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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 343 records · Page 19

Diffusion coefficients in the envelopes of white dwarfs

The diffusion of elements is a key process in understanding the unusual surface composition of white dwarfs and their spectral evolution. The diffusion coefficients of Paquette et al. have been widely used to model diffusion in white dwarfs. In this work, we perform new calculations of the coefficients of interdiffusion and ionic thermal diffusion with (1) a more advanced model that uses a recent modification of the calculation of the collision integrals that is more suitable for the partially ionized, partially degenerate, and moderately coupled plasma and (2) classical molecular dynamics. The coefficients are evaluated for silicon and calcium in white dwarf envelopes of hydrogen and helium. A comparison of our results with Paquette et al. shows that the latter systematically underestimates the coefficient of interdiffusion yet provides reliable estimates for the relatively weakly coupled plasmas found in nearly all types of stars, as well as in white dwarfs with hydrogen envelopes. In white dwarfs with cool helium envelopes (${T}_{\mathrm{eff}}$ < 15,000 K), the difference grows to more than a factor of two. We also explored the effect of the ionization model used to determine the charges of the ions and found that it can be a substantial source of discrepancy between different calculations. Finally, we consider the relative diffusion timescales of Si and Ca in the context of the pollution of white dwarf photospheres by accreted planetesimals and find factor of ≳3 differences between calculations based on Paquette et al. and our model.

79 ASTRONOMY AND ASTROPHYSICS↗

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

Investigation of Molecular Diffusion at Block Copolymer Thin Films Using Maximum Entropy Method-Based Fluorescence Correlation Spectroscopy and Single Molecule Tracking

Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated nitrogen atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. Furthermore, these results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photoinduced structural recovery dynamics of rare-earth nickelate thin films

Photoinduced structural dynamics of rare-earth nickelate thin films, NdNiO 3 and SmNiO 3 , grown on (001) oriented SrTiO 3 were studied using time-resolved x-ray diffraction. The evolution of the (002) Bragg peak was tracked following laser excitation. The recovery pathways were found to be strongly dependent on laser fluence for NdNiO 3 and distinct for the two rare-earth nickelates. The recovery of the (002) peak shifts was modeled using a one-dimensional thermal diffusion model which showed that the recovery processes are non-thermal at high fluences. For NdNiO 3 , the timescales for the recovery of the (002) peak shift were found to be closely related to Ni magnetism recovery, potentially indicating magneto-structural coupling. Moreover, the evolution of integrated intensity and full-width-half-maximum points towards the presence of a structural phase separation during recovery. In conclusion, our studies highlight structural recovery pathways in nickelates by comparing the distinct responses of the photoinduced metal-insulator transition in NdNiO 3 and SmNiO 3 .

36 MATERIALS SCIENCE↗

Growth of HgZnTe alloy crystals by directional solidification

A series of Hg(1-x)Zn(x)Te crystals were grown by directional solidification with x ranging from 0.15 to 0.22. The axial and radial compositional variations were determined by precision density measurements, infrared (IR) transmission spectra, and energy dispersive X-ray spectroscopy (EDX). Comparison between the axial compositional profiles and the calculated results of a one-dimensional diffusion model gives a value for the effective diffusion coefficient in the HgZnTe melt of 2 to 4 x 10 to the -6th sq cm/s.

Su, Ching-Hua↗

Evaluation of the Emergency Response Dose Assessment System(ERDAS)

The emergency response dose assessment system (ERDAS) is a protype software and hardware system configured to produce routine mesoscale meteorological forecasts and enhanced dispersion estimates on an operational basis for the Kennedy Space Center (KSC)/Cape Canaveral Air Station (CCAS) region. ERDAS provides emergency response guidance to operations at KSC/CCAS in the case of an accidental hazardous material release or an aborted vehicle launch. This report describes the evaluation of ERDAS including: evaluation of sea breeze predictions, comparison of launch plume location and concentration predictions, case study of a toxic release, evaluation of model sensitivity to varying input parameters, evaluation of the user interface, assessment of ERDA's operational capabilities, and a comparison of ERDAS models to the ocean breeze dry gultch diffusion model.

Evans, Randolph J.↗

A novel directly coupled gradostat

The original bidirectional compound chemostat (gradostat) described by Lovitt and Wimpenny has been simplified by making a more compact apparatus in which chemical gradients are established by diffusion between adjacent culture chambers. The experimental model (diffusion coupled (DC) gradostat) consisted of five chambers whose contents could be agitated by turbines rotating in the horizontal plane on a common shaft. Two biological experiments were designed to reveal the value of the DC gradostat. A methylotroph (Methylophilus methylotrophus) grown in a methanol gradient showed expected changes in cell viability as a function of position in the five vessel array. Cells of two species of photosynthetic bacteria (Rhodobacter capsulata and Rhodopseudomonas marina/agilis) with different salt sensitivities could be mixed and subsequently separated by the DC gradostat operating with a NaCl gradient of 0-3% w/v.

NASA Discipline Exobiology↗

A turbulent transport model for free-shear flows

An attempt is made to formulate a more accurate and physically plausible diffusion model, which will include the effects of large eddy motion on turbulent transport, by incorporating bulk convection and gradient diffusion. The two-equation model of turbulence thus obtained is used in self-similar form to calculate axisymmetric and plane two-dimensional jets.

Biringen, S.↗

Quartz-hosted inclusions and embayments reveal storage, fluxing, and ascent of the Mesa Falls Tuff, Yellowstone

Quartz-hosted glasses from the Mesa Falls Tuff provide a geochemical window into the pre-eruptive magmatic system from one of Yellowstone's largest-volume caldera-forming eruptions. H 2 O and CO 2 concentrations, along with major and trace elements, were measured in both fully enclosed glass inclusions and partially enclosed embayments in the same quartz crystals. Major elements are largely consistent between the inclusions and embayments, except for K 2 O and Na 2 O. Of note, K 2 O is enriched by ~1 wt.% in embayment interiors relative to inclusions. Most trace elements are also enriched in the embayment interiors compared to inclusions from the same crystals. Fractionation trends of trace elements are consistent with ~30-60% crystallization. Quartz-hosted glass inclusions preserve 3.1±0.9 wt.% H 2 O and 493±227 ppm CO 2 whereas embayment interiors have 0.9±0.1 wt.% H 2 O and 399±229 ppm CO 2 . The CO 2 is roughly similar, but the distinct ~2 wt.% discrepancy between inclusion and embayment interior H 2 O contents may have been produced by CO 2 fluxing sourced from underplated Yellowstone basalts. H 2 O gradients within embayments are flat in their interiors and modified by sharp positive gradients near embayment exteriors which were produced by post-eruptive rehydration. CO 2 gradients occur as gently sloping concentration gradients that extend inward 150 to 250 μm from the embayment exterior. Finally, finite-difference 1D and 2D diffusion modeling indicates the distribution of H 2 O and CO 2 in embayments was produced by slow, fluid-saturated decompression that preceded rapid ascent during the caldera-forming eruption.

2D diffusion modeling↗

Thermal diffusion, exhaust gas recirculation and blending effects on lean premixed hydrogen flames

Thermodiffusively-unstable lean premixed hydrogen flames are investigated using two-dimensional direct numerical simulation employing finite-rate chemical kinetics. Three databases are generated focussing on the inclusion of the Soret effect, the recirculation of exhaust gas, and blending with methane. A simple rescaling of a classic thermal diffusion model is presented and shown to mimic multicomponent diffusion with very low computational cost and little-to-no loss in accuracy. It is also shown that a previously developed model for mean local flame speeds in lean premixed hydrogen flames can still be used provided Soret effects are taken into account in one-dimensional calculations. The addition of exhaust gas to the unburned mixture is found to enhance thermodiffusive instability; the primary mechanism for this was shown to be the highly-efficient third-body nature of water, with the reduction of adiabatic flame temperature a second-order effect. Again, the existing mean local flame speed model proved sufficient. Finally, blending with methane was found to reduce the thermodiffusive response of the flame, more so than the existing model suggests, despite adjustment of the fuel Lewis number; an adapted model is presented to account for this.

08 HYDROGEN↗

Effects of Material Degradation on the Structural Integrity of Composite Materials: Experimental Investigation and Modeling of High Temperature Degradation Mechanisms

It has previously been demonstrated that simple coupled reaction-diffusion models can approximate the aging behavior of PMR-15 resin subjected to different oxidative environments. Based on empirically observed phenomena, a model coupling chemical reactions, both thermal and oxidative, with diffusion of oxygen into the material bulk should allow simulation of the aging process. Through preliminary modeling techniques such as this it has become apparent that accurate analytical models cannot be created until the phenomena which cause the aging of these materials are quantified. An experimental program is currently underway to quantify all of the reaction/diffusion related mechanisms involved. The following contains a summary of the experimental data which has been collected through thermogravimetric analyses of neat PMR-15 resin, along with analytical predictions from models based on the empirical data. Thermogravimetric analyses were carried out in a number of different environments - nitrogen, air and oxygen. The nitrogen provides data for the purely thermal degradation mechanisms while those in air provide data for the coupled oxidative-thermal process. The intent here is to effectively subtract the nitrogen atmosphere data (assumed to represent only thermal reactions) from the air and oxygen atmosphere data to back-figure the purely oxidative reactions. Once purely oxidative (concentration dependent) reactions have been quantified it should then be possible to quantify the diffusion of oxygen into the material bulk.

Cunningham, Ronan A.↗

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↗

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↗

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↗

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.↗

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↗

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.↗

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↗