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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Quantifying the impact of material-model error on macroscale quantities-of-interest using multiscale a posteriori error-estimation techniques

An a posteriori error-estimation framework is introduced to quantify and reduce modeling errors resulting from approximating complex mesoscale material behavior with a simpler macroscale model. Such errors may be prevalent when modeling welds and additively manufactured structures, where spatial variations and material textures may be present in the microstructure. We consider a case where a <100> fiber texture develops in the longitudinal scanning direction of a weld. Transversely isotropic elastic properties are obtained through homogenization of a microstructural model with this texture and are considered the reference weld properties within the error-estimation framework. Conversely, isotropic elastic properties are considered approximate weld properties since they contain no representation of texture. Errors introduced by using isotropic material properties to represent a weld are assessed through a quantified error bound in the elastic regime. Lastly, an adaptive error reduction scheme is used to determine the optimal spatial variation of the isotropic weld properties to reduce the error bound.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Upscaling Calcite Growth Rates from the Mesoscale to the Macroscale

Quantitative prediction of mineral reaction rates in the subsurface remains a daunting task partly because a key parameter for macroscopic models, the reactive site density, is poorly constrained. Here we report atomic force microscopy (AFM) measurements on the calcite surface of monomolecular step densities, treated as equivalent to the reactive site density, as a function of aqueous calcium-to-carbonate ratio and saturation index. Data for the obtuse step orientation are combined with existing step velocity measurements to generate a model that predicts overall macroscopic calcite growth rates. The model is quantitatively consistent with several published macroscopic rates under a range of alkaline solution conditions, particularly for two of the most comprehensive data sets without the need for additional fit parameters. The model reproduces peak growth rates and its functional form is simple enough to be incorporated into reactive transport or other macroscopic models designed for predictions in porous media. However, it currently cannot model equilibrium, pH effects, and may overestimate rates at high aqueous calcium-to-carbonate ratios. The discrepancies in rates at high calcium-to-carbonate ratios may be due to differences in pre-treatment, such as exposing the seed material to SI 1.0 to generate/develop growth hillocks, or other factors.

Bracco, Jacquelyn N.↗
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Micro- and macroscale coefficients of friction of cementitious materials

Millions of metric tons of cementitious materials are produced, transported and used in construction each year. The ease or difficulty of handling cementitious materials is greatly influenced by the material friction properties. In the present study, the coefficients of friction of cementitious materials were measured at the microscale and macroscale. The materials tested were commercially-available Portland cement, Class C fly ash, and ground granulated blast furnace slag. At the microscale, the coefficient of friction was determined from the interaction forces between cementitious particles using an Atomic Force Microscope. At the macroscale, the coefficient of friction was determined from stresses on bulk cementitious materials under direct shear. The study indicated that the microscale coefficient of friction ranged from 0.020 to 0.059, and the macroscale coefficient of friction ranged from 0.56 to 0.75. The fly ash studied had the highest microscale coefficient of friction and the lowest macroscale coefficient of friction. -- Highlights: •Microscale (interparticle) coefficient of friction (COF) was determined with AFM. •Macroscale (bulk) COF was measured under direct shear. •Fly ash had the highest microscale COF and the lowest macroscale COF. •Portland cement against GGBFS had the lowest microscale COF. •Portland cement against Portland cement had the highest macroscale COF.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Comparing Macroscale and Microscale Simulations of Porous Battery Electrodes

This article describes a vertically-integrated exploration of NMC electrode rate limitations, combining experiments with corresponding macroscale (macro-homogeneous) and microscale models. Parameters common to both models were obtained from experiments or based on published results. Positive electrode tortuosity was the sole fitting parameter used in the macroscale model, while the microscale model used no fitting parameters, instead relying on microstructural domains generated from X-ray microtomography of pristine electrode material held under compression while immersed in electrolyte solution (additionally providing novel observations of electrode wetting). Macroscale simulations showed that the capacity decrease observed at higher rates resulted primarily from solution-phase diffusion resistance. This ability to provide such qualitative insights at low computational costs is a strength of macroscale models, made possible by neglecting electrode spatial details. To explore the consequences of such simplification, the corresponding, computationally-expensive microscale model was constructed. This was found to have limitations preventing quantitatively accurate predictions, for reasons that are discussed in the hope of guiding future work. Nevertheless, the microscale simulation results complement those of the macroscale model by providing a reality-check based on microstructural information; in particular, this novel comparison of the two approaches suggests a reexamination of salt diffusivity measurements.

25 ENERGY STORAGE↗
DOE OSTI2016

Direct numerical simulations in solid mechanics for quantifying the macroscale effects of microstructure and material model-form error

Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cell represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Furthermore, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Macroscale superlubricity by a sacrificial carbon nanotube coating

Superlubricity, i.e., coefficient of friction (COF) below 0.01, was earlier limited to microscale in controlled environments in the earlier literature and more recently realized for macroscale sliding of ceramic or carbon surfaces lubricated by water or other polar fluids. However, there is lack of report of superlubricity for the most common bearing system, i.e., steel-steel contact in non-polar oil lubrication. Here, in this work, we present ultra-low COF of 0.001–0.007 by using a sacrificial coating composed of vertically-aligned carbon nanotubes (CNTs) for macroscale steel-steel sliding under minimum quantity lubrication (MQL) of a polyalphaolefin (PAO) oil in the ambient environment. Raman spectroscopy and electron microscopy analyses detected graphene-containing tribofilms on both the steel surfaces, which was produced by the fractured CNT flakes and metallic wear debris during running-in. The in situ formed graphene-graphene contact interface presumably possesses a low shear resistance leading to superlubricity. The presence of oil, despite as little as one droplet, has proven to be crucial. Such a superlubricity performance has shown good sustainability in extended testing of more than 500,000 cycles and strong ability of accommodating changes in sliding conditions. Results here demonstrate feasibility with fundamental insights for achieving ambient environment macroscale superlubricity.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Encapsulation of Perovskite Nanocrystals into Macroscale Polymer Matrices: Enhanced Stability and Polarization

Lead halide perovskites hold promise for photonic devices, due to their superior optoelectronic properties. However, their use is limited by poor stability and toxicity. We demonstrate enhanced water and light stability of high-surface-area colloidal perovskite nanocrystals by encapsulation of colloidal CsPbBr 3 quantum dots into matched hydrophobic macroscale polymeric matrices. This is achieved by mixing the quantum dots with presynthesized high-molecular-weight polymers. In this work, we monitor the photoluminescence quantum yield of the perovskite-polymer nanocomposite films under water-soaking for the first time, finding no change even after >4 months of continuous immersion in water. Furthermore, photostability is greatly enhanced in the macroscale polymer-encapsulated nanocrystal perovskites, which sustain >10 10 absorption events per quantum dot prior to photodegradation, a significant threshold for potential device use. Control of the quantum dot shape in these thin-film polymer composite enables color tunability via strong quantum-confinement in nanoplates and significant room temperature polarized emission from perovskite nanowires. Not only does the high-molecular-weight polymer protect the perovskites from the environment but also no escaped lead was detected in water that was in contact with the encapsulated perovskites for months. In conclusion, our ligand-passivated perovskite-macroscale polymer composites provide a robust platform for diverse photonic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Metal Structural Environment in Zn x Ni 1-x O Macroscale and Nanoscale Solid Solutions

The metal structural environments in macroscale and nanoscale Zn x Ni 1–x O solid solutions were examined using X-ray diffraction (XRD), X-ray absorption spectroscopy (XAS), and X-ray photoelectron spectroscopy (XPS). XRD demonstrates that solid solutions form for both macroscale (bulk) and nanoscale crystallites, and that the lattice parameter increases linearly as the amount of zinc increases, an indication of a homogeneous solid solution. XAS for both the bulk material and the nanoparticles reveals that the zinc atoms are incorporated into the rocksalt lattice and do not form zinc oxide clusters. The X-ray absorption near edge spectroscopy (XANES) of the Zn k-edge region in the solid solution is similar to the Ni k-edge region of NiO, and not the Zn k-edge region of ZnO. XPS confirms that solid solutions are formed; Auger parameters for zinc are consistent with a different geometry than the tetrahedral coordination of wurtzite ZnO. Nanoscaled solid solutions show evidence of a lattice contraction relative to macroscale solutions of the same concentration. While the contraction persists across the entire concentration range, the nanoparticle lattice parameter approaches the bulk Zn x Ni 1–x O value as the concentration of zinc increases to predict ZnO rocksalt lattice parameters that are in agreement with observed ZnO data.

Peck, Matthea A.↗
DOE OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Abstract Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

Song, Jiaqi↗
DOE OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Macroscale structural changes of thylakoid architecture during high light acclimation in Chlamydomonas reinhardtii

Abstract Photoprotection mechanisms are ubiquitous among photosynthetic organisms. The photoprotection capacity of the green alga Chlamydomonas reinhardtii is correlated with protein levels of stress-related light-harvesting complex (LHCSR) proteins, which are strongly induced by high light (HL). However, the dynamic response of overall thylakoid structure during acclimation to growth in HL has not been fully understood. Here, we combined live-cell super-resolution microscopy and analytical membrane subfractionation to investigate macroscale structural changes of thylakoid membranes during HL acclimation in Chlamydomonas . Subdiffraction-resolution live-cell imaging revealed that the overall thylakoid structures became thinned and shrunken during HL acclimation. The stromal space around the pyrenoid also became enlarged. Analytical density-dependent membrane fractionation indicated that the structural changes were partly a consequence of membrane unstacking. The analysis of both an LHCSR loss-of-function mutant , npq4 lhcsr1 , and a regulatory mutant that over-expresses LHCSR, spa1-1 , showed that structural changes occurred independently of LHCSR protein levels, demonstrating that LHCSR was neither necessary nor sufficient to induce the thylakoid structural changes associated with HL acclimation. In contrast, stt7-9 , a mutant lacking a kinase of major light-harvesting antenna proteins, had a slower thylakoid structural response to HL relative to all other lines tested but still showed membrane unstacking. These results indicate that neither LHCSR- nor antenna-phosphorylation-dependent HL acclimation are required for the observed macroscale structural changes of thylakoid membranes in HL conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Macroscale and Nanoscale Photoelectrochemical Behavior of p-Type Si(111) Covered by a Single Layer of Graphene or Hexagonal Boron Nitride

Two-dimensional (2D) materials may enable a general approach to the introduction of a dipole at a semiconductor surface as well as control over other properties of the double layer at a semiconductor/liquid interface. Vastly different properties can be found in the 2D materials currently studied due in part to the range of the distribution of density-of-states. In this work, the open-circuit voltage (V oc ) of p-Si–H, p-Si/Gr (graphene), and p-Si/h-BN (hexagonal boron nitride) in contact with a series of one-electron outer-sphere redox couples was investigated by macroscale measurements as well as by scanning electrochemical cell microscopy (SECCM). The band gaps of Gr and h-BN (0–5.97 eV) encompass the wide range of band gaps for 2D materials, so these interfaces (p-Si/Gr and p-Si/h-BN) serve as useful references to understand the behavior of 2D materials more generally. The value of Voc shifted with respect to the effective potential of the contacting solution, with slopes (ΔV oc /ΔE Eff ) of -0.27 and -0.38 for p-Si/Gr and p-Si/h-BN, respectively, indicating that band bending at the p-Si/h-BN and p-Si/Gr interfaces responds at least partially to changes in the electrochemical potential of the contacting liquid electrolyte. Additionally, SECCM is shown to be an effective method to interrogate the nanoscale photoelectrochemical behavior of an interface, showing little spatial variance over scales exceeding the grain size of the CVD-grown 2D materials in this work. The measurements demonstrated that the polycrystalline nature of the 2D materials had little effect on the results and confirmed that the macroscale measurements reflected the junction behavior at the nanoscale.

2D material↗
DOE OSTI2015

Using Discrete Event Simulation for Programming Model Exploration at Extreme-Scale: Macroscale Components for the Structural Simulation Toolkit (SST).

Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading framework allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Hybrid Bio-Based Composites: Enabling Cellulose Nanofiber (CNF) Incorporation into Composites via Macroscale Natural Fiber Carriers

Cellulose nanofibers (CNFs) have significant potential in composites as additives to improve mechanical properties, melt rheology, and more. However, agglomeration of CNFs is a key challenge in composite melt processing as obtaining nano-level dispersion of CNFs often requires cost- and energy-intensive processes (e.g., solvent exchange or freeze drying) due to the strong hornification tendencies of CNF. Herein, we avoid these challenges by using a natural fiber carrier method to integrate CNF into thermoplastic composites. Fibers are co-dried to create a hybrid fiber feedstock for compounding in which natural fibers are decorated with dispersed nanofibers. The hybridized fibers result in up to a 24% increase in tensile strength and up to a 35% increase in Young’s modulus compared to composites only containing natural fibers. The lignocellulosic nanofibers are found to outperform their purely cellulosic counterpart, which is theorized to be due to either an increased propensity for fibrillation of the lignocellulosic fibers or the increased hydrophobicity of the fibers due to the presence of lignin. Surface analysis of fiber feedstocks, via streaming potential measurements and dynamic light scattering (DLS), confirmed a significant change in the feedstock hydrophobicity before and after hybridization. While mild additions of CNF (1 wt.% on the macroscale fiber) do not impact the composite melt viscosity, the viscosity is found to increase at higher CNF loadings (5 wt.% on the macroscale fiber), indicating its utility as a rheology modifier. Lastly, use of these materials as novel feedstocks for medium-scale additive manufacturing in high-fidelity part production was demonstrated.

bio-based↗
DOE OSTI2023

Macroscale Fabrication of Lightweight and Strong Porous Carbon Foams through Template-Coating Pair Design

Manufacturing of low-density-high-strength carbon foams can benefit the construction, transportation, and packaging industries. One successful route to lightweight and mechanically strong carbon foams involves pyrolysis of polymeric architectures, which is inevitably accompanied by drastic volumetric shrinkage (usually >98%). As such, a challenge of these materials lies in maintaining bulk dimensions of building struts that span orders of magnitude difference in length scale from centimeters to nanometers. Here, this work demonstrates fabrication of macroscale low-density-high-strength carbon foams that feature exceptional dimensional stability through pyrolysis of robust template-coating pairs. The template serves as the architectural blueprint and contains strength-imparting properties (e.g., high node density and small strut dimensions); it is composed of a low char-yielding porous polystyrene backbone with a high carbonization-onset temperature. The coating serves to imprint and transcribe the template architecture into pyrolytic carbon; it is composed of a high char-yielding conjugated polymer with a relatively low carbonization-onset temperature. The designed carbonization mismatch enables structural inheritance, while the decomposition mismatch affords hollow struts, minimizing density. The carbons synthesized through this new framework exhibit remarkable dimensional stability (≈80% dimension retention; ≈50% volume retention) and some of the highest specific strengths (≈0.13 GPa g -1 cm 3 ) among reported carbon foams derived from porous polymer templates.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A New Global River Network Database for Macroscale Hydrologic modeling

Coarse resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical Dominant River Tracing (DRT) algorithm for automated extraction and spatial upscaling of basin flow directions and river networks using fine-scale hydrography inputs (e.g., flow direction, river networks, and flow accumulation). The DRT was initially applied using HYDRO1K baseline fine-scale hydrography inputs and the resulting upscaled global hydrography maps were produced at several spatial scales, and verified against other available regional and global datasets. New baseline fine-scale hydrography data from HydroSHEDS are now available for many regions and provide superior scale and quality relative to HYDRO1K. However, HydroSHEDS does not cover regions above 60°N. In this study, we applied the DRT algorithms using combined HydroSHEDS and HYDRO1K global fine-scale hydrography inputs, and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions in a consistent (WGS84) projection. The new upscaled river networks are internally consistent and congruent with the baseline fine-scale inputs. The DRT results preserve baseline fine-scale river networks independent of spatial scales, with consistency in river network, basin shape, basin area, river length, and basin internal drainage structure between upscaled and baseline fine-scale hydrography. These digital data are available online for public access (ftp://ftp.ntsg.umt.edu/pub/data/DRT/) and should facilitate improved regional to global scale hydrological simulations, including runoff routing and river discharge calculations.

macroscale hydrological modeling↗
DOE OSTI2015

Macroscale Transformation Optics Enabled by Photoelectrochemical Etching

Photoelectrochemical etching of silicon can be used to form lateral refractive index gradients for transformation optical devices. This technique allows the fabrication of macroscale devices with large refractive index gradients. Patterned porous layers can also be lifted from the substrate and transferred to other materials, creating more possibilities for novel devices.

36 MATERIALS SCIENCE↗