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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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108 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Thermodynamic consistency and fluctuations in mesoscopic stochastic simulations of reactive gas mixtures

It is essential that mesoscopic simulations of reactive systems reproduce the correct statistical distributions at thermodynamic equilibrium. By considering a compressible fluctuating hydrodynamics (FHD) simulation method of ideal gas mixtures undergoing reversible reactions described by the chemical Langevin equations, we show that thermodynamic consistency in reaction rates and the use of instantaneous temperatures for the evaluation of reaction rates is required for fluctuations for the overall system to be correct. We then formulate the required properties of a thermodynamically consistent reaction (TCR) model. As noted in the literature, while reactions are often discussed in terms of forward and reverse rates, these rates should not be modeled independently because they must be compatible with thermodynamic equilibrium for the system. Using a simple TCR model where each chemical species has constant heat capacity, we derive the explicit condition that the forward and reverse reaction rate constants must satisfy in order for the system to be thermodynamically consistent. We perform equilibrium and non-equilibrium simulations of ideal gas mixtures undergoing a reversible dimerization reaction to measure the fluctuational behavior of the system numerically. We confirm that FHD simulations with the TCR model give the correct static structure factor of equilibrium fluctuations. For the statistically steady simulation of a gas mixture between two isothermal walls with different temperatures, we show using the TCR model that the temperature variance agrees with the corresponding thermodynamic-equilibrium temperature variance in the interior of the system, whereas noticeable deviations are present in regions near walls, where chemistry is far from equilibrium.

Polimeno, Matteo [University of California, Merced↗
DOE OSTI2020

Simulating transient heat transfer in graphene at finite Knudsen number via the Boltzmann transport equation and molecular dynamics

The phonon Boltzmann transport equation (BTE) with the relaxation time approximation (RTA) scattering model is used to calculate transient temperature profiles in graphene, and the results are compared to analogous molecular dynamics (MD) simulations. For the BTE calculations, the phonon dispersion relation and frequency-dependent scattering rates are obtained from a combination of MD data and semi-empirical power-law expressions for the normal and Umklapp phonon lifetimes. The dimensions and initial temperature conditions of graphene are varied to study the size and temperature dependence of thermal transport physics at the mesoscopic scale. Good quantitative agreement to within 5% is found between the BTE and MD results, over a wide range of temperatures and lengthscales of the temperature variation in the graphene sheet. Small differences are attributed to the inaccuracy of the RTA as applied to graphene, and to neglecting four-phonon scattering in the BTE simulations. The present results may further understanding in applications such as the transient heating of nanoelectronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Impact of acid site speciation and spatial gradients on zeolite catalysis

This mini-review provides an overview of the current state of acid site control in zeolite catalysts, including methods of synthesis, advanced characterization, and measured effects of acid properties (speciation, concentration, proximity, siting, and spatial distribution) on a variety of commerciallyrelevant reactions. The diversity of aluminum species is described with respect to their location at specific sites in zeolite crystals as well as mesoscopic gradients in elemental composition that give rise to zoned or core-shell architectures. Challenges in the identification of acid siting are highlighted within the context of trial-and-error synthesis methods for a range of aluminosilicate frameworks, which hinder a priori design of catalysts, and limitations in techniques to suitably characterize active sites. Emphasis is also placed on knowledge gaps in zeolite catalysis wherein broad development of structure-performance relationships relies on future advancement of synthesis and analytical methods in parallel with atomistic modeling.

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

Multi-scale computer-aided design and photo-controlled macromolecular synthesis boosting uranium harvesting from seawater

By integrating multi-scale computational simulation with photo-regulated macromolecular synthesis, this study presents a new paradigm for smart design while customizing polymeric adsorbents for uranium harvesting from seawater. A dissipative particle dynamics (DPD) approach, combined with a molecular dynamics (MD) study, is performed to simulate the conformational dynamics and adsorption process of a model uranium grabber, i.e., PAO m -b-PPEGMA n , suggesting that the maximum adsorption capacity with atomic economy can be achieved with a preferred block ratio of 0.18. The designed polymers are synthesized using the PET-RAFT polymerization in a microfluidic platform, exhibiting a record high adsorption capacity of uranium (11.4 ± 1.2 mg/g) in real seawater within 28 days. This study offers an integrated perspective to quantitatively assess adsorption phenomena of polymers, bridging metal-ligand interactions at the molecular level with their spatial conformations at the mesoscopic level. The established protocol is generally adaptable for target-oriented development of more advanced polymers for broadened applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Self-equilibrated backstresses induce compensation between hardening and softening: Micromechanical and microstructural features

For crystal plasticity formulation neglecting the strain gradients at the dislocation scale, backstresses are necessary to satisfy the mesoscopic stress equilibrium and strain compatibility requirements. Backstresses in a material point and those between neighboring points are treated separately. Physically backstresses can dynamically induce either hardening or softening effects to adjust the dislocation hardening of slip systems, whereas the sum of the stresses resulting in backstresses in the representative volume element (RVE) is zero. Backstress hardening suppresses certain slip activities, while backstress softening triggers excess dislocations. A two-phase brass is studied. Backstresses make the hard phase deform smaller and the soft phase deform more than those without employing backstresses in a model. In the former, more homogeneous lattice strain and higher yield stress are obtained. Backstress has limited effects on the evolution of the critical resolved shear stress and crystallographic texture. Furthermore, it is a major cause of the banded structures featuring sharp crystallographic contrasts which are not parallel to the slip planes. Tests indicate that backstress induces a serrated behavior at the early stages of deformation and induces the geometrically necessary bands (GNBs), which are parallel to the macroscopic axes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Programming Function via Soft Materials (PFvSM) (Final Report)

The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication

36 MATERIALS SCIENCE↗
DOE OSTI2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switching and phase transition mechanisms. However, identification of these mechanisms from observational data sets has remained a problem due to a large variety of possible configurations, many of which are degenerate. Here, an approach based on a combination of deep learning-based semantic segmentation, rotationally invariant variational autoencoder (VAE), and non-negative matrix factorization to enable learning of a latent space representation of the data with multiple real-space rotationally equivalent variants mapped to the same latent space descriptors is introduced. By varying the size of training sub-images in the VAE, the degree of complexity in the structural descriptors is tuned from simple domain wall detection to the identification of switching pathways. Importantly, this yields a powerful tool for the exploration of the dynamic data in mesoscopic electron, scanning probe, optical, and chemical imaging. Moreover, this work adds to the growing body of knowledge of incorporating physical constraints into the machine and deep-learning methods to improve learned descriptors of physical phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Soft matter roadmap

Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts.

36 MATERIALS SCIENCE↗
DOE OSTI2019

On the implicit immersed boundary method in coupled discrete element and lattice Boltzmann method

The coupled discrete element method and lattice Boltzmann method (DEMLBM) has increasingly drawn attention of researchers in geomechanics due to its mesoscopic nature since 2000. Immersed boundary method (IBM) and immersed moving boundary (IMB) are two popular schemes for coupling fluid particle in DEMLBM. This work aims at coupling DEM and LBM using the latest IBM algorithm and investigating its accuracy, computational efficiency, and applicability. Two benchmark tests, interstitial fluid flow in an ideal packing and single particle sedimentation in viscous fluid, are carried out to demonstrate the accuracy of IBM through semi-empirical Ergun equation, finite element method (FEM), and IMB. Then, simulations of particle migration with relatively large velocity in Poiseuille flow are utilized to address limitations of IBM in DEMLBM modeling. In addition, advantages and deficiencies of IBM are discussed and compared with IMB. It is found that the accuracy of IBM can be only guaranteed when sufficient boundary points are used and it is not suitable for geomechanical problems involving large fluid or particle velocity.

58 GEOSCIENCES↗
DOE OSTI2022

SuperScreen: An open-source package for simulating the magnetic response of two-dimensional superconducting devices

Quantitative understanding of the spatial distribution of magnetic fields and Meissner screening currents in two-dimensional (2D) superconductors and mesoscopic thin film superconducting devices is critical to interpreting the results of magnetic measurements of such systems. Here, we introduce SuperScreen, an open-source Python package for simulating the response of 2D superconductors to trapped flux and applied time-independent or quasi-DC magnetic fields for any value of the effective magnetic penetration depth, Λ. Given an applied magnetic field, SuperScreen solves the 2D London equation using an efficient matrix inversion method to obtain the Meissner currents and magnetic fields in and around structures composed of one or more superconducting thin films of arbitrary geometry. Further, SuperScreen can be used to model screening effects and calculate self- and mutual-inductance in thin film superconducting devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

SuperScreen: An open-source package for simulating the magnetic response of two-dimensional superconducting devices

Quantitative understanding of the spatial distribution of magnetic fields and Meissner screening currents in two-dimensional (2D) superconductors and mesoscopic thin film superconducting devices is critical to interpreting the results of magnetic measurements of such systems. Here, we introduce SuperScreen, an open-source Python package for simulating the response of 2D superconductors to trapped flux and applied time-independent or quasi-DC magnetic fields for any value of the effective magnetic penetration depth, Λ. Given an applied magnetic field, SuperScreen solves the 2D London equation using an efficient matrix inversion method to obtain the Meissner currents and magnetic fields in and around structures composed of one or more superconducting thin films of arbitrary geometry with spatially nonuniform magnetic penetration depth. SuperScreen can be used to model screening effects and calculate self- and mutual-inductance in superconducting devices, and simulate the magnetic response of inhomogeneous 2D superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Viscous dissipation in a gas of one-dimensional fermions with generic dispersion

A well-known feature of the classical monoatomic gas is that its bulk viscosity is strongly suppressed because the single-particle dispersion is quadratic. On the other hand, in condensed matter systems the effective single -particle dispersion is altered by lattice effects and interactions. In this work, we study the bulk viscosity of one-dimensional Fermi gases with generic energy-momentum dispersion relations. As an application, viscous dissipation arising from lattice effects is analyzed for the tight-binding model. In addition, we investigate how weak interactions affect the bulk viscosity. Finally, we discuss viscous dissipation in the regime in which the Fermi gas is not fully equilibrated, as can occur when the system is driven at frequencies that exceed the rate of fermion backscattering. In this case, the Fermi gas is described by three bulk viscosities, which we obtain for a generic single-particle dispersion.

1-dimensional systems↗
DOE OSTI2025

Many-body interference in kagome crystals

When electrons in metals act collectively, they enable emergent phenomena and electronic functionalities that transcend the behaviour of individual particles. Coherent collective charge motion has so far been observed primarily in superconductors, in which it arises with the formation of Cooper pairs. Here we report experimental evidence for coherent charge transport in the normal state of the kagome metal CsV 3 Sb 5 , indicative of a distinct collective electronic state. The signature is a set of magnetoresistance oscillations in mesoscopic crystalline pillars under in-plane magnetic fields, with a periodicity determined by the number of magnetic flux quanta h/e threading between adjacent kagome layers—effectively forming an interlayer Aharonov–Bohm interferometer. The cooperative nature of this phenomenon is evidenced by a non-analytic angular dependence characterized by abrupt transitions between discrete oscillation frequencies and its persistence over length scales that exceed the single-particle mean free path. Notably, the oscillation amplitude matches other anomalous electronic responses reported in CsV 3 Sb 5 , pointing to an underlying mechanism that establishes intrinsic coherence. These findings shed new light on the debated nature of correlated order in kagome metals and establish CsV 3 Sb 5 as a platform for realizing long-range coherent charge transport in the absence of superconductivity—opening new directions for coherence in correlated electron systems beyond conventional models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Elucidating the formation mechanisms of zeolites using data-driven modelling and in-situ characterization

Zeolites are the main solid catalysts used by the chemical industry. The use of zeolites in separations and as shape selective catalysts requires control of the width and connectivity of their pores. 235 distinct zeolite frameworks have been synthesized to date, of over 2 million that have been proposed. Recent work indicates that the limitation is in large part kinetic: new synthetic pathways are required to access new zeolites. Organic cations are used to direct the synthesis towards specific zeolites. However, the molecular mechanisms by which cations direct the nucleation towards specific zeolites is not known. Elucidating these mechanisms is key to realize new zeolites for catalysis and separations, and is the focus of this project. This project developed and implemented a synergistic, data-driven computational and experimental approach to resolve the molecular pathways of nucleation, growth, and polymorph selection of zeolites and the role of organic cations in directing their formation. The project developed computationally efficient and accurate models for the study of the nucleation and growth of pure silica zeolites in molecular simulations, using machine learning with data from experiments. Simulations with these models were integrated with scanning tunneling electron microscopy, computer vision, and deep learning to unveil the molecular pathways of formation of a zeolite. Of particular interest in this project was to elucidate the role of amorphous precursors in the nucleation of the zeolite. Previous experiments indicate that zeolites are born within non-crystalline aggregates in which the silicates and organic cations have local and medium range order similar to that of the zeolite. The organic cations that direct the formation of zeolites and those that direct the formation of ordered mesoporous silicas are similar. We hypothesized that the frustrated attraction that for large organic cations leads to the formation of stable mesophases that direct the synthesis of mesoporous silicas, could promote the formation of metastable mesophases that can assist in the nucleation and polymorph selection of zeolites. The simulations resolved how structure directing agents build crystalline order and showed that mesoscopic pre-ordering occurs is not required to facilitate the nucleation of zeolites, because the synthesis occurs at high driving forces, where the barriers for nucleation are negligible. This project unveiled that polymorph selection in zeolite synthesis occurs after nucleation, opening a distinct area of control through the kinetics of growth and not through nucleation barriers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Memory and rejuvenation in glassy systems

Here, the memory effect in a single crystal spin glass (Cu 0.92 Mn 0.08 ) has been measured using 1 Hz ac susceptibility measurements over a reduced temperature range of 0.4 - 0.7 T g and a model of the memory effect has been developed. A double-waiting-time protocol is carried out where the spin glass is first allowed to age at a temperature below T g , T w$_{1}$ , followed by a second aging 4 K lower, T w$_{2}$ . The 4 K separation is sufficient to ensure rejuvenation has occurred. The model is based on calculating overlaps between the growth of the correlation lengths at the two temperatures. It accounts for the absolute magnitude of the memory effect as a function of both waiting times and temperatures. The data can be explained by the memory loss being a function of the relative change in the correlated volume at the first waiting temperature due to growth in the correlations at the second waiting temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach

Abstract Although multiple oxide-based solid electrolyte materials with intrinsically high ionic conductivities have emerged, practical processing and synthesis routes introduce grain boundaries and other interfaces that can perturb primary conduction channels. To directly probe these effects, we demonstrate an efficient and general mesoscopic computational method capable of predicting effective ionic conductivity through a complex polycrystalline oxide-based solid electrolyte microstructure without relying on simplified equivalent circuit description. We parameterize the framework for Li 7- x La 3 Zr 2 O 12 (LLZO) garnet solid electrolyte by combining synthetic microstructures from phase-field simulations with diffusivities from molecular dynamics simulations of ordered and disordered systems. Systematically designed simulations reveal an interdependence between atomistic and mesoscopic microstructural impacts on the effective ionic conductivity of polycrystalline LLZO, quantified by newly defined metrics that characterize the complex ionic transport mechanism. Our results provide fundamental understanding of the physical origins of the reported variability in ionic conductivities based on an extensive analysis of literature data, while simultaneously outlining practical design guidance for achieving desired ionic transport properties based on conditions for which sensitivity to microstructural features is highest. Additional implications of our results are discussed, including a possible connection between ion conduction behavior and dendrite formation.

25 ENERGY STORAGE↗
DOE OSTI2022

Staircase formation by resonant and non-resonant transport of potential vorticity

The E × B staircase is a quasi-periodic pattern of pressure profile corrugations. In this work, we present a new mechanism for E × B staircase formation that involves resonant transport versus non-resonant transport. We start from a potential vorticity evolution system and use quasi-linear theory, a model dispersion relation, and a bi-Lorentzian spectrum approximation, to construct the relation between the fluxes and the profiles. With these fluxes, we close the profile evolution equations and the extended turbulence intensity evolution equation, which together constitute a turbulence-profile evolution system. In this system, the Doppler effect from the E × B mean flow can cause resonance between trapped ion precession motion and the trapped ion mode, which drives a resonant transport contribution to the fluxes. The profiles will be flattened where the resonant transport is switched on. In contrast, for the regions of non-resonant transport, profiles are steeper. A quasi-periodic pattern of profile corrugation (the E × B staircase) spontaneously emerges in this system, which is the two states mentioned above, arranged as alternating layers in space. The feedback processes during the staircase pattern formation are identified. An estimate of the critical value of the boundary heat flux is obtained, above which the staircase formation will be triggered. An estimate scaling of the step size in the staircase pattern is obtained. The resonant turbulent transport is also a mechanism for collisionless saturation of zonal flow. Furthermore, this work is related to internal transport barrier formation and suggests some new scenarios, such as an enhanced confined L mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗