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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Molecular Level Understanding of Polyethylene Terephthalate (PET) Depolymerization in Base/Alcohol Hybrid Systems

Polyethylene terephthalate (PET) depolymerization in base/alcohol hybrid systems represents a promising low-energy approach for chemically recycling PET waste into valuable monomers. This study investigates the mechanistic pathways of PET depolymerization in NaOH/alcohol solutions, emphasizing the competing roles of hydroxide and alkoxide species. Utilizing a combination of experimental techniques, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations, we explore how factors such as base concentration, alcohol chain length, and pKa values of alcohols influence PET depolymerization efficiency and pathways. Our findings indicate that alkoxide ions (RO⁻) exhibit notably higher reactivity than hydroxide ions (HO⁻), favoring an alcoholysis pathway in the base/alcohol hybrid system. Experimental results across a series of C1 to C5 alcohols show that longer-chain alcohols, particularly 1-butanol, achieve higher PET conversion, although this does not align solely with simple nucleophilicity trends of alkoxides. While DFT calculations reveal comparable activation energies for various alkoxides in PET depolymerization, MD simulations underscore the significant role of alcohol chain length, with longer-chain alcohols forming more stable or frequent interactions with PET. Additionally, the alkoxide concentration, influenced by the alcohol’s pK a , directly impacts PET conversion. These suggest that PET depolymerization is governed by a balance between alkoxide concentration and alkoxide-PET interactions, rather than activation energies or nucleophilicity alone. From a practical perspective, incorporating long-chain alcohols as cosolvents may enhance process efficiency but increases raw material costs by approximately 30%. However, long-chain alcohols present a safer and more sustainable alternative to hazardous cosolvents such as dichloromethane. This work offers a molecular-level understanding of PET depolymerization in base/alcohol systems and provides insights into optimizing these systems for more efficient and sustainable PET recycling processes.

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

Yttrium Contenting Compositionally Complex Medium-Entropy Li-Garnet Electrolyte with Improved Ionic Conductivity

The compositionally complex medium/high-entropy design concept can greatly expand the categories and affect the properties of the materials. With such a designing concept, a medium-entropy Li-garnet electrolyte with appropriate yttrium content (formula Li 6.6 La 3 ZrNb 0.3 Ta 0.3 Hf 0.3 Y 0.1 O 12 ) shows a record-high ionic conductivity of ∼5.7 × 10 –4 S/cm, the highest reported for any single-site substituted high/medium-entropy Li-garnet. The assembled Li metal symmetric cells also show stable long-term cycling (0.1 mA/cm 2 for over 200 h). Neutron powder diffraction and Rietveld refinement results indicate that a competing conduction mechanism between (1) occupancy on high mobility of 96h sites and (2) the associated site vacancies and the bond length requires an appropriate content of Y for enhanced ionic conductivity. Li-ion hopping through the bottleneck can also contribute to the conductivity. Finally, density functional theory and Born–Oppenheimer molecular dynamics simulations also indicate the high mobility and number of hopping transitions of Li ions, contributing to the high ionic conductivity.

Li-garnet↗
DOE OSTI2021

Direct observation of kink evolution due to Hund’s coupling on approach to metal-insulator transition in NiS 2- x Se x

Understanding characteristic energy scales is a fundamentally important issue in the study of strongly correlated systems. In multiband systems, an energy scale is affected not only by the effective Coulomb interaction but also by the Hund’s coupling. Direct observation of such energy scale has been elusive so far in spite of extensive studies. Here, we report the observation of a kink structure in the low energy dispersion of NiS 2- x Se x and its characteristic evolution with x , by using angle resolved photoemission spectroscopy. Dynamical mean field theory calculation combined with density functional theory confirms that this kink originates from Hund’s coupling. We find that the abrupt deviation from the Fermi liquid behavior in the electron self-energy results in the kink feature at low energy scale and that the kink is directly related to the coherence-incoherence crossover temperature scale. Our results mark the direct observation of the evolution of the characteristic temperature scale via kink features in the spectral function, which is the hallmark of Hund’s physics in the multiorbital system.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiscale computational understanding and growth of 2D materials: a review

Abstract The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.

Momeni, Kasra↗
DOE OSTI2022

Pressure-induced concomitant topological and metal-insulator quantum phase transitions in Ce3Pd3Bi4

Abstract The electronic property and magnetic susceptibility of Ce 3 Pd 3 Bi 4 were systemically investigated from 18 to 290 K for varying values of cell volume using dynamic mean-field theory coupled with density functional theory. By extrapolating to zero temperature, the ground state of Ce 3 Pd 3 Bi 4 at ambient pressure is found to be a correlated semimetal due to insufficient hybridization. Upon applying pressure, the hybridization strength increases and a crossover to the Kondo insulator is observed at finite temperatures. The characteristic temperature signaling the formation of Kondo singlet, as well as the characteristic temperature associated with f -electron delocalization–localization change, simultaneously vanishes around a critical volume of 0.992 V 0 , suggesting that such metal–insulator transition is possibly associated with a quantum critical point. Finally, Wilson’s loop calculations indicate that the Kondo insulating side is topologically trivial, thus a topological transition also occurs across the quantum critical point.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deep learning workflow for the inverse design of molecules with specific optoelectronic properties

The inverse design of novel molecules with a desirable optoelectronic property requires consideration of the vast chemical spaces associated with varying chemical composition and molecular size. First principles-based property predictions have become increasingly helpful for assisting the selection of promising candidate chemical species for subsequent experimental validation. However, a brute-force computational screening of the entire chemical space is decidedly impossible. To alleviate the computational burden and accelerate rational molecular design, we here present an iterative deep learning workflow that combines (i) the density-functional tight-binding method for dynamic generation of property training data, (ii) a graph convolutional neural network surrogate model for rapid and reliable predictions of chemical and physical properties, and (iii) a masked language model. As proof of principle, we employ our workflow in the iterative generation of novel molecules with a target energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The role of ambient gas confinement, plasma chemistry, and focusing conditions on emission features of femtosecond laser-produced plasmas

Ultrafast laser ablation coupled with optical emission spectroscopy is currently under development for standoff detection of elements and their isotopes for a wide range of application areas. In this work, we explore the role of ambient air pressure during the interaction of an ultrafast laser beam with two metallic targets (brass and uranium) with significantly different oxygen gas-phase reactivity. Plasma plumes were generated by focusing ~800 nm, ~35 fs pulses from an ultrafast laser system using a long focal length lens with f = 1 m. Two-dimensional spectral imaging was performed over the pressure range of 30 mTorr-700 Torr air to evaluate emission dynamics, plasma chemistry, signal-to-background ratio, and characteristic parameters (i.e. excitation temperature, electron density). An increase in ambient air pressure during ultrafast laser ablation leads to plume confinement and subsequent changes in the emission dynamics due to plasma chemistry as well as changes in plasma generation conditions (i.e. focused fs laser ablation versus filament ablation). Ablation crater morphologies were also investigated via scanning electron microscopy. Results indicate atomic emission intensity and signal-to-background ratios peak at moderate pressure levels (~50-100 Torr air) for both targets studied, although plasma chemistry influences uranium emission signatures. The emission features of the uranium plasma at pressures = 10 Torr showed the presence of atoms and oxide molecules which are co-located within the plume. We also find filament ablation leads to wider, more shallow craters compared to focused laser ablation. Our study provides unique insight into the interplay between plume dynamics, confinement, and oxygen chemistry of fs laser-produced plasmas and how these phenomena evolve with changing ambient air pressure.

Laser-produced plasma↗
DOE OSTI2023

Design of high polarization low switching barrier hybrid improper ferroelectric perovskite oxide superlattices

Hybrid improper ferroelectricity is a useful tool to design ABO 3 /A'BO 3 polar superlattices from non polar building blocks. In this study, we have designed high polarization-low switching barrier hybrid improper ferroelectric superlattices with efficient polarization, and polarization-magnetization switching properties above room temperature, using density functional theory and ab initio molecular dynamics simulations. Superlattices with a chemical formula of (AAlO 3 ) m /(A'AlO 3 ) n , where m/n = 1/1, 1/3, 3/1, 1/5 and 5/1, A, A' = Lanthanide and Y cations are considered to outline the design principles behind polarization switching and (LaFeO 3 ) 3 /(CeFeO 3 ) 1 is investigated for polarization-magnetization switching. We find that the unconventional switching paths via out-of-phase rotation Q R- (a 0 a 0 c - ) and tilt precession QTP always yield lower switching barrier compared to those via in-phase rotation Q R+ (a 0 a 0 c + ) and tilt QT (a - a - c 0 ) of BO 6 octahedra. Results from ab initio molecular dynamics simulations estimate the temperature at which the lowest energy barrier can be overcome. Furthermore, it is possible to tune the polarization switching barrier by tuning the tolerance factor, A,A' cation radius mismatch and super lattice periodicity. For switching via Q R- , the switching barrier varies exponentially with rotation angle, indicating how high switching barrier is expected for systems, away from cubic symmetry. We provide a recipe to overcome such a bottleneck by tuning superlattice periodicity. Finally, we have proposed the multiferroic device application concept through a proposed polarization-temperature hysteresis loop and magnetization switching.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strain dependence of Auger recombination in 3 μm GaInAsSb/GaSb type-I active regions

We differentiate the effect of strain induced by lattice-mismatched growth from strain induced by mechanical deformation on cubic nonradiative Auger recombination in narrow-gap GaInAsSb/GaSb quantum well (QW) heterostructures. The typical reduction in the Auger coefficient observed with lattice-mismatched growth appears to be due to the concomitant compositional change rather than the addition of strain, with implications for mid-IR semiconductor laser design. We induced a range of internal compressive strain in five samples from -0.90% to -2.07% by varying the composition during the growth and mechanically induced a similar range of internal strain in analogous quantum well membrane samples. We performed time-resolved photoluminescence and differential reflectivity measurements to extract the carrier recombination dynamics, taken at 300 K with carrier densities from 2.7 × 10 18 cm -3 to 1.4 × 10 19 cm -3 . We observed no change with strain in the cubic Auger coefficient of samples that were strained mechanically, but we did observe a trend with strain in samples that were strained by the QW alloy composition. Measured Auger coefficients ranged from 3.0 × 1 0 - 29 cm 6 s -1 to 3.0 × 1 0 - 28 cm 6 s -1 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

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

Reaction processes at step edges on S-decorated Cu(111) and Ag(111) surfaces: MD analysis utilizing machine learning derived potentials

We report a variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M–S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal–sulfur complexes, especially MS 2 ; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal–sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.

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

Role of morphology in defect formation and photo-induced carrier instabilities in amorphous indium oxide

Ab initio molecular dynamics liquid-quench simulations and hybrid density functional calculations are performed to model the effects of room-temperature atomic fluctuations and photo-illumination on the structural and electronic properties of amorphous sub-stoichiometric In 2 O 2.96 . A large configurational ensemble is employed to reliably predict the distribution of localized defects as well as their response to the thermal and light activation. The results reveal that the illumination effects on the carrier concentration are greater in amorphous configurations with shorter In–O bond length and reduced polyhedral sharing as compared to the structures with a more uniform morphology. Further, the obtained correlation between the photo-induced carrier density and the reduction in the number of fully coordinated In-atoms implies that metal oxides with a significant fraction of crystalline/amorphous interfaces would show a more pronounced response to illumination. Photo-excitation also produces In–O 2 –In defects that have not been previously found in sub-stoichiometric amorphous oxides; these defects are responsible for carrier instabilities due to overdoping.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Mitigation of deceleration-phase Rayleigh–Taylor instability growth in inertial confinement fusion implosions

Rayleigh–Taylor growth during shell deceleration is one of the main limiting factors for target performance in inertial confinement fusion implosions. Here, using analytical scaling laws and hydrodynamic simulations, we show that such amplification can be mitigated by reducing the initial mass density in the central target region. The perturbation growth reduction is caused by a smaller hot-spot convergence ratio during deceleration, increased density scale length, and enhanced ablation stabilization. The required central density reduction can be achieved using the dynamic shell formation concept.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Resonant x-ray absorption of strong-field-ionized CF 3 Br

We report on an experimental and theoretical study of strong-field laser ionization of CF 3 Br followed by resonant x-ray absorption at the Br K-edge. Distinct 1s -> 4p, 5p Rydberg transitions of Br q+ (q = 1-4) atomic ions are observed and identified with Hartree-Fock-Slater and relativistic configuration interaction calculations. Time-dependent density functional theory and ab initio molecular dynamics calculations were performed to simulate the dissociative ionization process and the molecular orbitals for the q = 1-4 charge states. Measurements were made with both parallel and perpendicular linear polarizations of the laser and x-rays, but dichroism was not observed, indicating negligible alignment by the laser ionization process. This result is explained by calculations on atomic Br and the molecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

First-principles investigation of structure-property relationships in stable and metastable MXenes

Understanding the structure–property relationships in layered transition-metal carbides or nitrides, known as MXenes, is of critical importance for their rational design, synthesis, and application. However, the vast chemical and structural diversity of MXenes, stemming from their wide range of M and X elements, surface terminations, and different atomic coordination environments, makes it challenging to clearly understand these structure–property relationships. Here, in this work, we perform first-principles density functional theory (DFT) calculations and molecular dynamics (MD) simulations to comprehensively investigate the stability and a variety of physical properties of MXenes with different coordination environments. Using Ti- and Mo-based carbide MXenes as model systems, energetic calculations reveal that Ti-based MXenes are most stable in octahedral coordination, whereas Mo-based MXenes preferentially adopt prismatic coordination. This fundamental difference in preferred atomic coordination gives rise to markedly distinct properties between these two systems as a function of the fraction of octahedral and prismatic sites. For instance, the in-plane stiffness of Ti-based MXenes increases as octahedral coordination becomes dominant, but it decreases in the Mo-based MXenes under the same conditions. Additional stability analyses based on mechanical, lattice-dynamical, and temperature-dependent thermodynamic properties demonstrate that many metastable MXenes not only satisfy the strict stability criteria but can also undergo phase transitions among different structures and even become stabilized at elevated temperatures. Although surface terminations, such as F and O atoms, do not alter the energetic ordering or the overall stiffness trends among stable and metastable MXenes, they influence other material properties. For instance, O termination can induce semiconducting behavior in both stable and metastable Ti 2 ⁢CO 2 MXenes. This study significantly advances the fundamental understanding of structure–property relationships in MXenes and provides valuable guidance for developing coordination-based design principles to precisely engineer MXenes with improved properties.

Oyeniran, Noah [University of Alabama, Tuscaloosa,↗
DOE OSTI2020

Nonlinear dynamics and dissipation of a curvilinear vortex driven by a strong time-dependent Meissner current

Here, we report numerical simulations of large-amplitude oscillations of a trapped vortex line under a strong ac magnetic field $\textit{H(t) = H}$ sin$\textit{ωt}$ parallel to the surface. The power dissipated by an oscillating vortex segment driven by the surface ac Meissner currents was calculated by taking into account the nonlinear vortex line tension, vortex mass, and a nonlinear Larkin-Ovchinnikov (LO) viscous drag coefficient $\textit{η(v)}$. We show that the LO decrease of $\textit{η(v)}$ with the vortex velocity $\textit{v}$ can radically change the field dependence of the surface resistance R i ( H ) caused by trapped vortices. At low frequencies, $R_i(H)$ exhibits a conventional increase with $\textit{H}$, but as $\textit{ω}$ increases, the surface resistance becomes a nonmonotonic function of $\textit{H}$ which decreases with $\textit{H}$ at higher fields. The effects of frequency, pin spacing, and the mean-free path $l_i$ on the field dependence of $R_i(H)$ were calculated. It is shown that, as the surface gets dirtier and $l_i$ decreases, the anomalous drop of $R_i(H)$ with $\textit{H}$ shifts to lower fields which can be much smaller than the lower critical magnetic field. Our numerical simulations also show that the LO decrease of $\textit{η(v)}$ with $\textit{v}$ can cause a vortex bending instability at high field amplitudes and frequencies, giving rise to the formation of dynamic kinks along the vortex. Measurements of $R_i(H)$ caused by sparse vortices trapped perpendicular to the surface can offer opportunities to investigate an extreme nonlinear dynamics of vortices driven by strong current densities up to the depairing limit at low temperatures. The behavior of $R_i(H)$, which can be tuned by varying the rf frequency or concentration of nonmagnetic impurities, is not masked by strong heating effects characteristic of dc or pulse transport measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Shock-compressed silicon: Hugoniot and sound speed up to 2100 GPa

In this work, the high-pressure equation of state and isentropic sound speed of fluid silicon were studied using laser-driven shock waves. Principal Hugoniot measurements to 2100 GPa were performed using impedance matching to an α-quartz reference. Sound speed was determined by time correlating imposed shock-velocity perturbations in both the sample (Si) and reference material (α-quartz). A change in shock velocity versus particle velocity (u s –u p ) slope on the fluid silicon principal Hugoniot was detected at 200 GPa. Density functional theory-based quantum molecular dynamics simulations suggest that an increase in ionic coordination and 50% increase in average ionization is coincident with the experimentally observed change in slope.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Reversible motions and disordered structure of soft particles in amorphous solids

In amorphous solids, soft vibrational modes derived from normal mode analysis can be utilized to identify the soft particles that are prone to irreversible rearrangements. However, the normal mode analysis approach cannot explain why the spatial distributions of clustered soft particles do not change over time. We define a softness parameter based on the vibrational density of states calculated directly from molecular dynamics simulations with both the harmonic vibrations and anharmonic relaxations being properly captured at finite temperatures. This parameter spontaneously correlates with the real space atomic motions and the dynamics heterogeneity. Using the softness parameter, we show that the softest particles are confined within rigid cages. These particles keep rearranging reversibly without long-range diffusion. The moderately soft particles rearrange irreversibly, and the hard particles mainly participate in vibrations without rearrangement. Here, we also show that the soft particles form locally disordered structures, while the hard particles present strong ordering. These findings confirm the defective nature of soft particles, and provide insights on the nature of softness as the ability to rearrange, but not necessarily irreversibly.

36 MATERIALS SCIENCE↗