Volumetric lattice Boltzmann method for pore-scale mass diffusion-advection process in geopolymer porous structures
Not Available
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
SEARCH · Engineering Papers
Results for “diffusion processes”
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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Integrated three-dimensional characterization of reactive phase formation and coarsening during isothermal annealing of metastable Zn–3Mg–4Al eutectic
Microstructural instabilities associated with a metastable lamellar eutectic when exposed to an elevated temperature were analyzed in a Zn-3Mg-4Al alloy as a model system. X-ray diffraction and scanning electron microscopy showed that annealing at a temperature 43 K below the equilibrium eutectic temperature converted the metastable ternary MgZn 2 /η-Zn/β-ZnAl eutectic to a stable mixture of Mg 2 Zn 11 /η-Zn/α-Al. 3D EBSD suggested that supersaturation of η-Zn with Mg and Al eased difficulties in nucleation of Mg 2 Zn 11 and α-Al at the MgZn 2 /η-Zn phase interfaces. Quasi-in-situ X-ray nanotomography revealed that a reactive diffusion process prevailed in an early stage of annealing leading to rapid consumption of MgZn 2 for growth of Mg 2 Zn 11 and concomitant thinning and pinch-off of η-Zn lamellae. The reactive diffusion process also brought about significant and quantifiable changes in the topological characteristics of the η-Zn phase at remarkably shorter time scales compared to Rayleigh instability and Ostwald ripening mechanisms. Overall, the present results provide fresh insights on the short-term annealing effects on metastable eutectics, with relevance to structural evolution in additive manufacturing.
36 MATERIALS SCIENCE↗
Li-Ion Diffusion Correlations in LiAlGeO 4 : Quasielastic Neutron Scattering and Ab Initio Simulation
Here, we investigated the impact of Li stoichiometry and host flexibility on Li + diffusion processes in LiAlGeO 4 at the microscopic level using quasielastic neutron scattering (QENS) and ab initio molecular dynamics (AIMD) simulations. Using sufficiently long AIMD trajectories, we could simulate the observed QENS signal and identify the localized dynamics of Li in crystalline LiAlGeO 4 . Such information is vital to identify the bottleneck of diffusion processes and design materials for battery application. Our AIMD simulations in LiAlGeO 4 reveal that the Li + conductivity can be significantly improved by manipulating the Li stoichiometry and/or host flexibility via amorphization. We determined that excess Li stoichiometry enhances the Coulomb repulsion of neighboring Li sites and softens the host structure to enable faster Li + diffusion along the hexagonal c-axis. In the amorphous structure, random orientations of AlO 4 and GeO 4 polyhedral units create a wide distribution of intersite distances and significantly soften the host structure, greatly enhancing the Li + diffusion. The simulations are used to understand the nature of diffusion, especially the role of the host structure, the possible hopping pathways, and the diffusion behavior in various structures of LiAlGeO 4 .
localized dynamics↗
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties
Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.
42 ENGINEERING↗
Dynamic response of photorespiration in fluctuating light environments
Abstract Photorespiration is a dynamic process that is intimately linked to photosynthetic carbon assimilation. There is a growing interest in understanding carbon assimilation during dynamic conditions, but the role of photorespiration under such conditions is unclear. In this review, we discuss recent work relevant to the function of photorespiration under dynamic conditions, with a special focus on light transients. This work reveals that photorespiration is a fundamental component of the light induction of assimilation where variable diffusive processes limit CO2 exchange with the atmosphere. Additionally, metabolic interactions between photorespiration and the C3 cycle may help balance fluxes under dynamic light conditions. We further discuss how the energy demands of photorespiration present special challenges to energy balancing during dynamic conditions. We finish the review with an overview of why regulation of photorespiration may be important under dynamic conditions to maintain appropriate fluxes through metabolic pathways related to photorespiration such as nitrogen and one-carbon metabolism.
Plant Sciences↗
Atomic-scale in situ observation of electron beam and heat induced crystallization of Ge nanoparticles and transformation of Ag@Ge core-shell nanocrystals
Crystallization of amorphous materials by thermal annealing has been investigated for numerous applications in the fields of nanotechnology, such as thin-film transistors and thermoelectric devices. The phase transition and shape evolution of amorphous germanium (Ge) and Ag@Ge core–shell nanoparticles with average diameters of 10 and 12 nm, respectively, were investigated by high-energy electron beam irradiation and in situ heating within a transmission electron microscope. The transition of a single Ge amorphous nanoparticle to the crystalline diamond cubic structure at the atomic scale was clearly demonstrated. Depending on the heating temperature, a hollow Ge structure can be maintained or transformed into a solid Ge nanocrystal through a diffusive process during the amorphous to crystalline phase transition. Selected area diffraction patterns were obtained to confirm the crystallization process. In addition, the thermal stability of Ag@Ge core–shell nanoparticles with an average core of 7.4 and a 2.1 nm Ge shell was studied by applying the same beam conditions and temperatures. The results show that at a moderate temperature (e.g., 385 °C), the amorphous Ge shell can completely crystallize while maintaining the well-defined core–shell structure, while at a high temperature (e.g., 545 °C), the high thermal energy enables a freely diffusive process of both Ag and Ge atoms on the carbon support film and leads to transformation into a phase segregated Ag–Ge Janus nanoparticle with a clear interface between the Ag and Ge domains. In conclusion, this study provides a protocol as well as insight into the thermal stability and strain relief mechanism of complex nanostructures at the single nanoparticle level with atomic resolution.
36 MATERIALS SCIENCE↗
Deep potential generation scheme and simulation protocol for the Li 10 GeP 2 S 12 -type superionic conductors
We report solid-state electrolyte materials with superior lithium ionic conductivities are vital to the next-generation Li-ion batteries. Molecular dynamics could provide atomic scale information to understand the diffusion process of Li-ion in these superionic conductor materials. Here, we implement the deep potential generator to set up an efficient protocol to automatically generate interatomic potentials for Li 10 GeP 2 S 12 -type solid-state electrolyte materials (Li 10 GeP 2 S 12 , Li 10 SiP 2 S 12 , and Li 10 SnP 2 S 12 ). The reliability and accuracy of the fast interatomic potentials are validated. With the potentials, we extend the simulation of the diffusion process to a wide temperature range (300 K–1000 K) and systems with large size (~1000 atoms). Important technical aspects such as the statistical error and size effect are carefully investigated, and benchmark tests including the effect of density functional, thermal expansion, and configurational disorder are performed. The computed data that consider these factors agree well with the experimental results, and we find that the three structures show different behaviors with respect to configurational disorder. Our work paves the way for further research on computation screening of solid-state electrolyte materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ion Dynamics in Ionic-Liquid-Based Li-Ion Electrolytes Investigated by Neutron Scattering and Dielectric Spectroscopy
A detailed understanding of the diffusion mechanisms of ions in pure and doped ionic liquids remains an important aspect in the design of new ionic-liquid electrolytes for energy storage. Here, to gain more insight into the widely used imidazolium-based ionic liquids, the relationship between viscosity, ionic conductivity, diffusion coefficients, and reorientational dynamics in the ionic liquid 3-methyl-1-methylimidazolium bis(trifluoromethanesulfonyl)imide (DMIM-TFSI) with and without lithium bis(trifluoromethanesulfonyl)imide (Li-TFSI) was examined. The diffusion coefficients for the DMIM + cation and the role of ion aggregates were investigated by using the quasielastic neutron scattering (QENS) and neutron spin echo techniques. Two diffusion mechanisms are observed for the DMIM + cation with and without Li-TFSI, that is, translational and local. The data additionally suggest that Li + ion transport along with ion aggregates, known as the vehicle mechanism, may play a significant role in the ion diffusion process. These dielectric-spectroscopy investigations in a broad temperature and frequency range reveal a typical α–β-relaxation scenario. The α relaxation mirrors the glassy freezing of the dipolar ions, and the β relaxation exhibits the signatures of a Johari–Goldstein relaxation. In contrast to the translational mode detected by neutron scattering, arising from the decoupled faster motion of the DMIM + ions, the α relaxation is well coupled to the dc charge transport, that is, the average translational motion of all three ion species in the material. Finally, the local diffusion process detected by QENS is only weakly dependent on temperature and viscosity and can be ascribed to the typical fast dynamics of glass-forming liquids.
25 ENERGY STORAGE↗
Machine learning-based model predictive control of diffusion-reaction processes
Not Available
Dodhia, Aarsh↗
Comprehensive Model of Single Particle Pulverized Coal Combustion Extended to Oxy-Coal Conditions
Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive CFD simulations are valuable tools in evaluating and deploying oxy-fuel and other carbon capture technologies either as retrofit technologies or for new construction. But, accurate predictive simulations require physically realistic submodels with low computational requirements. In particular, comprehensive char oxidation and gasification models have been developed that describe multiple reaction and diffusion processes. Our work extends a comprehensive char conversion code (CCK), which treats surface oxidation and gasification reactions as well as processes such as film diffusion, pore diffusion, ash encapsulation, and annealing. In this work several submodels in the CCK code were updated with more realistic physics or otherwise extended to function in oxy-coal conditions. Improved submodels include the annealing model, the swelling model, the mode of burning parameter, and the kinetic model, as well as the addition of the chemical percolation devolatilization (CPD) model. We compare our results of the char combustion model to oxy-coal data, and further compared to parallel data sets near conventional conditions. A potential method to apply the detailed code in CFD work is given.
01 COAL, LIGNITE, AND PEAT↗
Vacancies and Vacancy-Mediated Self Diffusion in Cr 2 O 3 : A First-Principles Study
Charged and neutral vacancies and vacancy mediated self diffusion in alpha-Cr2O3 were investigated using first principles density functional theory (DFT) and periodic supercell formalism. The vacancy formation energies of charged defects were calculated using the electrostatic finite-size corrections to account for electrostatic interactions between supercells and the corrections for the bandgap underestimation in DFT. Calculations predict that neutral oxygen (O) vacancies are predominant in chromium (Cr)-rich conditions and Cr vacancies with -2 charge state are the dominant defects in O-rich conditions. The charge transition levels of both O and Cr vacancies are deep within the bandgap indicating the stability of these defects. Transport calculations indicate that vacancy mediated diffusion along the basal plane has lower energy barriers for both O and Cr ions. The most favorable vacancy mediated self diffusion processes correspond to the diffusion of Cr ion in 3+ charge state and O ion in 2- state, respectively. Our calculations reveal that Cr triple defects comprised of Cr in octahedral interstitial sites with two adjacent Cr vacancies along the c-axis have a lower formation energy compared to that of charged Cr vacancies. The formation of such triple defects facilitate Cr self diffusion along the c-axis.
Medasani, Bharat (ORCID:0000000220734162)↗
Spatiotemporal Observation of Quasi-Ballistic Transport of Electrons in Graphene
We report spatiotemporal observations of room-temperature quasi-ballistic electron transport in graphene, which is achieved by utilizing a four-layer van der Waals heterostructure to generate free charge carriers. The heterostructure is formed by sandwiching a MoS 2 and MoSe 2 heterobilayer between two graphene monolayers. Transient absorption measurements reveal that the electrons and holes separated by the type-II interface between MoS 2 and MoSe 2 can transfer to the two graphene layers, respectively. Transient absorption microscopy measurements, with high spatial and temporal resolution, reveal that while the holes in one graphene layer undergo a classical diffusion process with a large diffusion coefficient of 65 cm 2 s –1 and a charge mobility of 5000 cm 2 V –1 s –1 , the electrons in the other graphene layer exhibit a quasi-ballistic transport feature, with a ballistic transport time of 20 ps and a speed of 22 km s –1 , respectively. The different in-plane transport properties confirm that electrons and holes move independently of each other as charge carriers. Furthermore, the optical generation of ballistic charge carriers suggests potential applications for such van der Waals heterostructures as optoelectronic materials.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Highly efficient parallel grand canonical simulations of interstitial-driven diffusion-deformation processes
Not provided.
Materials Science↗
Entanglement and dynamics of diffusion-annihilation processes with Majorana defects
Not Available
Nahum, Adam↗
Processes of diffusion in a limited ensemble of charged particles in a static magnetic field
The dynamics of a limited ensemble of charged particles in a spatially uniform static magnetic field has been studied analytically and numerically. Calculations have been performed for particles with various masses and charges in a wide range of the parameters of the systems under study. It has been shown that the transverse diffusion coefficient in an ensemble of particles in the magnetic field for weakly nonideal systems is described by the Townsend formula. Analytical estimates have been proposed for the analysis of the effective diffusion radius of the ensemble of particles owing to their thermal motion. The proposed relations have been tested by the numerical simulation of the problem.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)
In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.
03 NATURAL GAS↗
Probing the Structure and Dynamics of Fluid Mixtures in Porous Materials Through Ultrafast Vibrational Spectro-Microscopy and Many-Body Molecular Dynamics
This research program focused on the characterization of both molecular structure and dynamics of aqueous solutions in various metal-organic frameworks (MOFs) and organic polymers that have recently been proposed for applications in water treatment technologies. This was accomplished by integrating ultrafast vibrational spectroscopy and microscopy, which are sensitive to local environments, molecular orientation, and dynamical couplings, with many-body molecular dynamics (MB-MD) simulations, which enable realistic modeling of aqueous systems and porous materials under different thermodynamic conditions. Our studies allowed for identifying the physical mechanisms and characterizing the underlying molecular interactions between water and host materials that determine the adsorption and transport processes of water in various MOFs and β-cyclodextrin polymers – prototypical examples of porous materials and polymers, that have recently been proposed for technological applications in water purification. By combining bulk- and surface-sensitive, spatially resolved ultrafast vibrational spectroscopy with MB-MD simulations, it was possible to gain broad insight into the structure and mobility of water under heterogeneous confinement at various length scales. In particular, measurements of surface- and bulk-sensitive vibrational spectra at single crystal level, integrated with MB-MD simulations were used to characterize domain-specific, structure–binding affinity relationships. Besides providing specific information about the behavior of aqueous solutions in prototypical MOFs and organic polymers for potential applications in water treatment technologies, our studies also provided fundamental insights into the properties of aqueous solutions in confined heterogeneous environments, which have broad implications in many areas, ranging from heterogeneous catalysis to oil recovery, ion transport processes, and reaction-diffusion processes in crowded systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Surface Self-Diffusion Induced Sintering of Nanoparticles
Despite the critical role of sintering phenomena in constraining the long-term durability of nanosized particles, a clear understanding of nanoparticle sintering has remained elusive due to the challenges in atomically tracking the neck initiation and discerning different mechanisms. Through the integration of in situ transmission electron microscopy and atomistic modeling, this study uncovers the atomic dynamics governing the neck initiation of Pt–Fe nanoparticles via a surface self-diffusion process, allowing for coalescence without significant particle movement. Real-time imaging reveals that thermally activated surface morphology changes in individual nanoparticles induce significant surface self-diffusion. Further, the kinetic entrapment of self-diffusing atoms in the gaps between closely spaced nanoparticles leads to the nucleation and growth of atomic layers for neck formation. This surface self-diffusion-driven sintering process is activated at a relatively lower temperature compared to the classic Ostwald ripening and particle migration and coalescence processes. The fundamental insights have practical implications for manipulating the morphology, size distribution, and stability of nanostructures by leveraging surface self-diffusion processes.
36 MATERIALS SCIENCE↗