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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Comparison of Atomic and Electronic Structures of Silica and Sodium Silicate Glasses

Glass scintillators may hold great promise for low-cost, large-volume, shapeable radiation detectors. However, the light yield and energy resolution of glass scintillators to-date have been more than an order of magnitude worse than for crystalline scintillators and far from the theoretical limits. Glass scintillators are fabricated by dissolving rare-earth dopants into a glass matrix. Their operation relies on gamma ray absorption in the glass generating electrons and holes that must migrate to a rare-earth activator atom to emit light. The transport of carriers in the glass limits the performance, particularly in glasses where the solubility limit of activator is low, since carriers may recombine non-radiatively before reaching an activator atom. In this work, we aim to use atomistic simulations to discover the nature of electron transport in specific glass materials and how it may be enhanced by tuning the composition or forming process. The analysis proceeds in two steps: generation of a computational model of a given glass’s atomic structure, then extraction of the electronic structure to correlate electronic structure with carrier transport. Here we report results for two glasses: silica (SiO 2 ) and sodium silicate (Na 2 O:SiO 2 ). Multiple compositions of the latter are studied, namely Na 2 O:SiO 2 ratios of of 1:2, 1:3, and 3:7, with most results focused on the 3:7 composition. The overall goal is to establish a computational framework that can mimic a range of experimental glass structures by tuning computational parameters in the construction of the glass model, and enable studies of the correlation between atomic structure and electronic transport properties of the glass materials. These correlations would direct synthesis parameters for a given glass to optimize its transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electronic Band Structures of a Germanium Halide Perovskite Semiconductor

CsGeX 3 , a class of halide perovskites, is an emergent semiconductor with ferroelectricity and potential optoelectronic properties that can be harnessed for device applications. However, measurements of the electronic structure for this class of material are still lacking. Here, in this work, we report, for the first time, the experimental band structures of CsGeI 3 , a ferroelectric halide perovskite semiconductor, through angle-resolved photoemission spectroscopy (ARPES). The crystals were cleaved along both the (110) and (111) surfaces, facilitating the observation of clear valence band dispersions in several high-symmetry momentum directions. The observed valence band is characterized by a small hole effective mass of ∼0.1m 0 at the valence band maximum, without notable spectral signatures associated with the Rashba effect. Our experimental measurements are supported by electronic structure calculations in the DFT + G0W0 framework, enabling assessment of the band orbital characteristics, dispersion, and spin-splitting. This work unveils the intrinsic electronic and transport properties of CsGeX 3 , thereby advancing the optimization of the optoelectronic properties of this class of materials.

angle-resolved photoemission spectroscopy↗
DOE OSTI2015

Whistlers, helicons, and lower hybrid waves: The physics of radio frequency wave propagation and absorption for current drive via Landau damping

This introductory-level tutorial article describes the application of plasma waves in the lower hybrid range of frequencies (LHRF) for current drive in tokamaks. Wave damping mechanisms in a nearly collisionless hot magnetized plasma are briefly described, and the connections between the properties of the damping mechanisms and the optimal choices of wave properties (mode, frequency, wavelength) are explored. The two wave modes available for current drive in the LHRF are described and compared. The terms applied to these waves in different applications of plasma physics are elucidated. The character of the ray paths of these waves in the LHRF is illustrated in slab and toroidal geometries. Applications of these ideas to experiments in the DIII-D tokamak are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Improved visible light driven photoelectrochemical properties of 3C-SiC semiconductor with Pt nanoparticles for hydrogen generation

We propose the n-type 3C-SiC with Pt nanoparticles (Pt NPs) as photo-anode for photoelectrochemical hydrogen (H{sub 2}) generation. We found that band-edge structure of 3C-SiC is suitable for H{sub 2} generation, and the property can be optimized by dopant (nitrogen) concentration in 3C-SiC. We also confirmed that Pt NPs enhance photoelectrochemical properties showing 0.2%–0.8% higher Incident Photon-to-Current Efficiency than bare 3C-SiC in visible wavelength despite diminished light absorption. Solar-conversion efficiency increases approximately 6.3 times, and H{sub 2} production is improved by 6.5 times with 33% of Faradaic efficiency. Lastly, 3C-SiC surface corrosion is effectively inhibited.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Random poly(3‐hexylthiophene‐ co ‐3‐cyanothiophene‐ co ‐3‐(2‐ethylhexyl)thiophene) copolymers with high open‐circuit voltage in polymer solar cells

ABSTRACT For the purpose of developing poly(3‐hexylthiophene) (P3HT) based copolymers with deep‐lying highest occupied molecular orbital (HOMO) levels for polymer solar cells with high open‐circuit voltage ( V oc ), we report a combined approach of random incorporation of 3‐cyanothiophene (CNT) and 3‐(2‐ethylhexyl)thiophene (EHT) units into the P3HT backbone. This strategy is designed to overcome CNT content limitations in recently reported P3HT‐CNT copolymers, where incorporation of more than 15% of CNT into the polymer backbone leads to impaired polymer solubility and raises the HOMO level. This new approach allows incorporation of a larger CNT content, reaching even lower‐lying HOMO levels. Importantly, a very low HOMO level of −5.78 eV was obtained, representing one of the lowest HOMO values for exclusively thiophene‐based polymers. Lower HOMO levels result in higher V oc and higher power conversion efficiencies (PCE) compared to the previously reported P3HT‐CNT copolymers containing only 3‐hexylthiophene and CNT units. As a result, solar cells based on P3HT‐CNT‐EHT(15:15) , which contains 70% of P3HT, 15% of CNT and 15% of EHT, yield a V oc of 0.83 V in blends with PC 61 BM while preserving high fill factor (FF) and high short‐circuit current density ( J sc ), resulting in 3.6% PCE. Additionally, we explored the effect of polymer number‐average molecular weight ( M n ) on the optoelectronic properties and solar cell performance for the example of P3HT‐CNT‐EHT(15:15). The organic photovoltaic (OPV) performance improves with polymer M n increasing from 3.4 to 6.7 to 9.6 kDa and then it declines as M n further increases to 9.9 and to 16.2 kDa. The molecular weight study highlights the importance of not only the solar cell optimization, but also the significance of individual polymer properties optimization, in order to fully explore the potential of any given polymer in OPVs. The broader ramification of this study lies in potential application of these high band gap copolymers with low‐lying HOMO level in the development of ternary blend photovoltaics as well as tandem OPV. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2016 , 54 , 1526–1536

Rudenko, Andrey E.↗
DOE OSTI2016

Valence-band electronic structure evolution of graphene oxide upon thermal annealing for optoelectronics

We report valence band electronic structure evolution of graphene oxide (GO) upon its thermal reduction. Degree of oxygen functionalization was controlled by annealing temperatures, and an electronic structure evolution was monitored using real-time ultraviolet photoelectron spectroscopy. We observed a drastic increase in density of states around the Fermi level upon thermal annealing at ~600 °C. The result indicates that while there is an apparent band gap for GO prior to a thermal reduction, the gap closes after an annealing around that temperature. This trend of band gap closure was correlated with electrical, chemical, and structural properties to determine a set of GO material properties that is optimal for optoelectronics. The results revealed that annealing at a temperature of ~500 °C leads to the desired properties, demonstrated by a uniform and an order of magnitude enhanced photocurrent map of an individual GO sheet compared to as-synthesized counterpart.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanical Characterization of Loblolly Pine

Biorefineries are faced with various material flow challenges during feeding and handling, due to inherent variability and inhomogeneity of biomass feedstocks. This impacts the efficiency of refinery processes and unit operations. Proper characterization of bulk properties allows for optimal process design and reduction of overall costs. This work is aimed at evaluating the physical and mechanical properties that impact bulk flow of loblolly pine. Cyclic axial compression tests are performed to elucidate consolidation behavior under different stress conditions. The results are then used to develop correlations between material parameters (particle size, tissue type, moisture content) and Elastic Modulus of bulk samples.

09 BIOMASS FUELS↗
DOE OSTI2019

Microscopic origin of multiple exciton emission in low-dimensional lead halide perovskites

Low-dimensional halide perovskites exhibit intriguing excitonic properties and emerge as an important class of self-activated luminescent materials. However, the ability to manipulate and optimize their luminescent properties is limited by the lack of the microscopic understanding of the exciton relaxation and emission and the inconsistency in the theoretical results in the literature. In this work, based on first-principles calculations, we studied excitons in 1D lead halide perovskites, C 4 N 2 H 14 PbBr 4 and C 4 N 2 H 14 PbCl 4 , which are both bright visible-light emitters. We find that, in both compounds, the polaron-pair exciton (EX-PP) is more stable than the onsite exciton (EX-OS) and only the EX-PP emission energy from the calculation is close to the main photoluminescence (PL) peak observed in the experiment. We note the EX-OS is found to emit UV light in both compounds. Therefore, the EX-PP is responsible for the experimentally observed visible light emission in both C 4 N 2 H 14 PbBr 4 and C 4 N 2 H 14 PbCl 4 . Furthermore, the calculated small energy difference between the EX-PP and EX-OS in C 4 N 2 H 14 PbBr 4 suggests that the metastable EX-OS can be thermally populated at room temperature (RT); the calculated EX-OS emission energy agrees well with the energy of a minor PL peak observed at RT but not at 77 K. The validity our approach in the exciton calculation is supported by the benchmark of the calculated exciton emission energies against the experimental results in 13 0D and 1D metal halides. The discrepancies between this work and a recent theoretical study in the literature are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

THE POTENTIAL OF NANOPARTICLE ENHANCED IONIC LIQUIDS (NEILS) AS ADVANCED HEAT TRANSFER FLUIDS

Interest in capturing the energy of the sun is rising as demands for renewable energy sources increase. One area of developing research is the use of concentrating solar power (CSP), where the solar energy is concentrated by using mirrors to direct the sunlight towards a collector filled with a heat transfer fluid (HTF). The HTF transfers the collected energy into pressurized steam, which is used to generate energy. The greater the energy collected by the HTF, the more efficent the electrical energy production is, thus the overall efficiency is controlled by the thermal fluid. Commercial HTFs such as Therminol{reg_sign} (VP-1), which is a blend of biphenyl and diphenyl oxide, have a significant vapor pressure, especially at elevated temperatures. In order for these volatile compounds to be used in CSP systems, the system either has to be engineered to prevent the phase change (i.e., volatilization and condensation) through pressurization of the system, or operate across the phase change. Over thirty years ago, a class of low-melting organic compounds were developed with negligible vapor pressure. These compounds are referred to as ionic liquids (ILs), which are organic-based compounds with discrete charges that cause a significant decrease in their vapor pressure. As a class, ILs are molten salts with a melting point below 100 C and can have a liquidus range approaching 400 C, and in several cases freezing points being below 0 C. Due to the lack of an appreciable vapor pressure, volatilization of an IL is not possible at atmospheric pressure, which would lead to a simplification of the design if used as a thermal fluid and for energy storage materials. Though the lack of a vapor pressure does not make the use of ILs a better HTF, the lack of a vapor pressure is a compliment to their higher heat capacity, higher volummetric density, and thus higher volumetric heat capacity. These favorable physical properties give ILs a pontential advantage over the current commerically used thermal fluids. Also within the past decade nanofluids have gained attention for thermal conductivity enhancment of fluids, but little analysis has been completed on the heat capacity effects of the nanoparticle addition. The idea of ILs or nanofluids as a HTF is not new, as there are several references that have proposed the idea. However, the use of ionic liquid nanofluids containing nanomaterials other than carbon nanotubes has never before been studied. Here, for the first time, nano-particle enhanced ILs (NEILs) have been shown to increase the heat capacity of the IL with no adverse side effects to the ILs thermal stability and, only at high nanoparticle loading, are the IL physical properties affected. An increase of volumetric heat capacity translates into a better heat transfer fluid as more energy is stored per volumetric unit in the solar concentrating section, thus more efficency in increased steam pressure. Results show that the properties of the NEIL are highly dependant on the suspended nanomaterial and careful materials selection is required to fully optimize the nanofluid properties.

14 SOLAR ENERGY↗
DOE OSTI2019

Controlling risk and demand ambiguity in newsvendor models

We use distributionally robust optimization (DRO) to model a general class of newsvendor problems with unknown demand distribution. The goal is to find an order quantity that minimizes the worst-case expected cost among an ambiguity set of distributions. The ambiguity set consists of those distributions that are not far—in the sense of the total variation distance—from a nominal distribution. The maximum distance allowed in the ambiguity set (called level of robustness) places the DRO between the risk-neutral stochastic programming and robust optimization models. An important problem a decision maker faces is how to determine the level of robustness—or, equivalently, how to find an appropriate level of risk-aversion. We answer this question in two ways. Our first approach relates the level of robustness and risk to the regions of demand that are critical (in a precise sense we introduce) to the optimal cost. Our second approach establishes new quantitative relationships between the DRO model and the corresponding risk-neutral and classical robust optimization models. To achieve these goals, we first focus on a single-product setting and derive explicit formulas and properties of the optimal solution as a function of the level of robustness. Then, we demonstrate the practical and managerial relevance of our results by applying our findings to a healthcare problem to reserve operating room time for cardiovascular surgeries. Finally, we extend some of our results to the multi-product setting and illustrate them numerically.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Compositional Models of Glass/Melt Properties and their Use for Glass Formulation

Nuclear waste glasses must simultaneously meet a number of criteria related to their processability, product quality, and cost factors. The properties that must be controlled in glass formulation and waste vitrification plant operation tend to vary smoothly with composition allowing for glass property-composition models to be developed and used. Models have been fit to the key glass properties. The properties are transformed so that simple functions of composition (e.g., linear, polynomial, or component ratios) can be used as model forms. The model forms are fit to experimental data designed statistically to efficiently cover the composition space of interest. Examples of these models are found in literature. The glass property-composition models, their uncertainty definitions, property constraints, and optimality criteria are combined to formulate optimal glass compositions, control composition in vitrification plants, and to qualify waste glasses for disposal. An overview of current glass property-composition modeling techniques is summarized in this paper along with an example of how those models are applied to glass formulation and product qualification at the planned Hanford high-level waste vitrification plant.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗
DOE OSTI2023

Capturing Time-Varying Wake Dynamics Using Hybridized Actuator Disks in Steady-State Simulations for Improved Optimization Efficiency

When optimizing turbine blade properties, using a time varying, unsteady simulation allows for high-fidelity representations of the wake dynamics. Unfortunately these types of optimizations are prohibitively expensive in terms of computation time and memory requirements. This presentation aims to show a method of transferring the wake dynamics of an unsteady simulation to a much more computationally tractable steady state simulation using hybrid actuator disks informed by unsteady, actuator line model dynamics.

actuator disk model↗
DOE OSTI2021

Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature, T break , introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay below T break . We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A New Calmodulin-Binding Protein Expresses in the Context of Secondary Cell Wall Biosynthesis and Impacts Biomass Properties in Populus

Here, a greater understanding of biosynthesis, signaling and regulatory pathways involved in determining stem growth and secondary cell wall chemistry is important for enabling pathway engineering and genetic optimization of biomass properties. The present study describes a new functional role of PdIQD10 , a Populus gene belonging to the IQ67-Domain1 family of IQD genes, in impacting biomass formation and chemistry. Expression studies showed that PdIQD10 has enhanced expression in developing xylem and tension-stressed tissues in Populus deltoides . Molecular dynamics simulation and yeast two-hybrid interaction experiments suggest interactions with two calmodulin proteins, CaM247 and CaM014, supporting the sequence-predicted functional role of the PdIQD10 as a calmodulin-binding protein. PdIQD10 was found to interact with specific Populus isoforms of the Kinesin Light Chain protein family, shown previously to function as microtubule-guided, cargo binding and delivery proteins in Arabidopsis . Subcellular localization studies showed that PdIQD10 localizes in the nucleus and plasma membrane regions. Promoter-binding assays suggest that a known master transcriptional regulator of secondary cell wall biosynthesis (PdWND1B) may be upstream of an HD-ZIP III gene that is in turn upstream of PdIQD10 gene in the transcriptional network. RNAi-mediated downregulation of PdIQD10 expression resulted in plants with altered biomass properties including higher cellulose, wall glucose content and greater biomass quantity. Furthermore, these results present evidence in support of a new functional role for an IQD gene family member, PdIQD10 , in secondary cell wall biosynthesis and biomass formation in Populus.

09 BIOMASS FUELS↗
DOE OSTI2019

Tensile properties, strain rate sensitivity, and activation volume of additively manufactured 316L stainless steels [Tensile properties of 316L stainless steels made by laser powder-bed-fusion additive manufacturing]

The tensile properties of additively manufactured (AM) metals and alloys are among the most important variables that impact the potential applications of these materials. Here we examine and report on the tensile properties of AM 316L stainless steels fabricated by the laser powder-bed-fusion (L-PBF) technique, via twelve sets of optimized laser processing parameters that produce materials with density >98.8 ± 0.10%. A heterogeneous microstructure is observed in all L-PBF samples, including microscopic features such as dislocations, cellular walls, elemental segregations, local misorientations, impurities, precipitates, and a large fraction of low-angle grain boundaries (2-10°, ~40–60%). The derived average grain size defined by high-angle grain boundaries (>10°) is ~30–50 μm. Tensile testing reveals a yield strength ranging from 552 to 635 MPa and a tensile-elongation-to-failure (TEF) of 0.09–0.42 for directly-printed samples, whereas these values are 592–690 MPa and 0.29–0.50 for samples machined from the as-built rectangular thin plates. In all samples, we observe a variation of tensile yield strength within ~15% but not the TEF, suggesting marginal microstructural changes despite a wide range of laser processing parameters. The large scatter of TEF in directly-printed samples originates from the sensitivity of thin gauge geometry (~2 mm 2 cross-section area) to the built-in flaws. We measured a substantially higher strain rate sensitivity (m~0.02–0.03) of L-PBF 316L compared to the coarse-grained counterparts (~0.006), together with a small activation volume of ~20–30b3 (where b is the Burgers vector of 316L). In conclusion, these deformation kinetics parameters suggest that the tensile plasticity of L-PBF 316L is controlled by a much finer microstructural length scale than the measured grain size, consistent with the high strength and juxtaposed nano- to macro-structures seen in these materials. Strategies to optimize the tensile properties of AM materials are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Single-step gas phase synthesis of stable iron aluminide nanoparticles with soft magnetic properties

Soft magnetic alloys at the nanoscale level have long generated a vivid interest as candidate materials for technological and biomedical purposes. Consequently, controlling the structure of bimetallic nanoparticles in order to optimize their magnetic properties, such as high magnetization and low coercivity, can significantly boost their potential for related applications. However, traditional synthesis methods stumble upon the long standing challenge of developing true nanoalloys with effective control over morphology and stability against oxidation. Herein, we report on a single-step approach to the gas phase synthesis of soft magnetic bimetallic iron aluminide nanoparticles, using a versatile co-sputter inert gas condensation technique. This method allowed for precise morphological control of the particles; they consisted of an alloy iron aluminide crystalline core (DO{sub 3} phase) and an alumina shell, which reduced inter-particle interactions and also prevented further oxidation and segregation of the bimetallic core. Remarkably, the as-deposited alloy nanoparticles show interesting soft magnetic properties, in that they combine a high saturation magnetization (170 emu/g) and low coercivity (less than 20 Oe) at room temperature. Additional functionality is tenable by modifying the surface of the particles with a polymer, to ensure their good colloidal dispersion in aqueous environments.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A new hybrid genetic algorithm for optimizing the single and multivariate objective functions

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the most improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.

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