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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 OSTI2022

Efficiency and Forward Voltage of Blue and Green Lateral LEDs with V-shaped Defects and Random Alloy Fluctuation in Quantum Wells

For nitride-based blue and green light-emitting diodes (LEDs), the forward voltage V for is larger than expected, especially for green LEDs. This is mainly due to the large barriers to vertical carrier transport caused by the total polarization discontinuity at multiple quantum well and quantum barrier interfaces. The natural random alloy fluctuation in quantum wells has proven to be an important factor reducing V for . However, this does not suffice in the case of green LEDs because of their larger polarization-induced barrier. V-shaped defects (V-defects) have been proposed as another key factor in reducing V for to allow lateral injection into multiple quantum wells, thus bypassing the multiple energy barriers incurred by vertical transport. In this paper, to model carrier transport in the whole LED, we consider both random-alloy and V-defect effects. A fully two-dimensional drift-diffusion charge-control solver is used to model both effects. The results indicate that the turn-on voltages for blue and green LEDs are both affected by random alloy fluctuations and the V-defect density. For green LEDs, V for decreases more due to V-defects, where the smaller polarization barrier at the V-defect sidewall is the major path for lateral carrier injection. Then, we discuss how the V-defect density and size affects the results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Polyethylene Blends for Improved Oxygen Barrier: Processing-Dependent Microstructure and Gas Permeability

Here this work demonstrates a greater than expected enhancement of oxygen barrier properties in linear low-density polyethylene (LLDPE)-based materials by blending LLDPE with high-density polyethylene (HDPE). The films made by melt pressing the LLDPE/HDPE blends had a greater reduction in oxygen permeability coefficients (PO 2 ) than predicted using common permeability reduction models, i.e., the harmonic average model and zero-permeability nanofiller model. The reduction of PO 2 was attributed to the presence of spherulite crystal structures, as revealed by atomic force microscopy combined with infrared spectroscopy (AFM-IR). The LLDPE matrix exhibited significant spherulite formation even at a relatively low addition of HDPEs, which likely formed tortuous pathways for diffusing oxygen molecules. Transport results from melt-pressed films contrast with the results from films with similar compositions prepared by film blowing, which did not show barrier enhancement beyond expectation. AFM-IR revealed that the blown films lacked spherulite crystals likely due to stretching in the machine direction followed by rapid cooling. These findings demonstrate the role of processing in controlling microstructures and thus the oxygen barrier performance. This work offers the possibility of achieving easily recyclable LLDPE-based packaging materials by simple blending of polyethylenes with different crystalline content.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Stabilization of Miscible Aqueous Phases via Diffusion‐Controlled Multifunctional Nanoparticle‐Ligand Complexation

Liquid‐in‐liquid structuring by harnessing miscible aqueous domains can be achieved by inducing thermodynamically defined phase separation using aqueous solutions of incompatible solutes, where immiscibility is dictated by the concentrations of the solutes. For instance, in aqueous two‐phase systems (ATPSs), the interfacial tension between the two different aqueous solutions is so small that it stabilizes the phase‐separated domains, but not their shape, thus falling short of designing tunable, robust structures. Here, we introduce a diffusion‐controlled strategy that enables liquid‐in‐liquid compartmentalization absent a thermodynamically defined interface or bulk liquid‐liquid phase separation using a barrier formed in situ at the initial contact boundary of an aqueous dispersion of multifunctional nanoparticles and a solution of multifunctional ligands in pure water or a water/alcohol mixture. The nanoparticles and ligands are entropically driven to disperse uniformly but interact at the initial contact boundary more rapidly than bulk mixing, forming a layer that establishes a barrier akin to a semi‐permeable membrane and allows the formation of tubular compartments. A wealth of opportunities is enabled by the proposed technique, where examples in separations, soft electronic devices, and ultralight porous electromagnetic shielding materials are shown.

cryogels↗
DOE OSTI2020

Connecting energetics to dynamics in particle growth by oriented attachment using real-time observations

The interplay between crystal and solvent structure, interparticle forces and ensemble particle response dynamics governs the process of crystallization by oriented attachment (OA), yet a quantitative understanding is lacking. Using as a model system ZnO, we combine in situ TEM observations of single particle and ensemble assembly dynamics with simulations of interparticle forces and responses to relate experimentally derived interparticle potentials to the underlying interactions. We show that OA is driven by forces and torques due to a combination of electrostatic ion-solvent correlations and dipolar interactions that act at separations well beyond 5 nm. Importantly, coalignment is achieved before particles reach separations at which strong attractions drive the final jump to contact. The observed barrier to attachment is negligible, while dissipative factors in the quasi-2D confinement of the TEM fluid cell lead to abnormal diffusivities with timescales for rotation much less than for translation, thus enabling OA to dominate.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Elucidation of the physical factors that control activated transport of penetrants in chemically complex glass-forming liquids

Understanding the activated transport of penetrant or tracer atoms and molecules in condensed phases is a challenging problem in chemistry, materials science, physics, and biophysics. Many angstrom- and nanometer-scale features enter due to the highly variable shape, size, interaction, and conformational flexibility of the penetrant and matrix species, leading to a dramatic diversity of penetrant dynamics. Based on a minimalist model of a spherical penetrant in equilibrated dense matrices of hard spheres, a recent microscopic theory that relates hopping transport to local structure has predicted a novel correlation between penetrant diffusivity and the matrix thermodynamic dimensionless compressibility, S 0 ( T ) (which also quantifies the amplitude of long wavelength density fluctuations), as a consequence of a fundamental statistical mechanical relationship between structure and thermodynamics. Moreover, the penetrant activation barrier is predicted to have a factorized/multiplicative form, scaling as the product of an inverse power law of S 0 ( T ) and a linear/logarithmic function of the penetrant-to-matrix size ratio. This implies an enormous reduction in chemical complexity that is verified based solely on experimental data for diverse classes of chemically complex penetrants dissolved in molecular and polymeric liquids over a wide range of temperatures down to the kinetic glass transition. The predicted corollary that the penetrant diffusion constant decreases exponentially with inverse temperature raised to an exponent determined solely by how S 0 ( T ) decreases with cooling is also verified experimentally. Our findings are relevant to fundamental questions in glassy dynamics, self-averaging of angstrom-scale chemical features, and applications such as membrane separations, barrier coatings, drug delivery, and self-healing.

Science & Technology - Other Topics↗
DOE OSTI2022

Microsized Pore Structure Determination in EPDM Rubbers Using High-Pressure 129 Xe NMR Techniques

Microsized pore parameters, such as pore size and distance between pores in a series of model EPDM rubbers, were determined in situ under the pressure of 500 psi using 129 Xe nuclear magnetic resonance (NMR) techniques: spin–lattice (T 1 ) and spin–spin (T 2 ) relaxation measurements, pulsed-field gradient (PFG) NMR, and two-dimensional exchange spectroscopy (2D EXSY). The T 1 /T 2 (>>1) ratio for the xenon confined in the pores is larger than that for nonconfined free xenon. This suggests that almost the entire pore surface interacts with xenon atoms like a closed pore. While these pores still connect each other through very narrow diffusion/exchange channels, it is possible to observe the echo decay in PFG-NMR and cross-peaks in 2D EXSY. The results show that both diffusion (D pore ≈ 2.1 × 10 –10 m 2 /s) and exchange (exchange rate, τ exch = a few tens of milliseconds) of xenon between a pore within the material and outer surface are prolonged. The exchange distances (l), which correspond to the xenon gas penetration depth, were estimated to be 70–100 μm based on the measured diffusion coefficients and exchange rate (1/τ exch ). NMR diffraction analysis reveals that pore size (a) and pore distance (b) are on the order of magnitude of micrometers and tens of micrometers, while the diffusion coefficients of xenon gas in the diffusion channels (D eff ) are about 10 –8 m 2 /s. Overall, this study suggests that the pores with a few micrometers connected through very narrow flowing channels with the length of several tens of micrometers are developed 70 to 100 μm below the rubber surface. Furthermore, the overall steady-state diffusion of xenon is slower, approximately 2 orders of magnitudes, than the diffusion in the channel between the pores. Finally, the pore and exchange distances correlated with the composition of rubbers showed that the properties of EPDM rubber as a high-pressure gas barrier could be improved by reducing the size of cracks and the depth of gas penetration by the addition of both carbon black and silica fillers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Corrosion protection of steel pipelines with metal-polymer composite barrier liners

Pipelines are efficient in transporting natural gas over large distances. Wet carbon dioxide present in pipelines can create an environment that is corrosive to steel. Polymer liners made from either polyethylene or polyamide (nylon) are presently used to mitigate internal corrosion in natural gas pipelines. Gas diffuses through all polymers over time, and polymer-only liners lower the steel corrosion rate by reducing the reactive gas flux to the internal surface of a pipeline. Composite liners, which incorporate one or more metallic layers that are impermeable to corrosive gases, offer better protection than polymer-only liners. In this study, we measured the methane, water vapor, and carbon dioxide permeability of a multi-layer barrier film and found it to be more effective in resisting gas permeation than polyethylene and nylon-11 films.

03 NATURAL GAS↗
DOE OSTI2025

Ab-initio informed cluster dynamics simulation of self- and Xe diffusivity in uranium mononitride under irradiation

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuels considered for light water reactor and advanced reactor designs, as it presents significant advantages such as high uranium density (better economics) and high thermal conductivity and melting point (increased safety). Self- and fission gas diffusivities need to be better understood, given that they influence key fuel performance phenomena like swelling and fission gas release. Recently, radiation enhanced diffusivity was investigated in UN by means of cluster dynamics simulations relying on empirical potential-based parameterizations, the reliability of which highly depends on the interatomic potential accuracy. Here, in this work, we refine this approach by determining, using ab-initio calculations, the properties of defect clusters containing vacancies, self-interstitials and Xe impurities. We also consider larger clusters than previous studies. The obtained dataset (formation enthalpies, entropies, and migration barriers) is used to parameterize a cluster dynamics model of mobile clusters, and to calculate the defect cluster concentrations under irradiation. This gives us access to the radiation enhanced self- and fission gas diffusivities. Although the resulting diffusivities are close to the values reported in the literature, we find important qualitative differences in the diffusion mechanisms. Capturing the correct mechanisms is crucial to properly describe the chemistry and fission rate dependence of the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Overcoming Barriers Associated with Oral Delivery of Differently Sized Fluorescent Core‐Shell Silica Nanoparticles

Oral delivery, while a highly desirable form of nanoparticle-drug administration, is limited by challenges associated with overcoming several biological barriers. Here, in this study, the authors study how fluorescent and poly(ethylene glycol)-coated (PEGylated) core-shell silica nanoparticles sized 5 to 50 nm interact with major barriers including intestinal mucus, intestinal epithelium, and stomach acid. From imaging fluorescence correlation spectroscopy studies using quasi-total internal reflection fluorescence microscopy, diffusion of nanoparticles through highly scattering mucus is progressively hindered above a critical hydrodynamic size around 20 nm. By studying Caco-2 cell monolayers mimicking the intestinal epithelia, it is observed that ultrasmall nanoparticles below 10 nm diameter (Cornell prime dots, [C’ dots]) show permeabilities correlated with high absorption in humans from primarily enhanced passive passage through tight junctions. Particles above 20 nm diameter exclusively show active transport through cells. After establishing C’ dot stability in artificial gastric juice, in vivo oral gavage experiments in mice demonstrate successful passage through the body followed by renal clearance without protein corona formation. Results suggest C’ dots as viable candidates for oral administration to patients with a proven pathway towards clinical translation and may generate renewed interest in examining silica as a food additive and its effects on nutrition and health.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The impact of chemistry on anion migration in bixbyite-structured lanthanide oxides

This manuscript describes atomistic calculations of oxygen vacancy and interstitial migration in bixbyite structured lanthanide oxides. We examine two types of compounds, one in which only one type of lanthanide cation is present and a second class in which two lanthanides are present in a 3:1 ratio as dictated by the symmetry of the bixbyite crystal structure. Using temperature accelerated dynamics and the nudged elastic band method, we quantify the role of chemistry on the energy barriers for the most important pathways for both vacancy and interstitial migration. We then analyze the impact of these variations on the overall diffusivity of each defect, quantifying the contribution of each pathway using the theory of kinosons. We find that vacancy mobility can vary by as much as three orders of magnitude through changes in chemistry at 500 K. Changes in interstitial mobility are more modest but can still vary by an order of magnitude. This points to the ability to tune the mass transport characteristics of these compounds through appropriate choices in chemistry. We have also included supplementary information containing the atomic structures of the relevant pathways.

36 MATERIALS SCIENCE↗
DOE OSTI2020

First-principles study of hydrogen behavior near W/WC interfaces

Hydrogen (H) solution, migration, and binding to vacancies near the tungsten/tungsten carbide (W/WC) interfaces based on hcp WC or bcc W (W/WCb and Wb/WC) have been studied by first-principles simulations to provide insights into the effect of C on H behavior in W exposed to C deposition in fusion reactors. The H behavior near the W/WC interfaces is related to the tensile or compressive strain due to the lattice match and interfacial effects. Near the W/WCb interface, the H solution energy in hcp WC increases approaching the interface, while it decreases from the W side to the interface. The configuration change of the W slab significantly decreases the H solution energy but has only a modest effect on the H migration energy barrier in comparison with the values in bcc W. The interface enhances the H binding to vacancies in WC layers. Both the interface and configuration adjustment of the W slab reduce the H binding to vacancies on the W side of the interface. Near the Wb/WC interface, H solution energies in both WC and W slabs weakly decrease approaching the interface. The configuration change of the WC slab significantly increases the H solution energy and binding energy to vacancies but decreases the H migration energy barrier in comparison with the values in hcp WC. The H energetics near the W/WC interfaces indicate the likelihood of H localization and diffusion in the W side of the interface, rather than diffusing through the interface into WC layers.

Yang, L. (ORCID:0000000322166071)↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗
DOE OSTI2021

Correlation of Diffusion Limited Oxidation to Color Difference in Accelerated Aging of Electrical Cable Insulation

Diffusion limited oxidation (DLO) as a phenomenon has complicated material lifetime predictions from accelerated aging studies. Many methods to analyze DLO have been developed in recent years. However, an analytical tool for high throughput and low-cost analysis of DLO affected samples remains absent from the literature. Color differences in polymers exposed to oxidative conditions have recently been observed and correlated to increased concentrations of oxidation products. Herein, total color difference was utilized to rapidly quantify DLO in ethylene propylene rubber (EPR) polymeric cable insulation specimens. Insulation specimens were aged at 121 °C, 136 °C, 150 °C, and 165 °C and a 10% ?E*ab difference between the specimen edge and specimen center was used as the threshold for DLO. Based on these specifications DLO was observed in EPR insulation specimen at temperatures of 136 °C and above, with an increasing degree of DLO observed as the time of exposure increased. The method presented in this work represents a quantitative and high-throughput method for the investigation of DLO with a low cost barrier for entry.

diffusion limited oxidation, DLO, nuclear, electri↗
DOE OSTI2021

Activated penetrant dynamics in glass forming liquids: size effects, decoupling, slaving, collective elasticity and correlation with matrix compressibility

In this work, we employ the microscopic self-consistent cooperative hopping theory of penetrant activated dynamics in glass forming viscous liquids and colloidal suspensions to address new questions over a wide range of high matrix packing fractions and penetrant-to-matrix particle size ratios. The focus is on the mean activated relaxation time of smaller tracers in a hard sphere fluid of larger particle matrices. This quantity also determines the penetrant diffusion constant and connects directly with the structural relaxation time probed in an incoherent dynamic structure factor measurement. The timescale of the non-activated fast dissipative process is also studied and is predicted to follow power laws with the contact value of the penetrant–matrix pair correlation function and the penetrant–matrix size ratio. For long time penetrant relaxation, in the relatively lower packing fraction metastable regime the local cage barriers are dominant and matrix collective elasticity effects unimportant. As packing fraction and/or penetrant size grows, much higher barriers emerge and the collective elasticity associated with the correlated matrix dynamic displacement that facilitates penetrant hopping becomes important. This results in a non-monotonic variation with packing fraction of the degree of decoupling between the matrix and penetrant alpha relaxation times. The conditions required for penetrant hopping to become slaved to the matrix alpha process are determined, which depend mainly on the penetrant to matrix particle size ratio. By analyzing the absolute and relative importance of the cage and elastic barriers we establish a mechanistic understanding of the origin of the predicted exponential growth of the penetrant hopping time with size ratio predicted at very high packing fractions. A dynamics-thermodynamics power law connection between the penetrant activation barrier and the matrix dimensionless compressibility is established as a prediction of theory, with different scaling exponents depending on whether matrix collective elasticity effects are important. Quantitative comparisons with simulations of the penetrant relaxation time, diffusion constant, and transient localization length of tracers in dense colloidal suspensions and cold viscous liquids reveal good agreements. Multiple new predictions are made that are testable via future experiments and simulations. Extension of the theoretical approach to more complex systems of high experimental interest (nonspherical molecules, semiflexible polymers, crosslinked networks) interacting via variable hard or soft repulsions and/or short range attractions is possible, including under external deformation.

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

Lowering the barrier to access information-rich transient kinetic data for machine learning methods

Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.

Catalysis↗
DOE OSTI2020

Electrostatic Barriers to Nanoparticle Accessibility of a Porous Matrix

Translocation from one cavity to another through a narrow constriction (i.e., a “hole”) represents the fundamental elementary process underlying hindered mass transport of nanoparticles and macromolecules within many natural and synthetic porous materials, including intracellular environments. This process is complex and may be influenced by long-range (e.g., electrostatic) particle–wall interactions, transient adsorption/desorption, surface diffusion, and hydrodynamic effects. In this study, we used a three-dimensional (3D) tracking method to explicitly visualize the process of nanoparticle diffusion within periodic porous nanostructures, where electrostatic interactions were mediated via ionic strength. The effects of electrostatic interactions on nanoparticle transport were surprisingly large. For example, an increase in the Debye length of only a few nanometers (in a material with a hole diameter of ~100 nm) increased the mean cavity escape time 3-fold. A combination of computational and experimental analyses indicated that this hindered cavity escape was due to an electrostatic energy barrier in the region of the hole, which was quantitatively explained using DLVO theory. These findings explicitly demonstrate that the cavity escape process was barrier-limited and dominated by electrostatic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗