, gives the activation entropy and activation enthalpy for the addition of (C 5 H 4 CMe 2 CPhOx Me2 )Zr(NMe 2 ) 2 and HNMe 2 as -36 ± 4 cal·mol –1 K –1 and 8.9 ± 1.3 kcal·mol –1 , respectively; the elimination of HNMe 2 from (Ox Me2 CHPhCMe 2 C 5 H 4 )Zr(NMe 2 ) 3 is characterized by ΔS ‡ = -19 ± 5 cal·mol –1 K –1 and ΔH ‡ = 15.7 ± 1.5 kcal·mol –1 . DFT computational models indicate a single-step, nonlinear transfer of the H between the benzylic position of the noninnocent, oxazoline-coordinated ligand and NMe 2 . Computations also confirm the negative activation entropy and the trends in the barriers support the experimental results. Together, these studies indicate the importance of steric effects from the oxazoline ligand, metal center, ancillary ligands, and leaving group on the shuttling of the proton between HNMe 2 and the noninnocent ligand. Finally, these effects suggest that coordination of oxazoline to the metal center is a key part of the benzylic deprotonation and noninnocent behavior of the cyclopentadienyl-oxazoline ligand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Discovery of a Wurtzite-like Cu 2 FeSnSe 4 Semiconductor Nanocrystal Polymorph and Implications for Related CuFeSe 2 Materials

I 2 -II-IV-VI 4 and I-III-VI 2 semiconductor nanocrystals have found applications in photovoltaics and other optoelectronic technologies because of their low toxicity and efficient light absorption into the near-infrared. Herein, we report the discovery of a metastable wurtzite-like polymorph of Cu 2 FeSnSe 4 , a member of the I 2 -II-IV-VI 4 family of semi-conductors containing only Earth-abundant metals. Density functional theory calculations on this metastable poly-morph of Cu 2 FeSnSe 4 indicate that it may be a superior semiconductor for solar energy and optoelectronics applications compared to the thermodynamically preferred stannite polymorph, since the former displays a sharper dispersion of energy levels near the conduction band minimum that can enhance electron mobility and suppress hot electron cooling. The experimental optical band gap was measured by the inverse logarithmic derivative method to be direct, in agreement with theory, and in the range of 1.48-1.59 eV. Mechanistic studies reveal that this metastable phase de-rives from intermediate Cu 3 Se 2 nanocrystals that serve as a structural template for the final hexagonal wurtzite-like product. We compare the chemistry of wurtzite-like Cu 2 FeSnSe 4 to the related CuFeSe 2 material system. Our experimental and computational comparisons between Cu 2 FeSnSe 4 and CuFeSe 2 help explain both the crystal chemistry of CuFeSe 2 that prevents it from forming wurtzite-like polymorphs and the essential role of Sn in stabilizing the metastable structure of Cu 2 FeSnSe 4 . Furthermore, this work provides insight into the importance of elemental composition when designing syntheses for metastable materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Alloying Effects on the Transport Properties of Refractory High-entropy Alloys

Additive Manufacturing (AM) has opened new frontiers for the design of refractory high-entropy alloys (HEAs) for high-temperature applications. The thermal conductivity of the AM feedstock is among the most important thermo-physical properties that control the melting and solidification process. Despite its significance, there remains a notable gap in both computational and experimental research concerning the thermal conductivity of HEAs. Here, we use density functional theory (DFT) to systematically investigate the alloying effects on the transport properties of Ti-Cr-Mo-W-V-Nb-Ta RHEAs, including electrical and thermal conductivities and Seebeck coefficient. The relaxation time of charge carriers is a key underlying parameter determining thermal conductivity that is exceedingly challenging to predict from first principles alone, and we thus follow the approach by Mukherjee, Satsangi, and Singh [Chem Mater 32, 6507 (2022)] to optimize the relaxation time for RHEAs. Here we validated thermal conductivity predictions on elemental solids, binary and ternary alloys, and RHEAs and compared them against thermodynamic (CALPHAD) predictions and our experiments with good correlations. To understand observed trends in thermal conductivity, we assessed the phase stability, electronic structure, phonon, and intrinsic- and tensile strength of down-selected RHEAs. Our electronic structure and phonon results connect well with the observed compositional trends for thermal transport in RHEAs. Our DFT assessment and CALPHAD predictions provide a unique design guide for RHEAs with tailored thermal conductivity, a critical consideration for AM and thermal-management applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enhanced Twist-Averaging Technique for Magnetic Metals: Applications Using Quantum Monte Carlo

In this study, we propose an improved twist-averaging (TA) scheme for quantum Monte Carlo methods that use converged Kohn–Sham or Hartree–Fock orbitals as the reference. This TA technique is tailored to sample the Brillouin zone of magnetic metals, although it naturally extends to nonmagnetic (NM) conducting systems. The proposed scheme aims to reproduce the reference magnetization and achieves charge neutrality by construction, thus avoiding the large energy fluctuations and the postprocessing needed to correct the energies. It shows the most robust convergence of total energy and magnetism to the thermodynamic limit (TDL) when compared to four other TA schemes. Diffusion Monte Carlo applications are shown on NM Al and ferromagnetic α-Fe. The cohesive energy of Al in the TDL shows an excellent agreement with the experimental result. Furthermore, the magnetic moments in α-Fe exhibit rapid convergence with an increasing number of twists.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Configuration Space Integration for Adsorbate Partition Functions: The Effect of Anharmonicity on the Thermophysical Properties of CO–Pt(111) and CH 3 OH–Cu(111)

A method for computing anharmonic thermophysical properties for adsorbates on metal surfaces has been extended to include libration, or frustrated rotation. Classical phase space integration is used with Monte Carlo sampling of the configuration space to obtain the partition function of CO on Pt(111) and CH 3 OH on Cu(111). A minima-preserving neural network potential energy surrogate is used within the integration routines. Direct state counting using discrete variable representation is used to benchmark the results. We find that the phase space integration approach is in excellent agreement with the direct state counting results. Comparison with standard models such as the harmonic oscillator indicates that anharmonicity contributes significantly to the thermodynamic properties of CH 3 OH on Cu(111). We find that there is also a considerable difference between the harmonic oscillator and phase space integration for CO on Pt(111), although the discrepancy can largely be attributed to the presence of multiple binding sites within the unit cell. We demonstrate that a multisite harmonic oscillator model might be sufficient for CO-Pt(111). A more thorough description of the potential energy surface, which can be achieved with phase space integration, is necessary for weakly bound adsorbates such as CH 3 OH. In conclusion, the thermophysical properties were used to calculate free energies of adsorption on the respective metals, and subsequently the equilibrium constants and Langmuir isotherms in relevant temperature ranges. The results show that the choice of model to obtain partition functions greatly affects the resulting surface coverages in kinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗

NASA NTRS2010

Emission Spectroscopic Measurements in the Plenum Region of the NASA IHF Arc Jet Facility

A newly designed segment with optical access was installed in the plenum chamber of the 60 MW Interaction Heating arcjet Facility at NASA Ames Research Center. This special segment has ports located off axis, and the optical fibers can be inserted into these ports. The special segment allows for optical examination of the arc-heated flow as it enters the plenum, and thus assists in determining estimates of the thermodynamic state of the inflow to the convergent section of the nozzle. In the present work, optical emission measurements have been made in VIS-NIR region (wavelengths between 500 nm to 900 nm) for two settings of the arc heater - a 6000 A condition (high condition) with the minimum amount of radial injection of cold air in the plenum, and a 3300 A condition (low condition) with significant amount of cold air injection to reduce the enthalpy of the arc-heated stream. The results presented here were obtained using an Acton SP300i spectrometer coupled to a Princeton Instruments PI-max intensified camera. In addition to the optical emission measurements, computations were performed for the flow in the plenum and radiation along lines of sight corresponding to the optical ports. Along the centerline, i.e., the longest line of sight across the plenum cross-section, there is good agreement between computations and measurements for the high enthalpy condition, although the off-axis radial profiles show some differences. For the low enthalpy condition, there are significant differences between computations and measurements. The current working hypothesis is that the computational model does not capture details of the mixing process in the plenum.

Winter, Michael W.↗

DOE OSTI2026

BMINN: Learning chemical potentials and parameters from voltage data for multi-phase battery modeling

Free-energy landscapes and chemical potentials govern the dynamics of phase transitions, transport, and stability in functional materials, yet they remain experimentally inaccessible under realistic operating conditions. Here we introduce a Bayesian model-integrated neural network (BMINN) that embeds physics-based formulations of non-autonomous partial differential-algebraic equations into probabilistic learning. This approach reconstructs hidden thermodynamics directly from macroscopic current-voltage data, providing quantitative access to metastable states, staging transitions, and energy barriers without synchrotron probes. Demonstrated on lithium-graphite electrodes, BMINN recovers full Gibbs free-energy landscapes with fidelity validated against operando X-ray diffraction. The framework generalizes across dynamical regimes, enabling accurate voltage prediction, internal state estimation, and inference of governing parameters. Beyond batteries, BMINN exemplifies a broadly applicable strategy for learning missing physics in multiphase, non-equilibrium systems, offering a new pathway to uncover hidden thermodynamic functions across condensed matter and materials physics.

25 ENERGY STORAGE↗

DOE OSTI2021

Factors Governing Oxygen Vacancy Formation in Oxide Perovskites

The control of oxygen vacancy (V O ) formation is critical to advancing multiple metal-oxide-perovskite-based technologies. In this work, we report the construction of a compact linear model for the neutral V O formation energy in ABO 3 perovskites that reproduces, with reasonable fidelity, Hubbard-U-corrected density functional theory calculations based on the state-of-the-art, strongly constrained and appropriately normed exchange-correlation functional. We obtain a mean absolute error of 0.45 eV for perovskites stable at 298 K, an accuracy that holds across a large, electronically diverse set of ABO 3 perovskites. Our model considers perovskites containing alkaline-earth metals (Ca, Sr, and Ba) and lanthanides (La and Ce) on the A-site and 3d transition metals (Ti, V, Cr, Mn, Fe, Co, and Ni) on the B-site in six different crystal systems (cubic, tetragonal, orthorhombic, hexagonal, rhombohedral, and monoclinic) common to perovskites. Physically intuitive metrics easily extracted from existing experimental thermochemical data or via inexpensive quantum mechanical calculations, including crystal bond dissociation energies and (solid phase) reduction potentials, are key components of the model. Beyond validation of the model against known experimental trends in materials used in solid oxide fuel cells, the model yields new candidate perovskites not contained in our training data set, such as (Bi,Y)(Fe,Co)O 3 , which we predict may have favorable thermochemical water-splitting properties. The confluence of sufficient accuracy, efficiency, and interpretability afforded by our model not only facilitates high-throughput computational screening for any application that requires the precise control of V O concentrations but also provides a clear picture of the dominant physics governing V O formation in metal-oxide perovskites.

08 HYDROGEN↗