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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Insights into the Water Transport Mechanism in Polymeric Membranes from Neutron Scattering

Polymeric membranes are ubiquitous in transport applications including gas separation, water desalination, solid-state batteries, and fuel cells. The transport mechanism in certain classes of membranes is well understood. It is generally believed that polymeric membranes used in gas separation follow the solution-diffusion model. However, the transport mechanism in other membranes such as the ones used in water desalination is less clear as both the solution-diffusion and hydrodynamic models have been proposed. In this contribution, we study the structure as well as the water and polymer dynamics of several polymeric membranes using small-angle and quasi-elastic neutron scattering. We demonstrate that on the scale of a few nanometers, water appears to diffuse through a desalination membrane at a rate comparable to bulk water, while water diffuses at a rate that is a factor of 2 slower in an anion-exchange membrane. These results illustrate the importance of studying both the structure and dynamics of membrane materials and have important implications in understanding the transport mechanisms that differentiate the different types of polymeric membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2018

Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks

In many complex networked systems such as online social networks, at any given time, activity originates at certain nodes and subsequently spreads on the network through influence. To model the spread of influence in such a scenario, we consider the problem of identification of influential entities in a complex network when nodal activation can happen through two different mechanisms. The first mode of activation is due mechanisms intrinsic to the node. The second mechanism is through the influence of connected neighbors. In this work, we present a simple probabilistic formulation that models such self-evolving systems where information diffusion occurs primarily because of the intrinsic activity of users and the spread of activity occurs due to influence. We provide an algorithm to mine for the influential seeds in such a scenario by modifying the well-known influence maximization framework with the independent cascade diffusion model. We provide small motivating examples to provide an intuitive understanding of the effect of including the intrinsic activation mechanism. We sketch a proof of the submodularity of the influence function under the new formulation and demonstrate the same with larger graphs. We then show by means of additional experiments on a real-world twitter dataset how the formulation can be applied to real-world social media datasets. Finally we derive a computationally efficient centrality metric that takes into account, both the mechanisms of activation and provides for an accurate as well as computationally efficient alternative approach to the problem of identifying influencers under intrinsic activation.

Visweswara Sathanur, Arun↗
DOE OSTI2021

Improved performance of a near-field thermophotovoltaic device by a back gapped reflector

Various spectral control techniques can be applied to improve the performance of a thermophotovoltaic (TPV) device. For example, a back surface reflector (BSR) is a common structure to improve the performance of TPV devices. A conventional metal BSR structure enhances the photogeneration rate by increasing the absorption probability of photons via back surface reflections, affording a second chance for absorption. However, the effects of surface passivation and external luminescence introduced by BSR structures have been previously ignored, which potentially decreases the performance of TPV devices. Recently, a back gapped reflector (BGR) structure was proposed to greatly improve the performance of far-field TPV devices by reducing imperfect reflections at the semiconductor-metal interface. In the present work, the performance improvement on a thin-film, near-field InAs TPV device with a BGR is investigated, comparing its performance to that with a conventional metal BSR. Surface passivation conditions are also investigated to further improve the performance of TPV devices with back reflectors. Further, the output power and efficiency are calculated using an iterative model combining fluctuational electrodynamics and the full drift diffusion model. For the well-passivated condition, when the BSR is replaced by the BGR, the calculated conversion efficiency of the near-field TPV was improved from 16.4% to 21% and the output power was increased by 10%. Finally, the absorption of the back reflectors and external luminescence loss are analyzed to explain the performance improvement.

external luminescence↗
DOE OSTI2016

Exciton dynamics at a single dislocation in GaN probed by picosecond time-resolved cathodoluminescence

We investigate the dynamics of donor bound excitons (D°X{sub A}) at T = 10 K around an isolated single edge dislocation in homoepitaxial GaN, using a picosecond time-resolved cathodoluminescence (TR-CL) setup with high temporal and spatial resolutions. An ∼ 1.3 meV dipole-like energy shift of D°X{sub A} is observed around the dislocation, induced by the local strain fields. By simultaneously recording the variations of both the exciton lifetime and the CL intensity across the dislocation, we directly assess the dynamics of excitons around the defect. Our observations are well reproduced by a diffusion model. It allows us to deduce an exciton diffusion length of ∼24 nm as well as an effective area of the dislocation with a radius of ∼95 nm, where the recombination can be regarded as entirely non-radiative.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Antimony diffusion in CdTe

Group V dopants may be used for next-generation high-voltage cadmium telluride (CdTe) solar photovoltaics, but fundamental defect energetics and kinetics need to be understood. Here, antimony (Sb) diffusion is studied in single-crystal and polycrystalline CdTe under Cd-rich conditions. Diffusion profiles are determined by dynamic secondary ion mass spectroscopy and analyzed with analytical bulk and grain-boundary diffusion models. Slow bulk and fast grain-boundary diffusion are found. Density functional theory is used to understand formation energy and mechanisms. Lastly, the theory and experimental results create new understanding of group V defect kinetics in CdTe.

14 SOLAR ENERGY↗
NASA NTRS1987

Growth kinetics of the (001) face of TGS below the ferroelectric transition temperature

The growth rates of the (001) face of triglycine sulfate (TGS) from aqueous solutions were measured at 33.55 C in an apparatus which produced a laminar flow of solution past the crystal. The data of growth rate as a function of relative supersaturation were compared with the results of two well-known models: the Burton-Cabrera-Frank (1951) surface diffusion model and the birth-and-spreading growth model. Both models produced good fits to the growth rate data. However, on the basis of the qualitative aspects of the experimentally-observed growth, it is suggested that the correct growth model for these crystals is the Burton-Cabrera-Frank model.

Reiss, D. A.↗
NASA NTRS1992

Thermionic emission current in a single barrier varactor

From I-V measurements on Single Barrier Varactors (SBV) at different temperatures we concluded that thermionic emission across the barrier of the actual device is mainly due to transport through the X band. The same structure was also modeled with a one-dimensional drift-diffusion model, including a 'boundary condition' for thermionic emission across the heterojunction interface. By including thermionic field emission through the top of the triangular barrier of a biased diode and the effect of a non-abrupt interface at the heterojunction, we obtained good agreement between the modeled and measured I-V characteristics.

Hjelmgren, Hans↗
NASA NTRS1994

Using FU Orionis outbursts to constrain self-regulated protostellar disk models

One-dimensional, convective, vertical structure models and one dimensional time-dependent, radial diffusion models are combined to create a self-consistent picture in which FU Orionis outbursts occur in young stellar objects (YSOs) as the result of a large-scale, self-regulated, thermal ionization instability in the surrounding protostellar accretion disk. Although active accretion disks have long been postulated to be ubiqitous among low-mass YSOs, few constraints have until now been imposed on physical conditions in these disks. By fitting the results of time-dependent disk models to observed timescales of FU Orionis events, we estimate the magnitude of the effective viscous stress in the inner disk (r approximately less than 1 AU) to be, in accordance with an ad hoc 'alpha' prescription, the product of the local sound speed, pressure scale height, and an efficiency factor alpha of 10(exp -4) where hydrogen is neutral and 10(exp 3) where hydrogen is ionized. We hypothesize that all YSOs receive infall onto their outer disks which is steady (or slowly declining with time) and that FU Orionis outbursts are self-regulated, disk outbursts which occur only in systems which transport matter inward at a rate sufficiently high to cause hydrogen to be ionized in the inner disk. We estimate a critical mass flux of dm(sub crit)/dt = 5 x 10(exp 7) solar mass/yr independent of the magnitude of alpha for systems with one solar mass, three solar radius central objects. Infall accretion rates in the range of dm(sub in)/dt = 1-10) x 10(exp -6) solar mass/yr produce observed FU Orionis timescales consistent with estimates of spherical molecular cloud core collapse rates. Modeled ionization fronts are typically initiated near the inner edge of the disk and propogate out to a distance of several tens of stellar radii. Beyond this region, the disk transports mass steadily inward at the supplied constant infall rate. Mass flowing through the innermost disk annulus is equal to dm(sub in)/dt only in a time-averaged sense and is regulated by the ionization of hydrogen in the inner disk such that long intervals (approximately 1000 yr) of low-mass flux: (1-30) x 10(exp -8) solar mass/yr are punctuated by short intervals (approximately 100 yr) of high-mass flux: (1-30) x 10(exp -5) solar mass/yr. Timescales and mass fluxes derived for quiescent and outburst stages are consistent with estimates from observations of T Tauri and FU Orionis systems, respectively.

Bell, K. R.↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
NASA NTRS1987

Modeling scalar flux and the energy and dissipation equations

Closure models derived from the Two-Scale Direct-Interaction Approximation were compared with data from direct simulations of turbulence. Attention was restricted to anisotropic scalar diffusion models, models for the energy dissipation equation, and models for energy diffusion.

Yoshizawa, A.↗
NASA NTRS1975

A simple reaction-rate model for turbulent diffusion flames

A simple reaction rate model is proposed for turbulent diffusion flames in which the reaction rate is proportional to the turbulence mixing rate. The reaction rate is also dependent on the mean mass fraction and the mean square fluctuation of mass fraction of each reactant. Calculations are compared with experimental data and are generally successful in predicting the measured quantities.

Bangert, L. H.↗
DOE OSTI2019

Ab initio study of phosphorus effect on vacancy-mediated process in nickel alloys – An insight into Ni 2 Cr ordering

The development of long range order in nickel-chromium alloys is of great technological interest but the kinetics and mechanisms of the transformation are poorly understood. The present research utilizes a combined computational and experimental approach to elucidate the mechanism by which phosphorus accelerates the ordering rate of stoichiometric Ni 2 Cr in Ni-Cr alloys. A series of Ni-33%Cr-x%P samples (in atomic percent) were fabricated with phosphorus concentrations, x = <0.005–0.1 at.% and aged between 373 and 470 °C for times up to 3000 h. The first-principles modeling considers fcc Ni with dilute P as a reasonable approximation for the complex Ni-Cr-P alloy system. Calculation results show a pronounced enhancement of vacancy transport by vacancy-solute pair diffusion via consecutive exchange and rotation jumps of vacancies associated with the phosphorus atom. The energy barriers of these two migration paths are at least 0.35 eV lower than that of vacancy-atom exchange in pure Ni solvent. The analytical diffusion model predicts enhanced solvent diffusion by 2 orders of magnitude for 0.1 at.% P at 400–500 °C. The model prediction is in good agreement with the evolution of micro-hardness. We characterize the micro-hardness result by a kinetic ordering model, showing a significant decrease of the activation energy of ordering transformation. These results help gauge the risk of industrial alloys developing long range order which increases strength but degrades ductility and toughness. Specifically, minor alloying additions that bind with excess vacancies and lower the vacancy migration barrier can greatly accelerate hardening via Ni 2 Cr precipitation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

GrainPaint: A multi-scale diffusion-based generative model for microstructure reconstruction of large-scale objects

Simulation-based approaches to microstructure generation can suffer from a variety of limitations, such as high memory usage, long computational times, and difficulties in generating complex geometries. Generative machine learning models present a way around these issues, but they have previously been limited by the fixed size of their generation area. Here, we present a new microstructure generation methodology leveraging advances in inpainting using denoising diffusion models to overcome this generation area limitation. We show that microstructures generated with the presented methodology are statistically similar to grain structures generated with a kinetic Monte Carlo simulator, SPPARKS.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Measuring the Local Diffusion Coefficient with H.E.S.S. Observations of Very High-Energy Electrons

The HAWC Collaboration has recently reported the detection of bright and spatially extended multi-TeV gamma-ray emission from Geminga, Monogem, and a handful of other nearby, middle-aged pulsars. The angular profile of the emission observed from these pulsars is surprising, in that it implies that cosmic-ray diffusion is significantly inhibited within ~25 pc of these objects, compared to the expectations of standard Galactic diffusion models. This raises the important question of whether the diffusion coefficient in the local interstellar medium is also low, or whether it is instead better fit by the mean Galactic value. Here, we utilize recent observations of the cosmic-ray electron spectrum (extending up to ~20 TeV) by the H.E.S.S. Collaboration to show that the local diffusion coefficient cannot be as low as it is in the regions surrounding Geminga and Monogem. Instead, we conclude that cosmic rays efficiently diffuse through the bulk of the local interstellar medium. Among other implications, this further supports the conclusion that pulsars significantly contribute to the observed positron excess and provides strong evidence for spatially varying diffusion coefficients throughout the Milky Way.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Semi-Analytical Simulation and Optimization of AlGaAs/GaAs p-i-n Quantum Well Solar Cell

This paper deals with a AlGaAs/GaAs p-i-n quantum well solar cell. The doped region are based on AlGaAs semiconductor while the intrinsic region “I” contain multi quantum well (MQW) system AlGaAs/GaAs. A semi-analytical model in the intrinsic region and numerical drift-diffusion model in doped regions are combined to extract the total current density of the cell versus voltage. The current-voltage (J-V) characteristics are generated for the AM1.5 solar spectrum. The effect of the Aluminum molar fraction x (Al{sub x}Ga{sub 1–x}As), the number, the width, the depth of the wells and barriers in the “i” layer and the doping densities on the electrical outputs of the solar cell are also presented. The optimized solar cell reached a conversion efficiency of 28.72% with a short circuit current density of 36.9 mA/cm{sup 2} and an open circuit voltage of 0.97 V.

14 SOLAR ENERGY↗
NASA NTRS1991

Nonequilibrium radiation and chemistry models for aerocapture vehicle flowfields

The primary tasks performed are: (1) the development of a second order local thermodynamic nonequilibrium (LTNE) model for atoms; (2) the continued development of vibrational nonequilibrium models; and (3) the development of a new multicomponent diffusion model. In addition, studies comparing these new models with previous models and results were conducted and reported.

Carlson, Leland A.↗