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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization

Single-atom catalysts (SACs) minimize noble metal utilization and can alter the activity and selectivity of supported metal nanoparticles. However, the morphology of active centers, including single atoms and subnanometer clusters of a few atoms, remains elusive due to experimental challenges. The computational cost to describe numerous cluster shapes and sizes makes direct first-principles calculations impractical. We present a computational framework to enable structure determination for single-atom and subnanometer cluster catalysts. As a case study, we obtained the low energy structures of Pd n (n = 1-21) clusters supported on CeO 2 (111), which are critical components of automobile three-way catalysts. Trained on density functional theory data, a three-dimensional cluster expansion is established using statistical learning to describe the Hamiltonian and predict energies of supported Pdn clusters of any structure. Low energy stable and metastable structures are identified using a Metropolis Monte Carlo-based genetic algorithm in the canonical ensemble at 300 K. We observe that supported single atoms sinter to form bilayer clusters and large cluster isomers share similarities in both shape and energy, and elucidate the significance of the support and microstructure on cluster stability. We discovered a simple surrogate structure-energy model, where the energy per atom scales with the square root of the average first coordination number, which can be used to estimate energies and compare the stability of clusters. Our framework, applicable to any metal/support system, fills an important methodological gap to predict the stability of supported metal catalysts in the subnanometer regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Optimizing proton conductivity in zirconates through defect engineering

The alkaline-earth zirconates (CaZrO 3 , SrZrO 3 , and BaZrO 3 ) are under active investigation as solid-state electrolytes in hydrogen fuel cells. Their performance as proton conductors depends critically on the properties of acceptor dopants. Here, we use first-principles calculations to study the role of acceptors and point defects in incorporating protons through an oxygen-vacancy-mediated process. For CaZrO 3 , we find that Zr Ca antisites suppress formation of oxygen vacancies. Other intrinsic point defects are shown not to hinder performance. Common unintentional impurities, such as C and N, are not good acceptors but can incorporate in other configurations. Our results show that the effectiveness of common dopants such as Sc and Y is limited by self-compensation due to their incorporation on the "wrong" cation site, where they act as donors. We demonstrate that using alkali metal dopants overcomes this problem, as the formation energy of compensating donors is very high. Alkali metal dopants also have low binding energies for protons, reducing their tendency to act as traps and hence enhancing proton conductivity. As a result, our guidelines for choosing acceptor dopants and optimizing synthesis conditions can greatly improve the efficacy of these proton-conducting oxides as solid-state electrolytes.

08 HYDROGEN↗
DOE OSTI2014

Device characterization for design optimization of 4 junction inverted metamorphic concentrator solar cells

Quantitative electroluminescence (EL) and luminescent coupling (LC) analysis, along with more conventional characterization techniques, are combined to completely characterize the subcell JV curves within a fourjunction (4J) inverted metamorphic solar cell (IMM). The 4J performance under arbitrary spectral conditions can be predicted from these subcell JV curves. The internal radiative efficiency (IRE) of each junction has been determined as a function of current density from the external radiative efficiency using optical modeling, but this required the accurate determination of the individual junction current densities during the EL measurement as affected by LC. These measurement and analysis techniques can be applied to any multijunction solar cell. The 4J IMM solar cell used to illustrate these techniques showed excellent junction quality as exhibited by high IRE and a one-sun AM1.5D efficiency of 36.3%. This device operates up to 1000 suns without limitations due to any of the three tunnel junctions.

14 SOLAR ENERGY↗
DOE OSTI2020

Significantly increased Raman enhancement on defect-rich O-incorporated 1T-MoS 2 nanosheets

Improving charge transfer is the key to the performance of non-noble metal semiconductor-based surface enhanced Raman scattering (SERS) substrates. In this work, the O-incorporated 1T-MoS 2 nanosheets with rich sulfur defects (ID-MoS 2 ) are obtained by simple calcination of 1T-MoS 2 nanosheets in air atmosphere. Using rhodamine 6G (R6G) as typical probe molecules, ID-MoS 2 nanosheets show ultrahigh Raman enhancement effects with an enhancement factor of 1.24 × 10 7 due to sulfur defects and O incorporation in the 1T-MoS 2 lattice. First-principle density functional theory calculations suggest that the existence of sulfur defects and O incorporation significantly increase the Fermi energy level (E f ) and electronic density of states of ID-MoS 2 . Furthermore, O incorporation can enhance the interactions between the substrate and the adsorbed molecules through electrostatic and hydrogen bonding. All these improve the charge transfer resonance and result in the remarkable SERS activity of ID-MoS 2 nanosheets. This is the first study on the increasing SERS performance of semiconductor substrates by simultaneously employing defect and dopant incorporation. This study provides an approach to optimize the performance of semiconductor-based SERS substrates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Extended Lagrangian Excited State Molecular Dynamics

In this work, an extended Lagrangian framework for excited state molecular dynamics (XL-ESMD) using time-dependent self-consistent field theory is proposed. The formulation is a generalization of the extended Lagrangian formulations for ground state Born–Oppenheimer molecular dynamics [Phys. Rev. Lett. 2008 100, 123004]. The theory is implemented, demonstrated, and evaluated using a time-dependent semiempirical model, though it should be generally applicable to ab initio theory. The simulations show enhanced energy stability and a significantly reduced computational cost associated with the iterative solutions of both the ground state and the electronically excited states. Relaxed convergence criteria can therefore be used both for the self-consistent ground state optimization and for the iterative subspace diagonalization of the random phase approximation matrix used to calculate the excited state transitions. In conclusion, the XL-ESMD approach is expected to enable numerically efficient excited state molecular dynamics for such methods as time-dependent Hartree–Fock (TD-HF), Configuration Interactions Singles (CIS), and time-dependent density functional theory (TD-DFT).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Understanding the Redox Obstacles in High Sulfur-Loading Li–S Batteries and Design of an Advanced Gel Cathode

Lithium-sulfur batteries with a high energy density are being considered a promising candidate for next-generation energy storage. However, realization of Li-S batteries is plagued by poor sulfur utilization due to the shuttle of intermediate lithiation products between electrodes and its dynamic redistribution. To optimize the sulfur utilization, an understanding of its redox behavior is essential. Here in this paper, we report a gel cathode consisting of a polysulfide-impregnated O- and N-doped porous carbon and an independent, continuous, and highly conducting 3-dimensional graphite film as the charge-transfer network. This design decouples the function of electron conduction and polysulfide absorption, which is beneficial for understanding the sulfur redox behavior and identifying the dominant factors leading to cell failure when the cells have high sulfur content and insufficient electrolyte. In conclusion, this design also opens up new prospects of tuning the properties of Li-S batteries via separately designing the material functions of electron conduction and polysulfide absorption.

25 ENERGY STORAGE↗
DOE OSTI2017

Atomic Structure and Dynamics of Single Platinum Atom Interactions with Monolayer MoS 2

In this work, we have studied atomic level interactions between single Pt atoms and the surface of monolayer MoS 2 using aberration-corrected annular dark field scanning transmission electron microscopy at an accelerating voltage of 60 kV. Strong contrast from single Pt atoms on the atomically resolved monolayer MoS 2 lattice enables their exact position to be determined with respect to the MoS2 lattice, revealing stable binding sites. In regions of MoS 2 free from surface contamination, the Pt atoms are localized in S vacancy sites and exhibit dynamic hopping to nearby vacancy sites driven by the energy supplied by the electron beam. However, in areas of MoS 2 contaminated with carbon surface layers, the Pt atoms appear at various positions with respect to the underlying MoS 2 lattice, including on top of Mo and in off-axis positions. These variations are due to the Pt bonding with the surrounding amorphous carbon layer, which disrupts the intrinsic Pt–MoS 2 interactions, leading to more varied positions. Density functional theory (DFT) calculations reveal that Pt atoms on the surface of MoS 2 have a small barrier for migration and are stabilized when bound to either a single or double sulfur vacancies. DFT calculations have been used to understand how the catalytic activity of the MoS 2 basal plane for hydrogen evolution reaction is influenced by Pt dopants by variation of the hydrogen adsorption free energy. Finally, this strong dependence of catalytic effect on interfacial configurations is shown to be common for a series of dopants, which may provide a means to create and optimize reaction centers.

2D materials↗
DOE OSTI2015

Computational Study of Molecular Structure and Self-Association of Tri-n-butyl Phosphates in n-Dodecane

Tri-n-butyl phosphate is an important extractant used in solvent extraction process for the recovery of uranium and plutonium from spent nuclear fuel. To understand the fundamental molecular level behavior of extracting agents in solution, an atomistic parameterization study was carried out using the AMBER force field to model TBP molecule and n-dodecane molecule, a commonly used organic solvent, for molecular dynamics simulations. For validation of the optimized force field, various thermophysical properties of pure TBP and pure n-dodecane in the bulk liquid phase such as mass density, dipole moment, self-diffusion coefficient and heat of vaporization were calculated and compared favorably with experimental values. The molecular structure of TBPs in n-dodecane at various TBP concentrations was examined based on radial distribution functions and 2D potential mean force, which was used as criteria for identifying TBP aggregates. The dimerization constant of TBP in n-dodecane was also obtained and matches the experimental value. The U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences funded the work performed by LXD.

molecular dynamics simulations↗
DOE OSTI2024

The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B -mode delensing for improved constraints on inflation

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision σ⁡(r = 0) ≤ 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing B-modes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO’s power-spectrum-based foreground-cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT B-modes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial B-modes, we find that the 1⁢σ statistical uncertainty on r, σ⁡(r), decreases by 37% as a result of delensing. Tensor modes at the level of r = 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO’s nominal sensitivity level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Electronic structure of mononuclear Cu-based molecule from density-functional theory with self-interaction correction

In this paper, we investigate the electronic structure of a planar mononuclear Cu-based molecule [Cu(C 6 H 4 S 2 ) 2 ] z in two oxidation states ( z = –2, –1) using density-functional theory (DFT) with Fermi–Löwdin orbital (FLO) self-interaction correction (SIC). The dianionic Cu-based molecule was proposed to be a promising qubit candidate. Self-interaction error within approximate DFT functionals renders severe delocalization of electron and spin densities arising from 3 d orbitals. The FLO-SIC method relies on optimization of Fermi–Löwdin orbital descriptors (FODs) with which localized occupied orbitals are constructed to create SIC potentials. Starting with many initial sets of FODs, we employ a frozen-density loop algorithm within the FLO-SIC method to study the Cu-based molecule. We find that the electronic structure of the molecule remains unchanged despite somewhat different final FOD configurations. In the dianionic state (spin S = 1/2), FLO-SIC spin density originates from the Cu d and S p orbitals with an approximate ratio of 2:1, in quantitative agreement with multireference calculations, while in the case of SIC-free DFT, the orbital ratio is reversed. Overall, FLO-SIC lowers the energies of the occupied orbitals and, in particular, the 3 d orbitals unhybridized with the ligands significantly, which substantially increases the energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) compared to SIC-free DFT results. The FLO-SIC HOMO–LUMO gap of the dianionic state is larger than that of the monoanionic state, which is consistent with experiment. Our results suggest a positive outlook of the FLO-SIC method in the description of magnetic exchange coupling within 3 d -element-based systems.

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

Design and additive manufacturing of optimized electrodes for energy storage applications

Supercapacitors exhibit fast charging/discharging ability and have attracted considerable attention within the automotive, aerospace, and telecommunication industries. Porous carbons, prized for their high electrical conductivity and high surface area, have been attractive candidates for supercapacitor electrodes. Moving to thick electrodes is one strategy to further increase energy density due to a higher volume fraction of active material. However, thick electrodes suffer from sluggish charged species transport, which is why thin electrodes are currently favored. In this work, we investigate the use of computational optimization and additive manufacturing to design and fabricate thick porous electrodes with improved performance. Electrode performance was maximized by designing their morphologies via topology optimization and printing by projection micro stereolithography (PμSL) using commercial resin (PR48). The PR48 resin was then pyrolyzed (PR48-P) to create the final conductive electrode. The optimized PR48-P electrodes exhibited 99% improvement in capacitance compared to control electrodes printed with cubic lattice morphologies. To further improve performance, we formulated a resin combining graphene oxide (GO) and trimethylolpropane triacrylate (TMPTA). Electrodes printed with 3 wt% GO in TMPTA exhibited improved capacitance retention after pyrolysis compared to the PR48-P electrodes. Finally, this work demonstrates the benefits of using topology optimization to design electrodes and material development to improve functional properties of 3D printable electrodes.

25 ENERGY STORAGE↗
DOE OSTI2022

Formation of 6H-Ba 3 Ce 0.75 Mn 2.25 O 9 during Thermochemical Reduction of 12R-Ba 4 CeMn 3 O 12 : Identification of a Polytype in the Ba(Ce,Mn)O 3 Family

The resurgence of interest in a hydrogen economy and the development of hydrogen-related technologies has initiated numerous research and development efforts aimed at making the generation, storage, and transportation of hydrogen more efficient and affordable. Solar thermochemical hydrogen production (STCH) is a process that potentially exhibits numerous benefits such as high reaction efficiencies, tunable thermodynamics, and continued performance over extended cycling. Although CeO 2 has been the de facto standard STCH material for many years, more recently 12R-Ba 4 CeMn 3 O 12 (BCM) has demonstrated enhanced hydrogen production at intermediate H 2 /H 2 O conditions compared to CeO 2 , making it a contender for large-scale hydrogen production. However, the thermo-reduction stability of 12R-BCM dictates the oxygen partial pressure (pO 2 ) and temperature conditions optimal for cycling. In this study, we identify the formation of a 6H-BCM polytype at high temperature and reducing conditions, experimentally and computationally, as a mechanism and pathway for 12R-BCM decomposition. 12R-BCM was synthesized with high purity and then controllably reduced using thermogravimetric analysis (TGA). Synchrotron X-ray diffraction (XRD) data is used to identify the formation of a 6H-Ba 3 Ce 0.75 Mn 2.25 O 9 (6H-BCM) polytype that is formed at 1350 degrees C under strongly reducing pO 2 . Density functional theory (DFT) total energy and defect calculations show a window of thermodynamic stability for the 6H-polytype consistent with the XRD results. These data provide the first evidence of the 6H-BCM polytype and could provide a mechanistic explanation for the superior water-splitting behaviors of 12R-BCM.

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

Metal–organic frameworks as O 2 -selective adsorbents for air separations

Oxygen is a critical gas in numerous industries and is produced globally on a gigatonne scale, primarily through energy-intensive cryogenic distillation of air. The realization of large-scale adsorption-based air separations could enable a significant reduction in associated worldwide energy consumption and would constitute an important component of broader efforts to combat climate change. Certain small-scale air separations are carried out using N 2 -selective adsorbents, although the low capacities, poor selectivities, and high regeneration energies associated with these materials limit the extent of their usage. In contrast, the realization of O 2 -selective adsorbents may facilitate more widespread adoption of adsorptive air separations, which could enable the decentralization of O 2 production and utilization and advance new uses for O 2 . Here, we present a detailed evaluation of the potential of metal–organic frameworks (MOFs) to serve as O 2 -selective adsorbents for air separations. Drawing insights from biological and molecular systems that selectively bind O 2 , we survey the field of O 2 -selective MOFs, highlighting progress and identifying promising areas for future exploration. As a guide for further research, the importance of moving beyond the traditional evaluation of O 2 adsorption enthalpy, ΔH, is emphasized, and the free energy of O 2 adsorption, ΔG, is discussed as the key metric for understanding and predicting MOF performance under practical conditions. Based on a proof-of-concept assessment of O 2 binding carried out for eight different MOFs using experimentally derived capacities and thermodynamic parameters, we identify two existing materials and one proposed framework with nearly optimal ΔG values for operation under user-defined conditions. While enhancements are still needed in other material properties, the insights from the assessments herein serve as a guide for future materials design and evaluation. Computational approaches based on density functional theory with periodic boundary conditions are also discussed as complementary to experimental efforts, and new predictions enable identification of additional promising MOF systems for investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides

Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles–based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCoO 2 and LiNiO 2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA + U), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3d and O 2p orbitals as compared to GGA, resulting in a greater contribution from oxygen states to charge compensation upon delithiation in LiCoO 2 . We also find that the band gaps of Li-TM oxides increase linearly with the mixing parameter, enabling the straightforward determination of optimal mixing parameters based on GGA (α = 0.0) and HSE06 (α = 0.25) calculations. Our results also show that G 0 W 0 @ GGA + U band gaps of TM oxides ( M O , M = Mn , Co , Ni ) and LiCoO 2 agree well with experimental references, suggesting that G 0 W 0 calculations can be used as a reference for the calibration of the mixing parameter in cases when no experimental band gap has been reported.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Towards defect engineering in hexagonal MoS 2 nanosheets for tuning hydrogen evolution and nitrogen reduction reactions

Combined computational and experimental approaches were used to evaluate defective 2H-MoS 2 nanosheets for their activity and selectivity for hydrogen evolution reaction (HER) and nitrogen reduction reaction (NRR). Density functional theory calculations were used to understand the relationship between HER and NRR activity on the ideal basal MoS 2 plane, seven grain-boundaries, ten single-/few-atom vacancies and anti-sites, and zigzag and armchair edge sites. The results confirm that 2H-MoS 2 should contain several defects with high activity for HER: armchair and zigzag edges, VS vacancy, MoS 2 anti-site, and S-S and Mo-Mo grain boundaries. Considering Gibbs free energy change for all the steps in the NRR mechanism and kinetic barriers for a key NRR step, we have found that activation of perspective NRR selective sites in 2H-MoS 2 , namely V MoS6 and clusters of S-vacancies, would require large overpotential, conditions at which HER dominates. The DFT conclusions are supported by the electrochemical studies of NRR activity and selectivity under aqueous conditions, which show an increase in NRR activity but a decrease in Faradaic efficiency as applied cell potential becomes more negative. The results of this work therefore highlight the challenges in activating natural 2H-MoS 2 for NRR, which would require additional material engineering or reaction condition optimization as a way to suppress HER, decrease the NRR overpotential or preferentially both.

2H-MoS2↗
DOE OSTI2021

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study

We know that actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical to proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport. To tackle this problem, we adopted a machine-learning approach to study ThCl 4 -NaCl and UCl 3 -NaCl binary systems. The machine-learning potential, with the density functional theory accuracy, allows us to obtain long molecular dynamics trajectories (ns) for large systems (10 3 atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperature. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination-sphere lifetime. Our study also suggests that actinides in molten salts may not follow well known entropy-scaling laws.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗