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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pretreatment Effects on the Surface Chemistry of Small Oxygenates on Molybdenum Trioxide

Understanding surface reactions of biomass-derived oxygenates on metal oxides is important for designing catalysts for valorization of biomass. As such, This work elucidated the effect of different pretreatments on molybdenum trioxide (MoO 3 ) to understand how surface reactivity is controlled by the surface oxidation state. The catalyst was pretreated in oxidative, inert, and reducing environments. The inert and reducing pretreatments created oxygen vacancies on the catalyst surface that acted as active sites for the adsorption of oxygenated molecules, with the reducing pretreatment yielding a higher density of these active sites. Exposing the catalyst to an alcoholic solvent such as methanol also led to a partial reduction similar to the inert pretreatment. After pretreatment, the catalyst was exposed to ethanol, acetaldehyde, and crotonaldehyde with subsequent characterization by diffuse reflectance infrared spectroscopy (DRIFTS), temperature-programmed desorption (TPD), X-ray absorption near edge spectroscopy (XANES), and X-ray photoelectron spectroscopy (XPS). Density functional theory (DFT) was also used to determine adsorption configurations and energies of ethanol, acetaldehyde, and crotonaldehyde. Reduced surfaces were shown to have a stronger affinity for carbonyls, leading to a higher activity for the aldol condensation of acetaldehyde and ethanol to C 4 molecules. Catalysts pretreated in an oxidative environment were completely inactive toward chemisorption and reaction of acetaldehyde.

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

Atomic Three-Dimensional Investigations of Pd Nanocatalysts for Acetylene Semi-hydrogenation

Deciphering the three-dimensional (3D) insight into nanocatalyst surfaces at the atomic level is crucial to understanding catalytic reaction mechanisms and developing high-performance catalysts. Nevertheless, better understanding the inherent insufficiency of a long-range ordered lattice in nanocatalysts is a big challenge. Here, in this work, we report the local structure of Pd nanocatalysts, which is beneficial for demonstrating the shape-structure-adsorption relationship in acetylene hydrogenation. The 5.27 nm spherical Pd catalyst (Pd sph ) shows an ethylene selectivity of 88% at complete acetylene conversion, which is much higher than those of the Pd octahedron and Pd cube and superior to other reported monometallic Pd nanocatalysts so far. By virtue of the local structure revelation combined with the atomic pair distribution function (PDF) and reverse Monte Carlo (RMC) simulation, the atomic surface distribution of the unique compressed strain of Pd-Pd pairs in Pd sph was revealed. Density functional theory calculations verified the obvious weakening of the ethylene adsorption energy on account of the surface strain of Pd sph . It is the main factor to avoid the over-hydrogenation of acetylene. The present work, entailing shape-induced surface strain manipulation and atomic 3D insight, opens a new path to understand and optimize chemical activity and selectivity in the heterogeneous catalysis process.

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

Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning

Abstract Green hydrogen production is crucial for a sustainable future, but current catalysts for the oxygen evolution reaction (OER) suffer from slow kinetics, despite many efforts to produce optimal designs, particularly through the calculation of descriptors for activity. In this study, we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides, and adsorption energies of OER intermediates, which includes compositions up to quaternary and facets up to (555). We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting, and develop a machine learning model that accurately predicts these properties directly from the local chemical environment. We leverage these per-site properties to identify promising perovskites with high theoretical OER activity. The identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.

Chemistry↗
DOE OSTI2020

Chemical manipulation of hydrogen induced high p-type and n-type conductivity in Ga 2 O 3

Advancement of optoelectronic and high-power devices is tied to the development of wide band gap materials with excellent transport properties. However, bipolar doping (n-type and p-type doping) and realizing high carrier density while maintaining good mobility have been big challenges in wide band gap materials. Here P-type and n-type conductivity was introduced in β-Ga 2 O 3 , an ultra-wide band gap oxide, by controlling hydrogen incorporation in the lattice without further doping. Hydrogen induced a 9-order of magnitude increase of n-type conductivity with donor ionization energy of 20 meV and resistivity of 10 -4 Ω.cm. The conductivity was switched to p-type with acceptor ionization energy of 42 meV by altering hydrogen incorporation in the lattice. Density functional theory calculations were used to examine hydrogen location in the Ga 2 O 3 lattice and identified a new donor type as the source of this remarkable n-type conductivity. Positron annihilation spectroscopy measurements confirm this finding and the interpretation of the experimental results. This work illustrates a new approach that allows a tunable and reversible way of modifying the conductivity of semiconductors and it is expected to have profound implications on semiconductor field. At the same time, it demonstrates for the first time p-type and remarkable n-type conductivity in Ga 2 O 3 which should usher in the development of Ga 2 O 3 devices and advance optoelectronics and high-power devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Photoinduced electronic excitations drive polymerization of carbon monoxide: A first-principles study

Under pressure, carbon monoxide (CO) transforms into a polymer that can be recovered to ambient conditions. While this transformation can occur without additional stimuli, experimental observations have shown that laser irradiation can induce a similar transformation at reduced pressure. The resulting polymeric phase, which is metastable under ambient conditions, releases energy through decomposition into more stable configurations. Using time-dependent density functional theory and Born–Oppenheimer molecular dynamics simulations, we investigate the mechanism by which electronic excitation facilitates CO polymerization. Our calculations reveal that electronic excitation enhances carbon–carbon bonding, enabling polymerization at pressures significantly lower than those required by conventional compression methods. In conclusion, these findings suggest that a photo-assisted approach could be employed to synthesize novel, potentially energetic materials under less demanding pressure conditions.

Born-Oppenheimer molecular dynamics↗
DOE OSTI2021

An investigation of aqueous ammonium nitrate aerosols with soft X-ray spectroscopy

Aqueous aerosols are important in atmospheric chemistry, drug delivery, and human health. X-ray photoelectron spectroscopy (XPS), a surface-sensitive technique and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy which informs on the bulk, is deployed to study the solvation of ammonium nitrate (NH 4 NO 3 ). Aerosolised solutions of NH 4 NO 3 were introduced into a photoelectron spectrometer via an aerodynamic lens, and interrogated with soft X-ray photons, the resulting electrons were imaged via velocity map imaging. Density functional theory calculations were performed to compare with the measured binding energies of NH 4 + and NO 3 - solvated in water. The results reveal that the nitrate anion has a slight propensity for the surface, while both ammonium and nitrate ions are present in equal measure in the bulk.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Native defects in antiferromagnetic topological insulator MnBi 2 Te 4

Using scanning tunneling microscopy and spectroscopy, in this study we visualized the native defects in antiferromagnetic topological insulator MnBi 2 Te 4 . Two native defects, Mn Bi and Bi Te antisites, can be well resolved in the topographic images. Mn Bi tend to suppress the density of states at the conduction band edge. Spectroscopy imaging reveals a localized peaklike local density of state at ~ 80 meV below the Fermi energy. A careful inspection of topographic and spectroscopic images, combined with density functional theory calculation, suggests this results from Bi Mn antisites at Mn sites. The random distribution of Mn Bi and Bi Mn antisites results in spatial fluctuation of local density of states near the Fermi level in MnBi 2 Te 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dislocation loop evolution in Kr-irradiated ThO 2

Here, the early stage of microstructural evolution of ThO 2 , under krypton irradiation at 600, 800, and 1000°C, was investigated using in situ transmission electron microscopy (TEM). Dislocation loops grew faster, whereas their number density decreased with increasing irradiation temperature. Loop density was found to decrease with ion dose. Interstitial dislocation loops, including Frank loops with Burgers vector of $\textit{a}/3\langle111\rangle$ and perfect loops with Burgers vector of $\textit{a}/2\langle110\rangle$, were determined by traditional TEM and atomic resolution–scanning TEM techniques. Atomistic and mesoscale level modeling are performed to interpret experimental observations. The migration energy barriers of defects in ThO 2 were calculated using density-functional theory. The energetics of different dislocation loop types were studied using molecular dynamics simulations. Loop density and diameter were analyzed using a kinetic rate theory model that considers stoichiometric loop evolution. This analysis reveals that loop growth is governed by the mobility of cation interstitials, whereas loop nucleation is determined by the mobility of anion defects. Lastly, a rate theory model was used to extract the diffusion coefficients of thorium interstitials, oxygen interstitials, and vacancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Single-Walled Carbon Nanotubes with Confined Chalcogens as the Catalysts and Electrodes for Oxygen Reduction Reaction in Fuel Cells

The goal of this project is to synthesize and characterize a new non-metal electro-catalyst for oxygen reduction reaction (ORR) for fuel cell applications. The intended catalyst is a composite material composed of sulfur chains encapsulated in narrow diameter single-walled carbon nanotubes (S@SWNTs). S@SWNTs were successfully synthesized through sulfur vapor infusion method, and validated with Raman spectroscopy. However, the electrochemical analysis on the ORR catalytic activity of S@SWNTs indicated that it had low ORR catalytic activity. Our theoretical study based on density functional theory (DFT) revealed that the poor oxygen adsorption (low binding energy) on the surface of S@SWNTs was the bottleneck of the entire catalytic reaction. The focus of the project was subsequently pivoted to the development of a new non-noble metal ORR catalyst that could provide durability in acidic electrolyte. The hypothesis was to encapsulate small iron (Fe) clusters in SWNTs (Fe@SWNTs) can provide ORR electro-catalytic activity and long durability in acidic environment. DFT-based computational studies were carried out to explore the feasibility of the Fe@SWNTs catalyst. The theoretical study indicated that Fe@SWNTs indeed could catalyze the ORR with lower theoretical overpotential than platinum (Pt). However, its weaker bonding energy with oxygen was the bottleneck of the overall reaction. On the other hand, Fe clusters (composed of 7 Fe atoms) encapsulated in nitrogen-doped SWNTs (Fe 7 @N 4 WSNTs) showed proper oxygen adsorption by the Fe cluster and low theoretical overpotential of ORR. Comparing to the Fe single atom catalyst on N-doped SWNTs (Fe-N 4 SWNTs), which is one the best non-noble metal ORR catalysts reported in the literature, the Fe 7 @N 4 WSNTs showed lower overpotential and better resistance to acidic environment. Fe encapsulated N-doped SWNTs were synthesized with ferrocene as the Fe precursors through vapor infusion method, and experimental validate is underway. This study theoretically demonstrated the feasibility of a new type of non-noble metal electro-catalyst for ORR that could have high catalytic activity and long durability.

08 HYDROGEN↗
DOE OSTI2023

The Galaxy–Halo Connection of DESI Luminous Red Galaxies with Subhalo Abundance Matching

Abstract We use subhalo abundance and age distribution matching to create magnitude-limited mock galaxy catalogs at z ∼ 0.43, 0.52, and 0.63 with z -band and 3.4 μ m W 1-band absolute magnitudes and r − z and r − W 1 colors. From these magnitude-limited mocks, we select mock luminous red galaxy (LRG) samples according to the ( r − z )-based (optical) and ( r − W 1)-based (infrared) selection criteria for the LRG sample of the Dark Energy Spectroscopic Instrument (DESI) survey. Our models reproduce the number densities, luminosity functions, color distributions, and projected clustering of the DESI Legacy Surveys that are the basis for DESI LRG target selection. We predict the halo occupation statistics of both optical and IR DESI LRGs at fixed cosmology and assess the differences between the two LRG samples. We find that IR-based SHAM modeling represents the differences between the optical and IR LRG populations better than using the z band and that age distribution matching overpredicts the clustering of LRGs, implying that galaxy color is uncorrelated with halo age in the LRG regime. Both the optical and IR DESI LRG target selections exclude some of the most luminous galaxies that would appear to be LRGs based on their position on the red sequence in optical color–magnitude space. Both selections also yield populations with a nontrivial LRG–halo connection that does not reach unity for the most massive halos. We find that the IR selection achieves greater completeness (≳90%) than the optical selection across all redshift bins studied.

Berti, Angela M. (ORCID:0000000335826649)↗
DOE OSTI2024

Nitrogen Vacancy Centers in Diamond for Stress Sensing Applications: Theory and Experiments

Sensing of stress under high elevated environmental conditions with high resolution has critical importance for range of applications including earth’s subsurface scanning and geological CO2 storage monitoring. Using first principles density functional theory (DFT) approach combined with the theoretical modelling of low energy Hamiltonian, here we investigate a novel approach to detect unprecedented level of pressure by taking advantage of solid-state electron’s spin of Nitrogen vacancy (NV) centers in nanodiamond. We computationally explore the effect of strain on the defect band edges and band gaps by varying the lattice parameters of diamond supercell hosting a single NV center. A low energy Hamiltonian is developed that includes effect of stress on the energy level of ±1 spin manifold at the ground state. By quantifying the energy level shift and split, we predict the pressure sensing of up to 0.3 MPa/√Hz. We show superiority of the quantum sensing over traditional optical sensing techniques by discussing our results from DFT and theoretical modelling for the frequency shift per unit pressure. The proposed quantum stress sensing could be useful to measure earth’s subsurface vibrations. Our results open avenues for development of sensing technology with a high sensitivity and resolution under extreme pressure conditions that potentially has a wider applicability than existing pressure sensing technologies.

Paudel, Hari P.↗
DOE OSTI2023

Achieving Thermodynamic Stability of Single-Crystal Co-Free Ni-Rich Cathode Material for High Voltage Lithium-Ion Batteries

Ni-rich layered cathode materials are progressively considered as the standard configuration of high-energy electric vehicles by virtues of their high capacity and eliminated “range anxiety.” However, the poor cyclic stability and severe cobalt supply crisis would restrain their wide commercial applicability. Here, a cost-effective single-crystal Co-free Ni-rich cathode material LiNi 0.8 Mn 0.18 Fe 0.02 O 2 (NMF), which outperforms widely commercial polycrystalline LiNi 0.83 Co 0.11 Mn 0.06 O 2 (MNCM) and single-crystal LiNi 0.83 Co 0.11 Mn 0.06 O 2 (SNCM) is reported. Surprisingly, NMF can compensate for the reversible capacity loss under the designed conditions of high-temperature and elevated-voltage, achieving a competitive energy density compared with conventional MNCM or SNCM. Further, combining operando characterizations and density functional theory calculation, it is revealed that NMF cathode with improved dynamic structure evolution largely alleviates the mechanical strain issue commonly found in Ni-rich cathode, which can reduce the formation of intragranular cracks and improve the safety performance. Consequently, this new Co-free NMF cathode can achieve a perfect equilibrium between material cost and electrochemical performance, which not only reduces the production cost by >15%, but also demonstrates excellent thermal stability and cycling performance.

25 ENERGY STORAGE↗
DOE OSTI2024

High energy density picoliter-scale zinc-air microbatteries for colloidal robotics

The recent interest in microscopic autonomous systems, including microrobots, colloidal state machines, and smart dust, has created a need for microscale energy storage and harvesting. However, macroscopic materials for energy storage have noted incompatibilities with microfabrication techniques, creating substantial challenges to realizing microscale energy systems. Here, we photolithographically patterned a microscale zinc/platinum/SU-8 system to generate the highest energy density microbattery at the picoliter (10 −12 liter) scale. The device scavenges ambient or solution-dissolved oxygen for a zinc oxidation reaction, achieving an energy density ranging from 760 to 1070 watt-hours per liter at scales below 100 micrometers lateral and 2 micrometers thickness in size. The parallel nature of photolithography processes allows 10,000 devices per wafer to be released into solution as colloids with energy stored on board. Within a volume of only 2 picoliters each, these primary microbatteries can deliver open circuit voltages of 1.05 ± 0.12 volts, with total energies ranging from 5.5 ± 0.3 to 7.7 ± 1.0 microjoules and a maximum power near 2.7 nanowatts. We demonstrated that such systems can reliably power a micrometer-sized memristor circuit, providing access to nonvolatile memory. We also cycled power to drive the reversible bending of microscale bimorph actuators at 0.05 hertz for mechanical functions of colloidal robots. Additional capabilities, such as powering two distinct nanosensor types and a clock circuit, were also demonstrated. The high energy density, low volume, and simple configuration promise the mass fabrication and adoption of such picoliter zinc-air batteries for micrometer-scale, colloidal robotics with autonomous functions.

Robotics↗
DOE OSTI2020

Machine learning with bond information for local structure optimizations in surface science

Local optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between the molecule and the substrate. In this work, we show how the explicit modeling of different characteristics of the bonds in these systems improves the performance of machine learning methods for optimization. Furthermore, we introduce an anisotropic kernel in the Gaussian process regression framework that guides the search for the local minimum, and we show its overall good performance across different types of atomic systems. The method shows a speed-up of up to a factor of two compared with the fastest standard optimization methods on adsorption systems. Additionally, we show that a limited memory approach is not only beneficial in terms of overall computational resources but can also result in a further reduction of energy and force calculations.

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

Small bimetallic clusters Agn-1M (M = Au, Co, Cu, Ni, Pd, Pt; n = 3, 9, 15): Density functional theory and genetic algorithm

We investigated the effect of size and composition on the properties of bimetallic nanoclusters. The geometric structures, stabilities, and electronic properties of size-selected Ag n-1 M (M = Au, Co, Cu, Ni, Pd, Pt; n = 3, 9, 15) bimetallic nanoclusters are systematically analyzed using spin-polarized density functional theory (DFT) within the generalized gradient approximation (GGA). We determine the most stable geometries for these clusters using a genetic algorithm (GA) in combination with DFT. Our results show that doping pure silver clusters with an M atom (transition metal), referred to as a “guest atom”, increases the stability as compared to pure Ag n (n = 3, 9, 15) clusters. The results for various properties including formation energy per atom, electronic structure, magnetic moments, and vibrational density of states (VDOS) are evaluated as a function of both size and composition of the system. The adsorption of selected bimetallic clusters on hydroxylated alumina substrate shows weak binding and minor changes in geometric properties except for Ag 8 Pt.

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

Efficient Modeling of Structural, Electronic, and Optical Properties of Silver and Gold Metal Nanoclusters and Alloys Using Optimized SCC-DFTB Parameters

Computation of optical properties using conventional time-dependent density functional theory (TD-DFT) is time-consuming and memory-intensive. In this study, we investigate the accuracy and efficiency of the density functional tight binding (DFTB) framework with newly optimized Slater–Koster (SK) parameters for modeling the structural, electronic properties, and absorption spectra of silver and gold nanoclusters and their alloys. Our investigation of the ground state (GS) properties demonstrates that the newly developed GS-SK parameters enable DFTB to closely approximate DFT-calculated bond lengths for octahedron, tetrahedron, icosahedra, and truncated octahedron with sizes Ag n /Au n (n = 19, 20, 38, 55), nanoclusters and Ag 20 /Au 20 nanoalloys, with a maximum deviation of approximately 0.15 Å. Formation energy results indicate that the GS-SK parameters can closely estimate changes in formation energies with alloy composition, and the comparison of electronic structures for Ag 20 , Au 20 , and AgAu alloy nanoclusters using the DFTB approximation reveals good agreement in the projected density of states (DOS) profiles and energy levels. A second set of SK parameters, ES-SK, has been developed to describe excited state (ES) properties, including the absorption spectra of silver octahedron Ag 19 , tetrahedral Ag n (n = 20, 56, 84), truncated octahedron Ag 38 , and icosahedra Ag 55 closed-shell clusters and their gold and alloy counterparts over a broad range of alloy compositions. This parametrization uses TD-DFTB calculations and fine-tunes the d and p eigenvalues by comparing them to reference absorption spectra from first-principles TD-DFT. This enables the generation of absorption spectra that closely match the reference spectra when plasmon excitation is dominant, as demonstrated by studying the plasmonic properties of icosahedral Ag n and Au n (n = 309 and 561) nanoparticles. This includes the rapid loss in plasmon quality when Au partially replaces Ag in alloy clusters. Furthermore, these results provide a foundation for addressing computational bottlenecks in plasmonics and with new prospects for applications in the quantum plasmonics for bimetallic alloys.

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

An evaluation for geometries, formation enthalpies, and dissociation energies of diatomic and triatomic (C, H, N, O), NO 3 , and HNO 3 molecules from the PAW DFT method with PBE and optB88-vdW functionals

The structural geometries, formation enthalpies, and dissociation energies of all diatomic and triatomic molecules consisting of the four basic elements C, H, N, and/or O are calculated using the projector augmented wave density functional theory (DFT) method with the Perdew–Burke–Ernzerhof and optB88-vdW exchange-correlation functionals. The calculations are also extended to two larger molecules NO 3 and HNO 3 , which consist of four and five atoms, respectively. In total, 82 molecules or isomers are considered in the calculations. The geometric parameters including 42 bond lengths and 15 bond angles of these molecules calculated using the planewave DFT method are highly satisfactory, relative to the available experimental data. The error analysis is also performed for 49 formation enthalpies and 138 dissociation energies (including 51 atomization energies as well as the corresponding bond dissociation energies). The results are also compared with the previous data from various atomic-orbital-based methods for molecules and from similar or different planewave DFT methods for various solids and other molecules. This provides an informative and instructive evaluation especially for calculating the large-size material systems containing these small molecules as well as for developing the DFT methods further.

74 ATOMIC AND MOLECULAR PHYSICS↗