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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Analysis of Al diffusion processes in TiN barrier layers for the application in silicon solar cell metallization

An evaporated Al layer is known as an excellent rear metallization for highly efficient solar cells, but suffers from incompatibility with a common solder process. To enable solar cell-interconnection and module integration, in this work the Al layer is complemented with a solder stack of TiN/Ti/Ag or TiN/NiV/Ag, in which the TiN layer acts as an Al diffusion barrier. X-ray photoelectron spectroscopy measurements prove that diffusion of Al through the stack and the formation of an Al{sub 2}O{sub 3} layer on the stack's surface are responsible for a loss of solderability after a strong post-metallization anneal, which is often mandatory to improve contact resistance and passivation quality. An optimization of the reactive TiN sputter process results in a densification of the TiN layer, which improves its barrier quality against Al diffusion. However, measurements with X-ray diffraction and scanning electron microscopy show that small grains with vertical grain boundaries persist, which still offer fast diffusion paths. Therefore, the concept of stuffing is introduced. By incorporating oxygen into the grain boundaries of the sputtered TiN layer, Al diffusion is strongly reduced as confirmed by secondary ion mass spectroscopy profiles. A quantitative analysis reveals a one order of magnitude lower Al diffusion coefficient for stuffed TiN layers. This metallization system maintains its solderability even after strong post-metallization annealing at 425 °C for 15 min. This paper thus presents an industrially feasible, conventionally solderable, and long-term stable metallization scheme for highly efficient silicon solar cells.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Diffusion of copolymers composed of monomers with drastically different friction factors in copolymer/homopolymer blends

Copolymers are commonly used as interface modifiers that allow for the compatibilization of polymer components in a blend. For copolymers to function as a compatibilizer, they must diffuse through the matrix of the blend to the interface between the two blend components. The diffusivity of a copolymer in a blend matrix therefore becomes important in determining good candidates for use as compatibilizers. In this paper, coarse-grained Monte Carlo simulations using the bond fluctuation model modified with an overlap penalty have been developed to study the diffusive behavior of PS/PMMA random copolymers in a PMMA homopolymer blend. The simulations vary the connectivity between different monomers, the thermodynamic interactions between the monomers which manifest within a chain, and between copolymer and homopolymer matrix and define the monomer friction coefficient of each component independently, allowing for the determination of the combined effect of these parameters on copolymer chain diffusion. Finally, the results of this work indicate that PS-r-PMMA copolymer diffusion is not linearly dependent on the copolymer composition on a logarithmic scale, but its diffusion is a balance of the kinetics governed by the dominant motion of the faster styrene monomers and thermodynamics, which are governed by the concentration of styrene monomer within a given monomer’s local volume.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Diffusive tunneling in an isobaric but non-isothermal fuel-pusher mixture

The hydrodynamic mix of fusion fuel and inert pusher can simultaneously generate smaller fuel pockets and finer pusher layers that separate them. Smaller fuel pockets have greater local Knudsen numbers, which tend to exacerbate the Knudsen layer reactivity reduction. A thinner pusher layer separating the neighboring fuel pockets, on the other hand, can enable the diffusive tunneling of Gamow fuel ions through the pusher layer and hence alleviate the Knudsen layer reactivity degradation. Here in this paper, the diffusive tunneling phenomenon describes a random walk process by which the Gamow fuel ions from one fuel pocket can traverse the inert pusher layer to join a neighboring fuel pocket without losing much of their energy. This is made possible by the much slower collisional slowing down rate compared with the pitch angle scattering rate of light fuel ions with heavier pusher ions. In an isobaric target mixture where fuel and pusher segments can have distinct temperatures, due to their different compressibilities, the temperature effect on the critical pusher layer areal density below which diffusive tunneling can occur, which is a property of the hydrodynamic mix, is understood by computing the ion charge state distribution using a collisional radiative model. This information is fed into the collisionality evaluation, enabling a parametric scan of the diffusive tunneling physics in terms of the target pressure, fuel, and pusher temperatures. It is found that when the gold pusher layer has a temperature above 1 keV, the variation of the pusher temperature has little effect on the critical areal mass density below which diffusive tunneling can occur. If the pusher layer is 1 keV or below, the critical areal mass density rises sharply, indicating that for a stronger fuel-pusher temperature disparity, the onset of diffusive tunneling will be at an earlier stage of the hydrodynamic mix when the fuel-pusher mixing structures are of less reduced size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Multiscale modeling of solute diffusion in triblock copolymer membranes

We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent field theory (SCFT) to predict the structure of the self-assembled, solvated membrane and on-lattice kinetic Monte Carlo (kMC) simulations to model diffusion of solutes. Solvation is simulated in SCFT by constraining the glassy membrane matrix while relaxing the brush-like membrane pore coating against the solvent. The kMC simulations capture the resulting solute spatial distribution and concentration-dependent local diffusivity in the polymer-coated pores; we parameterize the latter using particle-based simulations. We apply our approach to simulate solute diffusion through nonequilibrium morphologies of a model triblock copolymer, and we correlate diffusivity with structural descriptors of the morphologies. We also compare the model’s predictions to alternative approaches based on simple lattice random walks and find our multiscale model to be more robust and systematic to parameterize. Furthermore, our multiscale modeling approach is general and can be readily extended in the future to other chemistries, morphologies, and models for the local solute diffusivity and interactions with the membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Detailed numerical investigation of the Bohm limit in cosmic ray diffusion theory

A standard model in cosmic ray diffusion theory is the so-called Bohm limit in which the particle mean free path is assumed to be equal to the Larmor radius. This type of diffusion is often employed to model the propagation and acceleration of energetic particles. However, recent analytical and numerical work has shown that standard Bohm diffusion is not realistic. In the present paper, we perform test-particle simulations to explore particle diffusion in the strong turbulence limit in which the wave field is much stronger than the mean magnetic field. We show that there is indeed a lower limit of the particle mean free path along the mean field. In this limit, the mean free path is directly proportional to the unperturbed Larmor radius like in the traditional Bohm limit, but it is reduced by the factor δB/B {sub 0} where B {sub 0} is the mean field and δB the turbulent field. Although we focus on parallel diffusion, we also explore diffusion across the mean field in the strong turbulence limit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SPECTRA OF COSMIC RAY ELECTRONS AND DIFFUSE GAMMA RAYS WITH THE CONSTRAINTS OF AMS-02 AND HESS DATA

Recently, AMS-02 reported their results of cosmic ray (CR) observations. In addition to the AMS-02 data, we add HESS data to estimate the spectra of CR electrons and the diffuse gamma rays above TeV. In the conventional diffusion model, a global analysis is performed on the spectral features of CR electrons and the diffuse gamma rays by the GALRPOP package. The results show that the spectrum structure of the primary component of CR electrons cannot be fully reproduced by a simple power law and that the relevant break is around 100 GeV. At the 99% confidence level (C.L.) the injection indices above the break decrease from 2.54 to 2.35, but the ones below the break are only in the range of 2.746–2.751. The spectrum of CR electrons does not need to add TeV cutoff to also match the features of the HESS data. Based on the difference between the fluxes of CR electrons and their primary components, the predicted excess of CR positrons is consistent with the interpretation that these positrons originate from a pulsar or dark matter. In the analysis of the Galactic diffuse gamma rays with the indirect constraint of AMS-02 and HESS data, it is found that the fluxes of Galactic diffuse gamma rays are consistent with the GeV data of the Fermi-Large Area Telescope (LAT) in the high-latitude regions. The results indicate that inverse Compton scattering is the dominant component in the range of hundreds of GeV to tens of TeV, respectively from the high-latitude regions to the low ones, and in all of the regions of the Galaxy the flux of diffuse gamma rays is less than that of CR electrons at the energy scale of 20 TeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Se diffusion in CdTe thin films for photovoltaics

Manipulating CdSeTe bandgrading to enhance photocurrent and carrier lifetime is an essential part of high-performance CdTe photovoltaics (PVs). Here, we examine Se diffusion kinetics in single-crystal and polycrystalline CdTe during deposition, thermal annealing, and CdCl 2 treatments. Se distributions are determined by dynamic secondary-ion-mass spectroscopy and Auger electron spectroscopy depth profiling and coupled with electron backscatter diffraction images of the crystalline structure. Effective bulk and grain boundary diffusion coefficients are determined by analytical models and discussed in the context of processing and film morphology. Se is found to diffuse in CdTe at much higher rates during CdCl 2 treatments than with thermal processing alone. GB diffusion also occurs at a significantly faster rate than bulk diffusion. As a result of these two effects, the near interface bulk and GB Se diffusion during CdCl 2 treatments dominates the bandgrading profiles in CdTe PVs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Self-learning kinetic Monte Carlo simulations of diffusion in ferromagnetic α -Fe–Si alloys

Diffusion in α-Fe-Si alloys is studied using AKSOME, an on-lattice self-learning KMC code, in the ferromagnetic state. Si diffusivity in the α-Fe matrix were obtained with and without the magnetic disorder in various temperature ranges. In addition we studied vacancy diffusivity in ferromagnetic α-Fe at various Si concentrations up to 12.5at.% in the temperature range of 350–550 K. The results were compared with available experimental and theoretical values in the literature. Local Si-atom dependent activation energies for vacancy hops were calculated using a broken-model and were stored in a database. The migration barrier and prefactors for Si-diffusivity were found to be in reasonable agreement with available modeling results in the literature. Magnetic disorder has a larger effect on the prefactor than on the migration barrier. Prefactor was approximately an order of magnitude and the migration barrier a tenth of an electron-volt higher with magnetic disorder when compared to a fully ferromagnetic ordered state. In addition, the correlation between various have a larger effect on the Si-diffusivity extracted in various temperature range than the magnetic disorder. In the case of vacancy diffusivity, the migration barrier more or less remained constant while the prefactor decreased with increasing Si concentration in the disordered or A2-phase of Fe-Si alloy. Important vacancy-Si/Fe atom exchange processes and their activation barriers were also identified and discuss the effect of energetics on the formation of ordered phases in Fe-Si alloys.

AKSOME↗
DOE OSTI2018

Validation study of GENE on ASDEX Upgrade using perturbative thermal diffusivity measured with partial sawtooth heat pulses

Perturbative thermal diffusivity is measured with partial sawtooth-generated heat pulses on ASDEX Upgrade for the first time, and these measurements are used to validate the first nonlinear ion-scale gyrokinetic simulation that agrees with experimentally measured perturbative diffusivity. Recent work on Alcator C-Mod and DIII-D has shown that ion-scale gyrokinetics cannot adequately describe certain plasma conditions, and that in these instances multi-scale simulations may resolve the observed discrepancies. This work presents the first measurements of electron perturbative thermal diffusivity with partial sawteeth on ASDEX Upgrade (measuring values between 2 and 9 m 2 s -1 ), and compares these measurements to those made with more established modulated electron cyclotron heating measurements, finding good agreement within experimental uncertainty. Perturbative diffusivity is found to scale inversely with collisionality across ASDEX Upgrade and Alcator C-Mod plasmas. Finally, perturbative diffusivity is used as a validation constraint in a study with the gyrokinetic code GENE, showing the first instance where an ion-scale gyrokinetic simulation can simultaneously match the experimental ion and electron heat fluxes and the perturbative thermal diffusivity. Here these results indicate that multi-scale effects may only be important in some plasmas, and the collisionality and ratio of high to low wavenumber linear growth rates may distinguish these cases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Maximum CO 2 diffusion inside leaves is limited by the scaling of cell size and genome size

Maintaining high rates of photosynthesis in leaves requires efficient movement of CO 2 from the atmosphere to the mesophyll cells inside the leaf where CO 2 is converted into sugar. CO 2 diffusion inside the leaf depends directly on the structure of the mesophyll cells and their surrounding airspace, which have been difficult to characterize because of their inherently three-dimensional organization. Yet faster CO 2 diffusion inside the leaf was probably critical in elevating rates of photosynthesis that occurred among angiosperm lineages. Here we characterize the three-dimensional surface area of the leaf mesophyll across vascular plants. We show that genome size determines the sizes and packing densities of cells in all leaf tissues and that smaller cells enable more mesophyll surface area to be packed into the leaf volume, facilitating higher CO 2 diffusion. Measurements and modelling revealed that the spongy mesophyll layer better facilitates gaseous phase diffusion while the palisade mesophyll layer better facilitates liquid-phase diffusion. Our results demonstrate that genome downsizing among the angiosperms was critical to restructuring the entire pathway of CO 2 diffusion into and through the leaf, maintaining high rates of CO 2 supply to the leaf mesophyll despite declining atmospheric CO 2 levels during the Cretaceous.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Explainable machine learning for hydrogen diffusion in metals and random binary alloys

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen diffusion, they often lack accuracy when making quantitative predictions. Machine learning models are capable of making accurate predictions, but their inner workings are obscured, rendering it unclear which physical features are truly important. To develop interpretable machine learning models to predict the activation energies of hydrogen diffusion in metals and random binary alloys, we create a database for physical and chemical properties of the species and use it to fit six machine learning models. Our models achieve root-mean-squared errors between 98–119 meV on the testing data and accurately predict that elemental Ru has a large activation energy, while elemental Cr and Fe have small activation energies. By analyzing the feature importances of these fitted models, we identify relevant physical properties for predicting hydrogen diffusivity. While metrics for measuring the individual feature importances for machine learning models exist, correlations between the features lead to disagreement between models and limit the conclusions that can be drawn. Instead grouped feature importance, formed by combining the features via their correlations, agree across the six models and reveal that the two groups containing the packing factor and electronic specific heat are particularly significant for predicting hydrogen diffusion in metals and random binary alloys. In conclusion, this framework allows us to interpret machine learning models and enables rapid screening of new materials with the desired rates of hydrogen diffusion.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Intermolecular correlations are necessary to explain diffuse scattering from protein crystals

Conformational changes drive protein function, including catalysis, allostery, and signaling. X-ray diffuse scattering from protein crystals has frequently been cited as a probe of these correlated motions, with significant potential to advance our understanding of biological dynamics. However, recent work challenged this prevailing view, suggesting instead that diffuse scattering primarily originates from rigid body motions and could therefore be applied to improve structure determination. To investigate the nature of the disorder giving rise to diffuse scattering, and thus the potential applications of this signal, a diverse repertoire of disorder models was assessed for its ability to reproduce the diffuse signal reconstructed from three protein crystals. This comparison revealed that multiple models of intramolecular conformational dynamics, including ensemble models inferred from the Bragg data, could not explain the signal. Models of rigid body or short-range liquid-like motions, in which dynamics are confined to the biological unit, showed modest agreement with the diffuse maps, but were unable to reproduce experimental features indicative of long-range correlations. Extending a model of liquid-like motions to include disorder across neighboring proteins in the crystal significantly improved agreement with all three systems and highlighted the contribution of intermolecular correlations to the observed signal. These findings anticipate a need to account for intermolecular disorder in order to advance the interpretation of diffuse scattering to either extract biological motions or aid structural inference.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. We demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest, corresponding to, e.g., any arbitrary input object or message, through unknown random phase diffusers along the optical path. This hybrid electronic-optical model, trained using supervised learning, comprises a convolutional neural network-based electronic encoder and successive passive diffractive layers that are jointly optimized. After their joint training using deep learning, our hybrid model can transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers never seen before. The resulting electronic-encoder and optical-decoder model was experimentally validated using a 3D-printed diffractive network that axially spans <70λ, where λ = 0.75 mm is the illumination wavelength in the terahertz spectrum, carrying the desired optical information through random unknown diffusers. The presented framework can be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Silver diffusion over silicon surfaces with adsorbed tin atoms

Silver diffusion over the (111), (100), and (110) surfaces of silicon with preliminarily adsorbed tin atoms is studied by Auger electron spectroscopy and low-energy electron diffraction. Diffusion is observed only on the surface of Si(111)-2√3 × 2√3-Sn. The diffusion mechanism is established. It is found that the diffusion coefficient depends on the concentration of diffusing atoms. The diffusion coefficient decreases with increasing silver concentration, while the activation energy and the preexponential factor increase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

An Experimental Study of Diffusivity of Technetium-99 in Hanford Vadose Zone Sediments

One of the methods being considered at the Hanford site in Washington for safely disposing of low-level radioactive wastes (LLW) is to encase the waste in concrete and entomb the packages in the Hanford vadose zone sediments. The current plan for waste isolation consists of stacking low-level waste packages on a trench floor, surrounding the stacks with reinforced steel, and encasing these packages with concrete. Any failure of the concrete encasement may result in water intrusion and consequent mobilization of radionuclides from the waste packages. The mobilized radionuclides may escape from the encased concrete by mass flow and/or diffusion and move into the surrounding subsurface sediments. It is therefore necessary to conduct an assessment of the performance of the concrete encasement structure and the surrounding soil’s ability to retard radionuclide migration. The retardation factors for radionuclides contained in the waste packages can be determined from measurements of diffusion coefficients for these contaminants through concrete and fill material. Because of their anionic nature in aqueous solutions, the radionuclides, 99Tc and 129I were identified as long-term dose contributors in LLW. The leachability and/or diffusion of these radionuclide species must be measured in order to assess the long-term performance of waste grouts when contacted with vadose-zone porewater or groundwater. To measure the diffusivity, a set of experiments were conducted using 99Tc-spiked concrete (with 0 and 4% metallic iron additions) in contact with unsaturated soil half-cells that reflected the typical moisture contents of Hanford vadose zone sediments. The 99Tc diffusion profiles in the soil half cells were measured after a time lapse of ~1.9 yr. Using the concentration profiles, the 99Tc diffusivity coefficients were calculated based on Fick’s Second Law.

techetium, diffusion, vadose zone sediments↗
DOE OSTI2017

Perpendicular Diffusion Coefficient of Comic Rays: The Presence of Weak Adiabatic Focusing

The influence of adiabatic focusing on particle diffusion is an important topic in astrophysics and plasma physics. In the past, several authors have explored the influence of along-field adiabatic focusing on the parallel diffusion of charged energetic particles. In this paper, using the unified nonlinear transport theory developed by Shalchi and the method of He and Schlickeiser, we derive a new nonlinear perpendicular diffusion coefficient for a non-uniform background magnetic field. This formula demonstrates that the particle perpendicular diffusion coefficient is modified by along-field adiabatic focusing. For isotropic pitch-angle scattering and the weak adiabatic focusing limit, the derived perpendicular diffusion coefficient is independent of the sign of adiabatic focusing characteristic length. For the two-component model, we simplify the perpendicular diffusion coefficient up to the second order of the power series of the adiabatic focusing characteristic quantity. We find that the first-order modifying factor is equal to zero and that the sign of the second order is determined by the energy of the particles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Comparison of neutron diffusion and Monte Carlo models for a fission wave

Many groups have used neutron diffusion simulations to study fission wave phenomena in natural or depleted uranium. However, few studies of fission wave phenomena have been published that use Monte Carlo simulations to confirm the results of diffusion models for this type of system. In the present work we show the results of a criticality and burnup simulation of a traveling wave reactor using MCNPX 2.7.0. The characteristics of the fission wave in this simulation are compared with those from a simple one-dimensional, one-group neutron diffusion model. The diffusion simulations produce a wave speed of 5.9 cm/yr versus 5.3 cm/yr for the Monte Carlo simulations. The axial flux profile in the Monte Carlo simulation is similar in shape to the diffusion results, but with different peak values, and the two profiles have an R2 value of 0.93. The {sup 238}U, {sup 239}Np and {sup 239}Pu burnup profiles from the diffusion simulation show good agreement with the Monte Carlo simulations, R values of 0.98, 0.93 and 0.97 respectively are observed. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Diffusion Synthetic Acceleration for High Order S{sub N} Transport on Meshes with Curved Surfaces

Thermal radiation transport is integral to multiphysics applications such as inertial confinement fusion and astrophysics. Materials in these problems can be exceptionally optically thick and diffusive. A transport solver must be capable of accurate and efficient solutions to such problems. Previously, Woods et al. established a proof-of-concept for high order (HO) discontinuous Galerkin finite element (DGFEM) transport on meshes with curved surfaces. They numerically demonstrated the spatial convergence is order p + 1. Remarkably, these convergence rates are relatively invariant to the amount of curvature of the spatial mesh. We present here an extension of this work that demonstrates a rapidly-convergent iterative solver for the FEM transport equations on meshes with curved sides. We use the modified interior penalty (MIP) diffusion synthetic acceleration (DSA) established by Wang and Ragusa. The partially consistent MIP equations stem from the symmetric interior penalty (IP) derivation of the diffusion equation. The IP method is not stable for optically thick cells so it was combined with the diffusion conforming form (DCF), a discretized diffusion equation derived from the discretized S N equations that is not stable for intermediate optical thicknesses. The MIP equations adapt a 'switch' to the IP method in optically thinner regions and the DCF method in optically thicker regions. The literature does not reveal any Fourier analyses performed for iterative transport on meshes with curved surfaces. Wang and Ragusa performed a Fourier analysis for orthogonal meshes and our results appear to be as expected. Previous literature has reported on some of the sensitivities that affect the spectral radius of DSA schemes: polynomial order, and scattering ratios. Presently, we focus on the sensitivity of the spectral radius to polynomial order, scattering ratio, the constant C, and mesh curvature for varying cell thicknesses. We also numerically study the behavior of the spectral radius to verify our DSA implementation. A sequence of problems is designed to exercise the acceleration. As the problems become more optically thick and diffusive, the accelerated solution continues to converge toward the analytic solution. We employ the Modular Finite Element Methods (MFEM) package, developed at Lawrence Livermore National Laboratory, to generate the linear algebraic system of equations for each angle in the discrete ordinates quadrature set, and use UMFPack to solve this system of equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗