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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 325 records · Page 18

Performance of Diffusion Monte Carlo Calculations for Predicting the Relative Energies of Quinoidal and Nonquinoidal Species

Coupled cluster singles and doubles with perturbative triples [CCSD(T)] and single determinant fixed-node diffusion Monte Carlo (SD-DMC) have emerged as two of the most useful methods for providing benchmark reaction and interaction energies of chemical systems without strong static correlation. The errors in DMC energies are dominated by an inexact description of the nodal surfaces for electron exchange. One of the main approaches to addressing the fixed-node error is to use multideterminant (MD) trial wave functions. We consider here the energy differences between pairs of related molecules with aromatic and quinoidal structures as well as between quinoidal isomers. Quinoidal systems tend to have some diradical character, leading one to anticipate that SD-DMC calculations may face challenges in accurately describing their energetics. The MD trial wave functions were generated from the complete active space calculations. A comparison is made with the predictions of well-converged CCSD(T) calculations.

basis sets↗

Domain-Dependent Electronic Properties of 2D Copper Boride Synthesized from Reversible Subsurface Diffusion on Cu(111)

Emerging boron-based 2D materials hold properties with potential applications ranging from electronic devices to catalysis and energy storage. Using physical vapor deposition, 2D copper borides are formed on Cu(111) at elevated temperatures. However, the as-prepared surfaces often contain boron clusters that compromise structural homogeneity, and the dynamics of their formation is not yet fully understood. Through in situ low-energy electron microscopy (LEEM), Auger electron spectroscopy (AES), and scanning tunneling microscopy/spectroscopy (STM/STS), we show that cluster-free 2D CuB x is synthesized via reversible subsurface diffusion of boron atoms. The resolved regular atomic structure aligns with the previously calculated Cu 8 B 14 model. In a rare case, possibly due to surface strain and a change of orientation, a second domain of CuB x was observed with a pronounced change in electronic properties, yet electronic states remain delocalized in both domains. In conclusion, these findings demonstrate the sensitivity of electronic properties to domain structure and highlight a potential opportunity to tune 2D CuB x for diverse applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Reducing Thermal Degradation of Perovskite Solar Cells during Vacuum Lamination by Internal Diffusion Barriers

Current photovoltaic (PV) panels typically contain interconnected solar cells that are vacuum laminated with a polymer encapsulant between two pieces of glass or glass with a polymer backsheet. This packaging approach is ubiquitous in conventional photovoltaic technologies such as silicon and thinfilm solar modules, contributing to thermal management, mechanical reinforcement, and environmental protection to enable the long lifetimes necessary to become financially acceptable. Commercial vacuum lamination processes typically occur at 150 °C to ensure cross-linking and/or glass bonding of the encapsulant to the glass and PV cells. Perovskite solar cells (PSCs) have emerged as a promising next-generation PV technology that is known to degrade under thermal stresses, especially at temperatures above 100 °C. In this study, we determine degradation modes during lamination and engineer internal diffusion barriers within the PSC to withstand the harsh thermal conditions of vacuum lamination. PSCs with self-assembled monolayers at the ITO interface and SnO X layers deposited by atomic layer deposition at the electron extraction side of the device endured vacuum lamination at conditions typical of commercial PV processes (150 °C) without degradation. This work demonstrates that perovskite PV can be integrated into the existing module lamination process, enabling future single- and multijunction modules utilizing perovskite absorbers.

14 SOLAR ENERGY↗

A Mechanism-Based Reaction–Diffusion Model for Accelerated Discovery of Thermoset Resins Frontally Polymerized by Olefin Metathesis

Frontal ring-opening metathesis polymerization (FROMP) involves a self-perpetuating exothermic reaction, which enables the rapid and energy-efficient manufacturing of thermoset polymers and composites. Current state-of-the-art reaction–diffusion FROMP models rely on a phenomenological description of the olefin metathesis kinetics, limiting their ability to model the governing thermo-chemical FROMP processes. Furthermore, the existing models are unable to predict the variations in FROMP kinetics with changes in the resin composition and as a result are of limited utility toward accelerated discovery of new resin formulations. In this work, we formulate a chemically meaningful model grounded in the established mechanism of ring-opening metathesis polymerization (ROMP). Our study aims to validate the hypothesis that the ROMP mechanism, applicable to monomer-initiator solutions below 100 °C, remains valid under the nonideal conditions encountered in FROMP, including ambient to >200 °C temperatures, sharp temperature gradients, and neat monomer environments. Through extensive simulations, we demonstrate that our mechanism-based model accurately predicts the FROMP behavior across various resin compositions, including polymerization front velocities and thermal characteristics (e.g., T max ). Additionally, we introduce a semi-inverse workflow that predicts FROMP behavior from a single experimental data point. Notably, the physiochemical parameters utilized in our model can be obtained through DFT calculations and minimal experiments, highlighting the model’s potential for rapid screening of new FROMP chemistries in pursuit of thermoset polymers with superior thermo-chemo-mechanical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

54 ENVIRONMENTAL SCIENCES↗

Properties of Lower Hybrid Drift Waves and Energy Transfer Near and Inside the Magnetic Reconnection Electron Diffusion Regions

Here, we investigate properties of lower hybrid drift waves (LHDWs) near and inside the electron diffusion regions in 17 magnetopause and 9 magnetotail reconnection events using Magnetospheric MultiScale (MMS) mission observations. Our analysis show that LHDW type depend on the electron beta, as electron beta increases LHDWs become more electromagnetic in nature. The energy transfer from electromagnetic fields to particles is higher in electrostatic LHDWs and it is largely in parallel direction with respect to the local magnetic field. Linear dispersion analysis shows that electrostatic LHDWs are perpendicular propagating while electromagnetic waves propagate in oblique directions and the normalized wavenumber of all LHDW types falls within 0.5–0.8 range. A simple estimate on the LHDW nonlinear saturation suggests a possibly important roles played by these waves in supporting the reconnection electric field.

79 ASTRONOMY AND ASTROPHYSICS↗

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗

Probing the proton exchange kinetics of BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3− δ ceramic electrolyte by operando diffuse reflectance infrared Fourier transform spectroscopy

Proton exchange kinetics plays an important role in governing the performance of intermediate-temperature protonic ceramic electrolysis cells (PCECs) for hydrogen production. Our understanding of the nature of the surface hydration reaction at the single-cell level, however, remains very limited, hampering further efficiency improvements. Here, in this study, we developed a custom operando diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) platform that operates under high temperature and steam conditions with applied bias. Quantitative investigations of surface H 2 O/D 2 O isotope exchange in a BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3−δ (BZCYYb1711) protonic electrolyte-based single cell were conducted under different applied voltages using this DRIFTS platform, to gain molecular-level insight into hydration kinetics. The findings show that the application of an external voltage significantly enhances the surface proton exchange rate, decreasing the apparent activation energy from 29.1 kJ mol −1 at open-circuit voltage (OCV) to 6.8 kJ mol −1 at 1.3 V. In addition, distinct voltage-induced spectral shifts in O–D vibrations point to dynamic changes in surface hydration. These findings demonstrate a sensitive spectroscopic platform for probing interfacial proton processes and reveal strong electrochemical control over surface proton kinetics, offering new opportunities for probing electrolyte hydration behavior in PCECs.

36 - MATERIALS SCIENCE↗

Construction of generalized quasilinear diffusion coefficient using neural networks with physical restrictions

The quasilinear diffusion coefficient (D QL ) derived from our machine learning framework shows comparable trends with the ground truth D QL obtained from GENRAY-CQL3D simulations. Additionally, for the strong absorption cases, the radial current drive profiles generated using the D QL from our model exhibit consistent behavior with those obtained from the original simulation. These findings indicate the potential of our surrogate modeling approach with physical restrictions to replicate key wave–plasma interaction characteristics while reducing computational costs. Traditionally, calculating D QL for wave–particle interactions relies on computationally intensive wave simulations coupled with Fokker–Planck solvers. To address this challenge, we developed a machine learning-based surrogate model with physical restrictions derived from cold plasma theory and bounce-averaged damping effects. First, we establish the propagation domain of Lower Hybrid Waves in the (N∥, ρ) space by identifying the accessibility limit and determining the upper and lower bounds of N∥ using the Potential Power Deposition (PPD) method. Subsequently, leveraging a database constructed using Latin hypercube sampling alongside the underlying physical restrictions (e.g. PPD), machine learning methods including U-Net and Recurrent Neural Networks are employed to design a physics-restricted machine learning framework capable of reconstructing D QL .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Interactions of clathrate hydrate promoters sodium dodecyl sulfate and tetrahydrofuran investigated using 1H diffusion nuclear magnetic resonance at hydrate-forming conditions

Thermodynamic hydrate promoters and kinetic hydrate promoters can be used to reduce the P–T conditions for clathrate hydrate synthesis to decrease the nucleation induction time while increasing growth rates. Two commonly used promoters for hydrate research are tetrahydrofuran (THF) and sodium dodecyl sulfate (SDS), which can increase the overall hydrate promotion when used in tandem as compared to individually. There are several molecular theories regarding how SDS promotes hydrate growth. This study explores the micellular theory, for which hydrate formation depends on surfactant aggregates (micelles) at a critical micelle concentration (CMC) to increase the interfacial surface area. The micellular theory is the most investigated and criticized surfactant hydrate promotion theory. To address questions related to micellar behavior, this study investigates the intermolecular behavior between SDS and THF for the identification of micelles at hydrate-forming conditions. The systems explored contained THF at 3 and 5 wt. % with varying concentrations of SDS below and above the CMC. Several methods including a qualitative visual method, conductivity, interfacial tensiometry, 13C Liquid-state Nuclear Magnetic Resonance (NMR) spectroscopy, and 1H diffusion NMR spectroscopy were evaluated at temperatures below the Krafft point of SDS and above 0 °C. The presence of THF at low concentrations decreased the critical temperature for the formation of SDS micelles, where SDS is solubilized in THF/water solution at hydrate-forming temperatures without precipitation. The CMC of SDS was decreased significantly even at hydrate-forming conditions. Mixed surfactant–cosolvent micellular behavior of SDS in the presence of low concentrations of THF was confirmed at hydrate-forming conditions above 0 °C.

Chemistry↗

Impact of metal diffusion, lattice distortions, native defects, and ambient on dielectric breakdown in Ni–Ga 2 O 3 Schottky diodes

Ga 2 O 3 unipolar devices are of high interest due to their ~8 MV/cm predicted breakdown fields, which have not yet been achieved due to premature device failure. Pre- and post-failure defect analysis of Ni–Ga 2 O 3 Schottky diodes in ultrahigh vacuum (UHV) and air were performed using depth-resolved cathodoluminescence, high angle annular dark field scanning transmission electron microscopy, and energy dispersive x-ray analysis to understand the physical mechanisms that precede premature breakdown. The breakdown voltage in UHV was dramatically reduced by nearly 40% compared with the breakdown in air. This reduction in the breakdown voltage correlated with post-breakdown differences in Ni distribution, indicating that the coordination and bonding of Ni contribute strongly to electrical behavior in Ni–Ga 2 O 3 Schottky diodes. Breakdown studies in UHV revealed that Ni diffuses away more from the metal–semiconductor interface than with air breakdown, where Ni localizes more near the interface, indicative of the preferential formation of a Ni oxide under O-poor conditions. These measurements also identified the formation of divacancy-interstitial complexes and their characteristic luminescence signature ~150 nm from the interface, the densities of which correlated with breakdown fields. These findings show that electric-field-induced degradation occurs via the rearrangement of native point defects, which act as an additional precursor to device failure. Macroscopically, they show the impact of both vacuum conditions and metal reactivity on Ga 2 O 3 device fabrication.

36 MATERIALS SCIENCE↗

Universality in diffusion-controlled nucleation and growth

Nucleation and growth are studied in a system that undergoes diffusion-controlled condensation under gradual changes in parameters, such as cooling. Here, it is demonstrated that when the Gibbs–Thompson effect becomes negligible, the system falls into a universal regime. i.e., the final droplet size distribution remains invariant under certain rescaling of system parameters. An approximate yet very accurate analytic form is obtained for the final droplet size distribution in this regime.

36 MATERIALS SCIENCE↗

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer

Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and molecular properties. Furthermore, its excellent scalability with system complexity and near-perfect utilization of computational power make FN-DMC ideally positioned to leverage new advances in computing to address increasingly complex scientific problems. Even though the method is widely used as a computational gold standard, reproducibility across the numerous FN-DMC code implementations has yet to be demonstrated. This difficulty stems from the diverse array of DMC algorithms and trial wave functions, compounded by the method’s inherent stochastic nature. Here, this study represents a community-wide effort to assess the reproducibility of the method, affirming that yes, FN-DMC is reproducible (when handled with care). Using the water–methane dimer as the canonical test case, we compare results from eleven different FN-DMC codes and show that the approximations to treat the non-locality of pseudopotentials are the primary source of the discrepancies between them. In particular, we demonstrate that, for the same choice of determinantal component in the trial wave function, reliable and reproducible predictions can be achieved by employing the T-move, the determinant locality approximation, or the determinant T-move schemes, while the older locality approximation leads to considerable variability in results. These findings demonstrate that, with appropriate choices of algorithmic details, fixed-node DMC is reproducible across diverse community codes—highlighting the maturity and robustness of the method as a tool for open and reliable computational science.

Della Pia, Flaviano [Univ. of Cambridge (United Ki↗

X-ray thermal diffuse scattering as a texture-robust temperature diagnostic for dynamically compressed solids

We present a model of x-ray thermal diffuse scattering (TDS) from a cubic polycrystal with an arbitrary crystallographic texture, based on the classic approach of Warren [B. E. Warren, Acta Crystallogr. 6, 803 (1953)]. We compare the predictions of our model with femtosecond x-ray diffraction patterns gathered from ambient and dynamically compressed rolled copper foils obtained at the High Energy Density instrument of the European X-Ray Free-Electron Laser facility and find that the texture-aware TDS model yields more accurate results than does the conventional powder model owed to Warren. Nevertheless, we further show: with sufficient angular detector coverage, the TDS signal is largely unchanged by sample orientation and in all cases strongly resembles the signal from a perfectly random powder; shot-to-shot fluctuations in the TDS signal resulting from grain-sampling statistics are at the percent level, in stark contrast to the fluctuations in the Bragg-peak intensities (which are over an order of magnitude greater); and TDS is largely unchanged even following texture evolution caused by compression-induced plastic deformation. We conclude that TDS is robust against texture variation, making it a flexible temperature diagnostic applicable just as well to off-the-shelf commercial foils as to ideal powders.

Crystal lattices↗