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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 OSTI2017

Systematic parameter inference in stochastic mesoscopic modeling

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Silk Flexible Electronics: From Bombyx mori Silk Ag Nanoclusters Hybrid Materials to Mesoscopic Memristors and Synaptic Emulators

Functionalization of flexible materials based on mesoscopic reconstruction is a key strategy in fabricating biocompatible flexible electronics. This work is to acquire new mesoscopic bioelectronic hybrid materials of silk fibroin (SF)-Ag nanoclusters (AgNCs@BSA; BSA: bovine serum albumin), which enhance significantly the performance of silk memristors. It is to build AgNCs@BSA into SF mesoscopic networks by templated ß-crystallization. Atomic force microscopy potential probing indicates that AgNCs@BSA serve as electronic potential wells that change completely the transport behavior of charge particles within the SF films. This leads to significant enhancement in the switching speed (˜10 ns), very good switching stability, extremely low set/reset voltages (0.3/-0.18 V) of SF meso-hybrid memristors, compared with the original and other organic memristors, and displays unique synapse characteristics and the capability of synapse learning. Classical density functional theory Poisson–Nernst–Planck simulations indicate that the enhanced performance is subject to the low potential paths interconnecting the AgNCs@BSA, which guide charges' transport (Ag+) and deposition in SF films.

Shi, Chenyang↗
DOE OSTI2018

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number RE = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

Computer Science↗
DOE OSTI2018

Use of Mesoscopic Host Matrix to Induce Ferrimagnetism in Antiferromagnetic Spinel Oxide [Use of Mesoscopic Host Matrix for Ferrimagnetism in Antiferromagnetic Spinel Oxide]

Despite the advances in the methods for fabricating nanoscale materials, critical issues remain, such as the difficulties encountered in anchoring, and the deterioration in their stability after integration with other components. These issues need to be addressed to further increase the scope of their applicability. In this study, using epitaxial mesoscopic host matrices, materials are spatially confined at the nanoscale, and are supported, anchored, and stabilized. They also exhibit properties distinct from the bulk counterparts proving their high quality nanoscale nature. ZnFe 2 O 4 and SrTiO 3 are used as the model confined material and host matrix, respectively. The ZnFe 2 O 4 phases are spatially confined by the SrTiO 3 mesoscopic matrix and have strongly enhanced ferrimagnetic properties as compared to bulk and plain thin films of ZnFe 2 O 4 , with a Curie temperature of ≈500 K. The results of a series of control experiments and characterization measurements indicate that cationic inversion, which originates from the high interface–to–volume ratio of the ZnFe 2 O 4 phase in the ZnFe 2 O 4 –SrTiO 3 nanocomposite film, is responsible for the magnetization enhancement. An exchange bias is observed, owing to the coexistence of ferrimagnetic and antiferromagnetic regions in the confined ZnFe 2 O 4 phase. In conclusion, the magnetic properties are dependent on the ZnFe 2 O 4 crystallite size, which can be controlled by the growth conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interlayer Exciton Polarons in Mesoscopic V 2 O 5 for Broadband Optoelectronic Synapses

Persistent photoconductivity and optoelectronic synaptic behavior are demonstrated in solution-processed mesoscopic α-phase vanadium pentoxide (V 2 O 5 ) thin films. First-principles simulations coupled with the two-site Holstein polaron hopping model show that vacancies at the terminal oxygen position lead to long recombination times because photoexcited electrons and holes reside on different layers separated by the van der Waals gap, forming a weakly coupled interlayer exciton polaron. Mid-gap polaronic states also significantly broaden the photoresponse of the films to span across visible and infrared wavelengths. By controlling the amplitude/intensity, duration, and/or number of optical pulses, tunable optoelectronic memory functions, such as short-term and long-term plasticity, are experimentally established in V 2 O 5 -based optoelectronic synapses. Furthermore, device fabrication was extended to mechanically flexible ultrathin glass substrates. Flexible optoelectronic synapses maintained high performance after 150 bending cycles.

Phan, Thanh Luan [National Renewable Energy Labora↗
DOE OSTI2017

Mesoscopic Adaptive Resolution Scheme toward Understanding of Interactions between Sickle Cell Fibers

Understanding of intracellular polymerization of sickle hemoglobin (HbS) and subsequent interaction with the membrane of a red blood cell (RBC) is important to predict the altered morphologies and mechanical properties of sickle RBCs in sickle cell anemia. However, modeling the integrated processes of HbS nucleation, polymerization, HbS fiber interaction, and subsequent distortion of RBCs is challenging as they occur at multispatial scales, ranging from nanometers to micrometers. To make progress toward simulating the integrated processes, we propose a hybrid HbS fiber model, which couples fine-grained and coarse-grained HbS fiber models through a mesoscopic adaptive resolution scheme (MARS). To this end, we apply a microscopic model to capture the dynamic process of polymerization of HbS fibers, while maintaining the mechanical properties of polymerized HbS fibers by the mesoscopic model, thus providing a means of bridging the subcellular and cellular phenomena in sickle cell disease. At the subcellular level, this model can simulate HbS polymerization with preexisting HbS nuclei. At the cellular level, if combined with RBC models, the generated HbS fibers could be applied to study the morphologies and membrane stiffening of sickle RBCs. One important feature of the MARS is that it can be easily employed in other particle-based multiscale simulations where a dynamic coarse-graining and force-blending method is required. As demonstrations, we first apply the hybrid HbS fiber model to simulate the interactions of two growing fibers and find that their final configurations depend on the orientation and interaction distance between two fibers, in good agreement with experimental observations. We also model the formation of fiber bundles and domains so that we explore the mechanism that causes fiber branching.

Biophysics↗
DOE OSTI2020

Mesoscopic analyses of the impact of morphology and operating conditions on the transport resistances in a proton-exchange-membrane fuel-cell catalyst layer

Exploring the origins of local transport resistance and characterizing the oxygen transport resistances in the catalyst layer (RCL) are critical for cost reduction. In this paper, a comprehensive mesoscopic model for simulating coupled transport processes of oxygen and water vapor for different structural parameters under different operating conditions in reconstructed microstructures is proposed. The local transport resistance is calculated after achieving the limiting current density and the effective diffusivity of oxygen. The results demonstrate that RCL increases greatly with decreasing platinum loading (LPt) and the transport resistances in other components of the cell dominate for high-loadings. Both the reduced oxygen permeation coefficient in the ionomer thin-film and the adsorption resistance account for the origins of local transport resistance. The local transport resistance increases with the bare carbon ratio for a constant LPt and Pt/C ratio due to the decreased effective ionomer surface, and increases with the I/C ratio due to the increased ionomer thickness and decreased Knudsen diffusivity. Due to the presence of liquid water, a slight decrease followed by an increase of the local transport resistance versus relative humidity is obtained. The contribution of ionomer thin-films to RCL is more sensitive to liquid saturation compared with that of pores. This journal is

Mu, YT↗
DOE OSTI2015

Coupling a nano-particle with isothermal fluctuating hydrodynamics: Coarse-graining from microscopic to mesoscopic dynamics

We derive a coarse-grained description of the dynamics of a nanoparticle immersed in an isothermal simple fluid by performing a systematic coarse graining of the underlying microscopic dynamics. As coarse-grained or relevant variables, we select the position of the nanoparticle and the total mass and momentum density field of the fluid, which are locally conserved slow variables because they are defined to include the contribution of the nanoparticle. The theory of coarse graining based on the Zwanzing projection operator leads us to a system of stochastic ordinary differential equations that are closed in the relevant variables. We demonstrate that our discrete coarse-grained equations are consistent with a Petrov-Galerkin finite-element discretization of a system of formal stochastic partial differential equations which resemble previously used phenomenological models based on fluctuating hydrodynamics. Key to this connection between our “bottom-up” and previous “top-down” approaches is the use of the same dual orthogonal set of linear basis functions familiar from finite element methods (FEMs), both as a way to coarse-grain the microscopic degrees of freedom and as a way to discretize the equations of fluctuating hydrodynamics. Another key ingredient is the use of a “linear for spiky” weak approximation which replaces microscopic “fields” with a linear FE interpolant inside expectation values. For the irreversible or dissipative dynamics, we approximate the constrained Green-Kubo expressions for the dissipation coefficients with their equilibrium averages. Under suitable approximations, we obtain closed approximations of the coarse-grained dynamics in a manner which gives them a clear physical interpretation and provides explicit microscopic expressions for all of the coefficients appearing in the closure. Our work leads to a model for dilute nanocolloidal suspensions that can be simulated effectively using feasibly short molecular dynamics simulations as input to a FEM fluctuating hydrodynamic solver.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Smoothed dissipative particle dynamics model for mesoscopic multiphase flows in the presence of thermal fluctuations

Thermal fluctuations cause perturbations of fluid-fluid interfaces and highly nonlinear hydrodynamics in multiphase flows. In this work, we develop a novel multiphase smoothed dissipative particle dynamics model. This model accounts for both bulk hydrodynamics and interfacial fluctuations. Interfacial surface tension is modeled by imposing a pairwise force between SDPD particles. We show that the relationship between the model parameters and surface tension, previously derived under the assumption of zero thermal fluctuation, is accurate for fluid systems at low temperature but overestimates the surface tension for intermediate and large thermal fluctuations. To analyze the effect of thermal fluctuations on surface tension, we construct a coarse-grained Euler lattice model based on the mean field theory and derive a semi-analytical formula to directly relate the surface tension to model parameters for a wide range of temperatures and model resolutions. We demonstrate that the present method correctly models the dynamic processes, such as bubble coalescence and capillary spectra across the interface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Exploring Mesoscopic Physics of Vacancy-Ordered Systems through Atomic Scale Observations of Topological Defects

Vacancy-ordered transition metal oxides have multiple similarities to classical ferroic systems including ferroelectrics and ferroelastics. Bulk phase diagrams make the expansion coefficients for corresponding Ginzburg-Landau type free energies readily accessible. We demonstrate that the gradient and interfacial terms can quantitatively be determined from the atomically-resolved scanning transmission electron microscopy data of the topological defects and interfaces in model lanthanum-strontium cobaltite. Knowing this, the interplay between ordering, chemical composition, and mechanical effects at domain walls, interfaces and structural defects can be analyzed.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Degradation science: Mesoscopic evolution and temporal analytics of photovoltaic energy materials

Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance of material ensembles. Mesoscopic evolution modeling is shown to encompass the heterogeneity of these materials and systems, and enables the discrimination of the fast dynamics of their functional use and the slow and/or rare events of their degradation. As a result, we delineate paths forward for degradation science.

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

DFT-based mesoscopic interactions of N adatoms on Cu(100)

The first-principles density functional theory (DFT) method is used to directly calculate the interactions of N atoms of various configurations on Cu(100) surfaces. This allows us to derive a mesoscopic substratemediated interaction model. We find that, for these Cu(100)-supported two-dimensional N clusters, oscillating substrate-mediated interactions obtained from an elastic eigenvector approach including a mesoscopic interacting range (called the mesoscopic model) have reasonable agreement with the DFT results. The DFT periodic boundary conditions are properly mapped into the mesoscopic model. The model is used to analyze the energies of c(2×2) square islands independent of their sizes. Previous experimental studies have shown that, in the low coverage region, N atoms agglomerate to isolated square islands of about 5 nm × 5 nm in size with a c(2×2) structure. With increasing coverage, those islands form regular patterns but do not touch below about 0.4 monolayers. From previous experiments and calculations, the square island pattern shows significant elastic effects which are now confirmed.

74 ATOMIC AND MOLECULAR PHYSICS↗