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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 OSTI2018

Supernova-Explosion Mechanism Involving Neutrinos

A major part of the energy released upon the gravitational collapse of massive-star cores is carried away by neutrinos. Neutrinos play a crucial role in collapsing supernovae (SNe). At the present time, mathematical models of core-collapse SNe are based on multidimensional gas dynamics and thermonuclear reactions, whereas the neutrino transport is frequently treated in simplified way. An accurate analysis of neutrinos in a spherically symmetric gravitational collapse is performed on the basis of Boltzmann kinetic equations including all weak-interaction reactions with exact quantum-mechanical matrix elements. The role of multidimensional effects is studied bymeans of multidimensional gas dynamics allowing for the neutrino transport via diffusion treated by employing flux limiters. The possibility of largescale convection, which is of interest both from the point of view of explaining a type II supernova (SN) and from the point of view of implementing an experiment aimed at detecting possible energetic (≳10 MeV) neutrinos from an SN, is discussed. Thermonuclear burning leads to the explosion of a type I SN. A hot central region and the subsequent large-scale convection may also play an important role in the SN mechanism. If neutrinos and convection play a key role for a type II SN, then, in order to explain gamma radiation from product radioactive elements, convection is of importance in the case of SNe belonging to both types. In addition, convection may be important for bright type I SNe. Original methods are presented for multidimensional gas dynamics involving thermonuclear burning and for multitemperature gas dynamics involving radiative transfer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Anderson acceleration and application to the three-temperature energy equations

The Anderson acceleration method is an algorithm for accelerating the convergence of fixed-point iterations, including the Picard method. Anderson acceleration was first proposed in 1965 and, for some years, has been used successfully to accelerate the convergence of self-consistent field iterations in electronic-structure computations. Recently, the method has attracted growing attention in other application areas and among numerical analysts. Compared with a Newton-like method, an advantage of Anderson acceleration is that there is no need to form the Jacobian matrix. Thus the method is easy to implement. In this paper, an Anderson-accelerated Picard method is employed to solve the three-temperature energy equations, which are a type of strong nonlinear radiation-diffusion equations. Two strategies are used to improve the robustness of the Anderson acceleration method. One strategy is to adjust the iterates when necessary to satisfy the physical constraint. Another strategy is to monitor and, if necessary, reduce the matrix condition number of the least-squares problem in the Anderson-acceleration implementation so that numerical stability can be guaranteed. Numerical results show that the Anderson-accelerated Picard method can solve the three-temperature energy equations efficiently. Compared with the Picard method without acceleration, Anderson acceleration can reduce the number of iterations by at least half. A comparison between a Jacobian-free Newton–Krylov method, the Picard method, and the Anderson-accelerated Picard method is conducted in this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Beyond fragmented dopant dynamics in quantum spin lattices: Robust localization and non-Gaussian diffusion

The motion of dopants in magnetic spin lattices has received tremendous attention for at least four decades due to its connection to high-temperature superconductivity. Despite these efforts, we lack a complete understanding of their behavior, especially out of the equilibrium and at nonzero temperatures. In this paper, we take a significant step towards a much deeper understanding based on state-of-the-art matrix-product-state calculations. In particular, we investigate the nonequilibrium dynamics of a dopant in two-leg 𝑡−𝐽 ladders with antiferromagnetic XXZ spin interactions. In the Ising limit, we find that the dopant is localized for all investigated nonzero temperatures due to an emergent disordered potential, with a localization length controlled by the underlying correlation length of the spin lattice, which increases exponentially with decreasing temperature. The dopant, hereby, only delocalizes asymptotically in the zero temperature limit. This greatly generalizes the localization effect discovered recently in Hilbert space fragmented models [Phys. Rev. Res. 6, 023325 (2024), SciPost Phys. Core 7, 054 (2024)]. In the presence of spin-exchange processes at rate 𝛼, the dopant diffuses with a diffusion coefficient, 𝐷 ℎ , depending nonmonotonically on 𝛼. It initially increases linearly as 𝐷 ℎ ∝ 𝛼 for 𝛼 ≪ 1 before dropping off as 𝛼 −1 for 𝛼 > 1. Moreover, we show that the underlying spin dynamics at infinite temperature behaves qualitatively the same, albeit with important quantitative differences. We substantiate these findings by showing that the dynamics features self-similar scaling behavior, which strongly deviates from the Gaussian behavior of regular diffusion, especially for weak spin exchange. Finally, we show that the diffusion coefficient 𝐷 ℎ follows an Arrhenius relation at high temperatures, whereby it is exponentially suppressed upon cooling.

Anomalous diffusion↗
DOE OSTI2025

Exploring the energy landscape of RBMs: reciprocal space insights into bosons, hierarchical learning and symmetry breaking

Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationships among these models remain largely unexplored, a gap that hinders the development of a unified theory of AI learning. In this work, we address two central challenges: clarifying the connections between different deep generative models and deepening our understanding of their learning mechanisms. We focus on Restricted Boltzmann Machines (RBMs), a class of generative models known for their universal approximation capabilities for discrete distributions. By introducing a reciprocal space formulation for RBMs, we reveal a connection between these models, diffusion processes, and systems of coupled bosons. Our analysis shows that at initialization, the RBM operates at a saddle point, where the local curvature is determined by the singular values of the weight matrix, whose distribution follows the Marc̆enko-Pastur law and exhibits rotational symmetry. During training, this rotational symmetry is broken due to hierarchical learning, where different degrees of freedom progressively capture features at multiple levels of abstraction. This leads to a symmetry breaking in the energy landscape, reminiscent of Landau’s theory. This symmetry breaking in the energy landscape is characterized by the singular values and the weight matrix eigenvector matrix. We derive the corresponding free energy in a mean-field approximation. We show that in the limit of infinite size RBM, the reciprocal variables are Gaussian distributed. Our findings indicate that in this regime, there will be some modes for which the diffusion process will not converge to the Boltzmann distribution. To illustrate our results, we trained replicas of RBMs with different hidden layer sizes using the MNIST dataset. Our findings not only bridge the gap between disparate generative frameworks but also shed light on the fundamental processes underpinning learning in deep generative models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Exploratory Project: Rigid nanostructured organic polymer monolith for in situ collection and analysis of plant metabolites from soil matrices

Plant metabolites released from litter leachates and root exudates enable plants to adapt and survive in a wide range of habitats by facilitating resource foraging and plant-organismal interactions, and could influence soil carbon storage. The biological functions of these plant inputs and the organismal interactions they facilitate in soil are strictly governed by their composition and molecular identity. Our current understanding about the molecular identity of exudates is based on physiological studies that are done in soil-less axenic cultures. On the other hand, ecological studies that rely on isotope labeling to track the fluxes of carbon from plants to soil have found the complexities of soil-microbe matrices as an insurmountable barrier to undertake any meaningful molecular level characterization of plant inputs. Although it is constantly advocated to undertake a molecular level identification of the dynamicity of plant metabolites in soils, the complexity of soil system has thus far prevented any such endeavors. We developed polymeric probes through in-situ polymerization of poly(styrene-co-vinylbenzyl chloride-co-divinylbenzene) to elucidate the chemical environment of the soil to which the plant roots are exposed. Hypercrosslinking of the polymeric probes through an in-situ Friedel-Crafts alkylation significantly increased the surface area and the sorption capacity of the probes. Surface functionalization of the probes using a hybrid approach was also attempted. The efficacy of these probes was tested using batch equilibration. Scanning electron microscopy revealed extensive modification of the surface of the probes through hypercrosslinking. The probes exhibited a lower site specific sorption (slope of Freundlich adsorption isotherm close to unity) and percent recovery of the sorbed compounds from the probes were >70, indicating a predominance of reversible sorption. Further we imparted specificity to this copolymer matrix by using molecular-template imprinting approach for the selective capture of less abundant plant metabolites from a crowded soil/litter leachate. Our results suggests that i) the root exudate pattern of plants is highly dependent on the nutrient status of the plant, with greater specificity of root exudation occurring in growing medium with low available form of nutrients, ii) the chemical composition of root exudation is a function of the distance of sampling from the source-roots, with the composition of root exudation being more enriched in polar metabolites farther from the source-roots, iii) Further we demonstrated that the compounds present in real root exudates diffuse farther from the source roots than those in artificial root exudates that are traditionally used. Thus, our project highlights how the soil matrix is instrumental in modifying the chemical composition of root exudates, and highlights that, apart from the plant physiology, the specificity and function of root exudates is also modified by environmental factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Using complimentary microscopy methods to examine Ni-Mn-Si-precipitates in highly-irradiated reactor pressure vessel steels

Nano-scale Ni-Mn-Si-rich precipitates formed in a reactor pressure vessel steel under high neutron fluence have been characterized using highly complimentary atom probe tomography (APT) and scanning transmission electron microscopy with energy dispersive spectroscopy (STEM-EDS) combined with STEM-EDS modeling. Using these techniques in a synergistic manner to overcome the well-known trajectory aberrations in APT data, the average upper limit Fe concentration within the precipitates was found to be ~6 at.%. Using this knowledge, accurate compositions of the precipitates was determined and it was found that the spread of precipitate compositions was large, but mostly centered around the Γ2-and G-phases. The use of STEM-EDS also allowed for larger areas to be examined, and segregation of minor solutes was observed to occur on grain boundaries, along with Ni-Mn-Si-rich precipitates that were smaller in size than those in the matrix. Solute segregation at the grain boundaries is proposed to occur through a radiation induced segregation or radiation enhanced diffusion mechanism due to the presence of a denuded zone about the grain boundary. It is also proposed that the reduced precipitate size at the grain boundaries is due to the structure of the grain boundary. The lack of Ni-Mn-Si precipitates observed in larger Mo-rich precipitates is also discussed, and the absence of the minor solutes required to form the Ni-Mn-Si precipitates results in the lack of nucleation. This is in contrast to cementite phases in which Ni-Mn-Si precipitates have been seen to be formed. It was also determined through this work that the exclusion of all the Fe ions during atom probe analysis is a reasonable approximation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Strong Enhancement of Nanoconfined Water Mobility by a Structure Breaking Salt

For the majority of the water present on earth, the two most important factors influencing its behavior are confinement, in either inorganic or organic matrixes, and the presence of solutes. Here, we investigate the effect of confinement in 3 nm pores on water diffusivity in aqueous solutions with archetypical solutes, a structure making (kosmotrope) NaCl and a structure breaking (chaotrope) KCl, up to 1.0 M in concentration. The water diffusivity in bulk aqueous solutions in such a concentration range is known to decrease very slightly in the presence of NaCl and increase very slightly in the presence of KCl. However, here we observe the water diffusivity in confined H 2 O–KCl increases by a factor of 2 compared to the pure water diffusivity in the same confinement. This unusually strong cumulative effect of confinement and a structure breaking additive may have profound implications for the mobility and transport of aqueous species in nature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 OSTI2015

MRI reconstruction of multi-image acquisitions using a rank regularizer with data reordering

Purpose: To improve rank constrained reconstructions for undersampled multi-image MRI acquisitions. Methods: Motivated by the recent developments in low-rank matrix completion theory and its applicability to rapid dynamic MRI, a new reordering-based rank constrained reconstruction of undersampled multi-image data that uses prior image information is proposed. Instead of directly minimizing the nuclear norm of a matrix of estimated images, the nuclear norm of reordered matrix values is minimized. The reordering is based on the prior image estimates. The method is tested on brain diffusion imaging data and dynamic contrast enhanced myocardial perfusion data. Results: Good quality images from data undersampled by a factor of three for diffusion imaging and by a factor of 3.5 for dynamic cardiac perfusion imaging with respiratory motion were obtained. Reordering gave visually improved image quality over standard nuclear norm minimization reconstructions. Root mean squared errors with respect to ground truth images were improved by ∼18% and ∼16% with reordering for diffusion and perfusion applications, respectively. Conclusions: The reordered low-rank constraint is a way to inject prior image information that offers improvements over a standard low-rank constraint for undersampled multi-image MRI reconstructions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CO 2 in Ionene–Ionic Liquid Composite Membranes

Abstract Ionene – ionic liquid (IL) composites are promising materials for CO 2 separation, yet a molecular‐level understanding of their structure and its impact on CO 2 speciation, solubility, rotation, and diffusivity remains unclear. Herein, using multimodal nuclear magnetic resonance (NMR), time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), atomic force microscopy (AFM), and molecular dynamics (MD) simulations, we reveal that the composites contain IL‐rich domains extending across hundreds of nanometres within the ionene matrix, and these bicontinuous domains span the entire membrane depth. CO 2 also absorbs into the ionene matrix, with the distribution between two CO 2 species varying with temperature and time. The rotational correlation times of these two species are on the timescale of 0.1 and 1 ns, respectively. As IL content increases, the ionic domains expand, resulting in higher CO 2 solubility due to enhanced molecular dynamics and increased free volume in both ionene backbones and IL‐rich regions. Although CO 2 diffusion in the membranes is an order of magnitude slower than in bulk IL, the activation energy for CO 2 diffusion remains comparable. Ionene‐IL composites represent a promising platform for designing CO 2 separation membranes, offering enhanced CO 2 diffusion and selectivity through IL‐rich domains, and increased CO 2 solubility and mechanical integrity from the ionene matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Using θ' interfaces as templates for planar L1 2 precipitation in AlCuMnZr alloys

Controlled Mn and Zr additions to Al-Cu alloys have allowed for the improved retention of mechanical properties after extended 350°C exposures by stabilizing the main strengthening θ' (Al 2 Cu) phase. Ultimately, θ'/L1 2 (Al 3 Zr) co-precipitate formation stabilizes θ' most effectively; however, Zr diffuses sluggishly and has low solubility in aluminum castings. Increasing the Zr segregation rate would allow for faster and more effective θ'/L1 2 co-precipitation. It is demonstrated that the Zr segregation rate is faster when the Zr matrix content is higher. A much higher Zr matrix content was achieved by rapid cooling during additive manufacturing (AM) that produces θ'/L1 2 co-precipitation faster, which is shown by scanning transmission electron microscopy and atom probe tomography experiments. It was also found that Zr continuously segregates to θ' interfaces up to the most aggressive heat treatment studied such that planar L1 2 precipitates remain after the metastable θ' dissolves. In this manner, we demonstrate that θ' coherent interfaces serve as perfect templates to form stable planar L1 2 precipitates that can provide strength at higher temperatures than traditional θ' strengthened AlCu alloys. This work introduces an alloy design strategy that uses metastable precipitates to quickly nucleate and grow co-precipitates with a desired geometry that contain slow diffusing elements. These ideas can be applied to engineer more heat resistant alloys by taking advantage of high solute matrix contents enabled by rapid cooling during additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Pore-scale modelling of Ostwald ripening

In a saturated solution with dispersed clusters of a second phase, the mechanism by which the larger clusters grow at the expense of the smaller ones is called Ostwald ripening. Although the mechanism is well understood in situations where multiple clusters of gas exist in a liquid solution, evolution is much more complicated to predict when the two phases interact with a solid matrix, since the solid plays a significant role in determining the shape of the interface. In this paper, we study capillary dominated regimes in porous media where the driving force is inter-cluster diffusion. By decomposing the Ostwald ripening mechanism into two processes that operate on different time scales – the diffusion of solute gas in the liquid and the readjustment of the shape of the gas–liquid interface to accommodate a change in mass – we develop a sequential algorithm to solve for the evolution of systems with multiple gas ganglia. In the absence of a solid matrix, thermodynamic equilibrium is reached when all of the gas phase aggregates to form one large bubble. In porous media on the other hand, we find that ripening can lead to equilibrium situations with multiple disconnected ganglia, and that evolution is highly dependent on initial conditions and the structure of the solid matrix. The fundamental difference between the two cases is in the relationship between mass and capillary pressure.

bio-inspired, mechanical behavior, carbon sequestr↗
DOE OSTI2017

Grain Growth in Nanocrystalline Mg-Al Thin Films

An improved understanding of grain growth kinetics in nanocrystalline materials, and in metals and alloys in general, is of continuing interest to the scientific community. In this study, Mg - Al thin films containing ~10 wt.% Al and with 14.5 nm average grain size were produced by magnetron-sputtering and subjected to heat-treatments. The grain growth evolution in the early stages of heat treatment at 423 K (150 °C), 473 K (200 °C) and 573K (300 °C) was observed with transmission electron microscopy and analyzed based upon the classical equation developed by Burke and Turnbull. The grain growth exponent was found to be 7±2 and the activation energy for grain growth was 31.1±13.4 kJ/mol, the latter being significantly lower than in bulk Mg-Al alloys. The observed grain growth kinetics are explained by the Al supersaturation in the matrix and the pinning effects of the rapidly forming beta precipitates and possibly shallow grain boundary grooves. The low activation energy is attributed to the rapid surface diffusion which is dominant in thin film systems.

activation energy↗
DOE OSTI2021

Optimization of four terminal rear heterojunction GaAs on Si interdigitated back contact tandem solar cells

High-efficiency, four-terminal tandem solar cells composed of thin GaAs films mechanically stacked onto interdigitated back contact silicon solar cells with a glass interlayer are demonstrated. The optimal thickness of the absorber layer of a rear heterojunction GaAs subcell for use in four terminal tandem solar cells was studied. GaAs top cells with absorber layer thicknesses of 1.5, 1.9, 2.3, 2.8, and 3.5 µm were fabricated on glass and mechanically stacked onto interdigitated back-contact Si bottom cells. All tandem cells were found to have efficiencies above 30% under the AM1.5 G spectrum demonstrating a relatively weak sensitivity to thickness in the four-terminal configuration. We found the 2.8 µm absorber layer cell to have the highest top cell and tandem cell efficiency at 26.38% and 32.57%, respectively. Optical modeling with transfer matrix method for the planar top cell and Lambertian light trapping in the textured Si subcell, along with drift-diffusion Hovel equations, were used to show photon recycling enhancement to the effective diffusion length and VOC of the top cell as a result of the low-index glass interlayer.

14 SOLAR ENERGY↗
DOE OSTI2017

On the delta-type doping of GaAs-based heterostructures with manganese compounds

Heterostructures, which incorporate GaAs/InGaAs/GaAs quantum wells and are doped with spatially remote monatomic Mn layers, are formed on GaAs(001) substrate under conditions of multilayer buildup by the method of molecular-beam epitaxy. Combined studies of the obtained samples were performed by the method of secondary-ion mass spectrometry, by measurements of X-ray diffraction, and using a transmission electron microscope. The heterostructures under study with a doping impurity concentration amounting to 0.5 single layers are elastically stressed and demonstrate planar clearly defined interfaces without visible extended or point defects. A method for visualization of the distribution of the manganese concentration in the three-dimensional GaAs matrix in the vicinity of a quantum well is suggested. According to experimental results, there is a probability for manganese diffusion into the GaAs/InGaAs/GaAs quantum well when the critical thickness of the GaAs buffer layer is decreased to a value smaller than 3 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Thermophysical properties of sintered aluminum-silicon

The effect of silicon addition to aluminum on the thermophysical properties of Al was experimentally investigated. Thermal diffusivity, heat capacity, density, and thermal expansion of sintered Al-Si samples with Si content ranging 0-8 wt% were measured. For U-Mo/Al dispersion fuel for research reactors, an addition of Si (up to 8 wt% Si) to the Al matrix has been adopted as a method to reduce the formation of interaction layer between the U-Mo and the Al. In this study, the Si-added Al matrix was simulated by using a powder metallurgical method, in which an Al powder and a Si powder were mixed and sintered. All measured properties decreased with the addition of Si. The effect was most pronounced in thermal diffusivity while the decreases in heat capacity and density were relatively insignificant. The measured thermal conductivity from the present study was higher than those measured data for alloy samples available in the literature to the differences in the fabrication method. All measured data including this study, however, were lower than the prediction by the Bruggeman model. It is because the model assumes an ideal heat-transfer conditions such as spherical particles, homogeneous particle distribution, perfect bonding between Al and Si. (C) 2018 Elsevier B.V. All rights reserved.

Cho, Tae Won↗
DOE OSTI2020

Effects of Tethered Polymers on Dynamics of Nanoparticles in Unentangled Polymer Melts

Polymer-tethered nanoparticles (NPs) are commonly added to a polymer matrix to improve the material properties. Critical to the fabrication and processing of such composites is the mobility of the tethered NPs. Here, we study the motion of tethered NPs in unentangled polymer melts using molecular dynamics simulations, which offer a precise control of the grafted chain length N g and the number z of grafted chains per particle. As Ng increases, there is a crossover from particle-dominated to tethered-chain-dominated terminal diffusion of NPs with the same z. The mean squared displacement of loosely tethered NPs in the case of tethered-chain-dominated terminal diffusion exhibits two subdiffusive regimes at intermediate time scales for small z. The first one at shorter time scales arises from the dynamical coupling of the particle and matrix chains, while the one at longer time scales is due to the participation of the particle in the dynamics of the tethered chains. The friction of loosely grafted chains in unentangled melts scales linearly with the total number of monomers in the chains, as the friction of individual monomers is additive in the absence of hydrodynamic coupling. As more chains are grafted to a particle, hydrodynamic interactions between grafted chains emerge. As a result, there is a nondraining layer of hydrodynamically coupled chain segments surrounding the bare particle. Outside the nondraining layer is a free-draining layer of grafted chain segments with no hydrodynamic coupling. The boundary of the two layers is the stick surface where the shear stress due to the relative melt flow is balanced by the friction between the grafted and melt chains in the interpenetration layer. The stick surface is located further away from the bare surface of the particle with higher grafting density.

42 ENGINEERING↗