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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molecular Dynamics Study of the Effect of Grafting Density on Ion Diffusivity in a MARTINI Coarse-Grained Strong Polyelectrolyte Brush

Because surface-grafted polyelectrolyte brushes (PEBs) are responsive to external stimuli, such as electric fields and ionic strength, PEBs are attractive for applications ranging from drug delivery to separation technologies. Essential to PEB utilization is understanding how critical parameters like grafting density (σ) impact the PEB structure and the dynamics of the PEB and counterions. To study the effect of σ on PEB and the counterion structure and dynamics, we fine-tune a coarse-grained model that retains the chemical specificity of a strong polyelectrolyte, poly[(2-(methacryloyloxy)ethyl) trimethylammonium chloride] (PMETAC), using the MARTINI force field. Using “salt-free” conditions where the counterion concentration balances the charge on the brush, we build coarse-grained (CG) molecular dynamics simulations for MARTINI PMETAC brushes (N = 150 monomers; M W = 31.2 kg/mol) at experimentally relevant values of σ = 0.05, 0.10, 0.20, and 0.40 chains/nm 2 . Using 5 μs simulations, we investigate the effects of grafting density on the PEB structure, ion dissociation dynamics, polymer mobility, and counterion diffusivity. Results show that competition between electrostatic interactions, steric hindrance, and polymer mobility controls counterion diffusivity. Finally, the interplay of these factors leads to diffusivity that depends non-monotonically on σ, with counterion diffusivity peaking at an intermediate σ = 0.10 chains/nm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Isotopic Substitution Reveals the Importance of Aluminate Diffusion Dynamics in Gibbsite (Al(OH) 3 ) Crystallization from Alkaline Aqueous Solution

Understanding molecular-scale factors governing the precipitation of aluminum hydroxides, such as gibbsite, under alkaline conditions is important for the formation of laterite deposits, as well as aluminum processing. However, mechanisms enabling tetrahedral aluminate ions to assemble into octahedral sites of the gibbsite lattice remain unclear. Formation of oligomeric complexes has been hypothesized as a critical intermediate step. Here, we report a study of gibbsite solubility in highly alkaline solutions using deuterium substitution to probe equilibrium and kinetic factors that could affect oligomeric intermediate formation, including the reactivity and the diffusivity of aluminate ions. When substituting sodium hydroxide with sodium deuteroxide, solution analysis shows a nearly 40% and 50% increase in gibbsite solubility in 2.4 and 3.3 mol·kg –1 total sodium solutions, respectively. Raman spectroscopy indicated that monomeric aluminate ions are the predominant species in solution irrespective of deuteration. However, both 27 Al and 23 Na nuclear magnetic resonance (NMR) spectroscopy revealed significant differences in chemical shifts in deuterated solutions, and analysis of 1 H, 23 Na, and 27 Al diffusion coefficients with pulsed-field gradient, stimulated echo NMR spectroscopy shows a decrease in ion diffusivity with increasing total deuterium in solution, consistent with the notion of increasing strength in the hydrogen/deuterium bonding network. In conclusion, because the relative change in 1 H diffusion coefficients are commensurate with the difference in apparent solubility constants, there is evidence for an oligomeric intermediate whose steady-state concentration is maintained by the collision frequency of aluminate ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Spatially Mapping the CO 2 Alkaline Sorbent Diffuse Microenvironment Using Operando Raman Spectroscopy

When designing a chemical process, the local balance of transport and kinetics, collectively referred to as the diffuse microenvironment, plays a critical role in performance but is difficult to directly observe. This work demonstrates a method of two-dimensional spatial chemical mapping of the diffuse microenvironment in the context of alkali metal hydroxide direct air capture of carbon dioxide using a custom operando gas-absorption flow cell along with confocal Raman spectroscopy. Notably, we observe the concentration boundary layer near the gas–liquid interface and elucidate the interplay of carbonate and bicarbonate ions within it while inferring local hydroxide depletion through continuum modeling. These first of their kind observations provide a technique to compare the performance of direct air capture solvents based on diffuse microenvironment dynamics while also providing metrics important for air contactor design such as boundary layer thickness. Overall, this work showcases a new experimental platform to study interfacial diffuse microenvironments in and outside of the field of direct air capture of carbon dioxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Large Exciton Diffusion Coefficients in Two Dimensional Covalent Organic Frameworks with Different Domain Sizes Revealed by Ultrafast Exciton Dynamics

Large singlet exciton diffusion lengths are a hallmark of high performance in organic-based devices such as photovoltaics, chemical sensors, and photodetectors. In this study, exciton dynamics of a two-dimensional covalent organic framework, 2D COF-S, is investigated using ultrafast spectroscopic techniques. After photoexcitation, the COF-S exciton decays via three pathways: (1) excimer formation (4 +/- 2 ps), (2) excimer relaxation (160 +/- 40 ps), and (3) excimer decay (>3 ns). Excitation fluence-dependent transient absorption studies suggest that COF-5 has a relatively large diffusion coefficient (0.08 cm(2)/s). Furthermore, exciton-exciton annihilation processes are characterized as a function of COF-S crystallite domain size in four different samples, which reveal domain-size-dependent exciton diffusion kinetics. These results reveal that exciton diffusion in COF-S is constrained by its crystalline domain size. These insights indicate the outstanding promise of delocalized excitonic processes available in 2D COFs, which motivate their continued design and implementation into optoelectronic devices.

Flanders, Nathan C.↗
DOE OSTI2021

Connection Between Mass Flux Transport and Eddy Diffusivity in Convective Atmospheric Boundary Layers

Turbulence parameterizations for convective boundary layer in coarse-scale atmospheric models usually consider a combination of the eddy-diffusive transport and a non-local transport, typically in the form of a mass flux term, such as the widely adopted eddy-diffusivity mass-flux (EDMF) approach. These two types of turbulent transport are generally considered to be independent of each other. Using results from large-eddy simulations, here, we show that a Taylor series expansion of the updraft and downdraft mass-flux transport can be used to approximate the eddy-diffusivity transport in the atmospheric surface layer and the lower part of the mixed layer, connecting both eddy-diffusivity and mass-flux transport theories in convective conditions, which also quantifies departure from the Monin-Obukhov similarity (MOS) in the surface layer. This study provides a theoretical support for a unified EDMF parameterization applied to both the surface layer and mixed layer and highlights important correction required for surface models relying on MOS

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Pore Pressure Diffusion and Onset of Induced Seismicity

The Raton Basin of Southern Colorado and Northern New Mexico experienced a significant increase in seismicity over the last several decades, including two M5+ earthquakes. The increase in seismicity started soon after an increase in wastewater disposal associated with coal-bed methane production. Twenty-nine wastewater injection wells have operated in the Basin, with several high-rate injectors located within a kilometer of the most seismically active regions. We developed a pore pressure model to investigate the relationship between pore pressure diffusion and onset of induced seismicity, with an emphasis on the Trinidad fault zones. Our model indicates that sufficient pore pressure increase had accumulated on the northern extent of the Trinidad fault zone to induce seismicity at the time of early-stage seismic activity. The hydrogeologic architecture of the Basin played a key role in controlling pore pressure perturbation. The basal sedimentary interval with moderately low diffusivity restricted vertical pore pressure diffusion, creating a substantial lag time between wells becoming active and the expression of perturbation in the fault zones. The spatiotemporal relationship between early-stage seismicity and wastewater injection in conjunction with modeled pore pressures suggests that the early-stage seismicity in the Raton Basin was likely triggered by pore pressure diffusion.

58 GEOSCIENCES↗
DOE OSTI2025

A Unified Analytical Model for Pressure Solution With Fully Coupled Diffusion and Reaction

Abstract Geophysical models for pressure solution are typically developed for diffusion‐controlled or reaction‐controlled scenarios. We present a unified analytical model that considers fully coupled diffusion and reaction during pressure solution. The model recovers the diffusion‐controlled and reaction‐controlled models in the literature as specific limiting cases. When diffusion and reaction exhibit comparable influences, we validate the proposed model against independent numerical simulations. The proposed model is then employed in interpreting experimental measurements, demonstrating a better agreement compared to previous interpretations.

Wang, Ziyan [Energy Geosciences Division Lawrence ↗
DOE OSTI2021

Atomistic processes of surface-diffusion-induced abnormal softening in nanoscale metallic crystals

Abstract Ultrahigh surface-to-volume ratio in nanoscale materials, could dramatically facilitate mass transport, leading to surface-mediated diffusion similar to Coble-type creep in polycrystalline materials. Unfortunately, the Coble creep is just a conceptual model, and the associated physical mechanisms of mass transport have never been revealed at atomic scale. Akin to the ambiguities in Coble creep, atomic surface diffusion in nanoscale crystals remains largely unclear, especially when mediating yielding and plastic flow. Here, by using in situ nanomechanical testing under high-resolution transmission electron microscope, we find that the diffusion-assisted dislocation nucleation induces the transition from a normal to an inverse Hall-Petch-like relation of the strength-size dependence and the surface-creep leads to the abnormal softening in flow stress with the reduction in size of nanoscale silver, contrary to the classical “alternating dislocation starvation” behavior in nanoscale platinum. This work provides insights into the atomic-scale mechanisms of diffusion-mediated deformation in nanoscale materials, and impact on the design for ultrasmall-sized nanomechanical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Asymmetric rotations slow down diffusion under confinement

Translation and rotation are the two most fundamental forms of diffusion, yet their coupling mechanism is not clear, especially under confinement. Here, we provided evidence of the coupling between rotation and translation using a substituted benzene molecule as an example. A counterintuitive behavior was observed where the movement of the smaller molecule with an asymmetric shape was unexpectedly slower than the larger one with a symmetric shape in confined channels of zeolite. We showed that this diffusion behavior was caused by the presence of the specific and selective interaction of the asymmetric guest with the pores, which increased the local restricted residence time, thus inhibiting the translation under confinement, as further confirmed by dynamic breakthrough curves, uptake measurements, quasi-elastic neutron scattering, and 2 H solid-state NMR techniques. Our work correlated asymmetric rotation and diffusion under a confined environment, which enriched our understanding of the coupling between rotation and translation and could shed light on a fundamental understanding of the diffusion process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Grain Boundary Effects on Radiation Damage and Tritium Diffusion in Li–Al–O Ceramics from Molecular Dynamics and Experiments

Understanding irradiation damage and tritium transport in LiAlO2 ceramics is essential for their deployment in tritium-producing burnable absorber rods (TPBARs). Grain boundaries (GBs) play an important role in governing radiation response and tritium transport in LiAlO2 and its secondary phase LiAl5O8. Using molecular dynamics simulations, we investigated defect evolution and tritium diffusion during displacement cascades in single-crystal and bicrystal LiAlO2 and LiAl5O8 at 600 K. The results reveal that GBs suppress the damage in the LiAlO2 bicrystals as compared to single crystals, via interstitial emission. The effect is more pronounced for Li defects, than for Al and O. In LiAl5O8 the damage reduction due to introduction of GB is less pronounced overall. Tritium diffusion coefficients at GBs are higher by factors of 2–10 relative to diffusion inside grain bulk. The effect is particularly pronounced in LiAlO2, where S5, S17, and S25 GBs promote rapid tritium transport, whereas LiAl5O8 exhibits slower diffusion due to reduced free volume at its GBs. These findings evince a trade-off that while GBs mitigate radiation damage by absorbing interstitials, they simultaneously provide fast pathways for tritium migration which is not desirable for TPBAR application. The mechanistic insights gained here establish a foundation for microstructural design strategies to balance radiation tolerance and tritium retention in ceramic breeder materials.

Roy, Ankit↗
DOE OSTI2020

Mineral reaction kinetics constrain the length scale of rock matrix diffusion

Mass transport by aqueous fluids is a dynamic process in shallow crustal systems, redistributing nutrients as well as contaminants. Rock matrix diffusion into fractures (void space) within crystalline rock has been postulated to play an important role in the transient storage of solutes. The reacted volume of host rock involved, however, will be controlled by fluid-rock reactions. Here we present the results of a study which focusses on defining the length scale over which rock matrix diffusion operates within crystalline rock over timescales that are relevant to safety assessment of radioactive and other long-lived wastes. Through detailed chemical and structural analysis of natural specimens sampled at depth from an active system (Toki Granite, Japan), we show that, contrary to commonly proposed models, the length scale of rock matrix diffusion may be extremely small, on the order of centimetres, even over timescales of millions of years. This implies that in many cases the importance of rock matrix diffusion will be minimal. Additional analyses of a contrasting crystalline rock system (Carnmenellis Granite, UK) corroborate these results.

58 GEOSCIENCES↗
DOE OSTI2020

Carbon nanotube porin diffusion in mixed composition supported lipid bilayers

Carbon nanotube porins (CNTPs), short pieces of carbon nanotubes capable of self-inserting into a lipid bilayer, represent a simplified model of biological membrane channels. We have used high-speed atomic force microscopy (HS-AFM) and all-atom molecular dynamics (MD) simulations to study the behavior of CNTPs in a mixed lipid membrane consisting of DOPC lipid with a variable percentage of DMPC lipid added to it. HS-AFM data reveal that the CNTPs undergo diffusive motion in the bilayer plane. Motion trajectories extracted from the HS-AFM movies indicate that CNTPs exhibit diffusion coefficient values broadly similar to values reported for membrane proteins in supported lipid bilayers. The data also indicate that increasing the percentage of DMPC leads to a marked slowing of CNTP diffusion. MD simulations reveal a CNTP-lipid assembly that diffuses in the membrane and show trends that are consistent with the experimental observations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

The role of geography in the complex diffusion of innovations

The urban–rural divide is increasing in modern societies calling for geographical extensions of social influence modelling. Improved understanding of innovation diffusion across locations and through social connections can provide us with new insights into the spread of information, technological progress and economic development. In this work, we analyze the spatial adoption dynamics of iWiW, an Online Social Network (OSN) in Hungary and uncover empirical features about the spatial adoption in social networks. During its entire life cycle from 2002 to 2012, iWiW reached up to 300 million friendship ties of 3 million users. We find that the number of adopters as a function of town population follows a scaling law that reveals a strongly concentrated early adoption in large towns and a less concentrated late adoption. We also discover a strengthening distance decay of spread over the life-cycle indicating high fraction of distant diffusion in early stages but the dominance of local diffusion in late stages. The spreading process is modelled within the Bass diffusion framework that enables us to compare the differential equation version with an agent-based version of the model run on the empirical network. Although both model versions can capture the macro trend of adoption, they have limited capacity to describe the observed trends of urban scaling and distance decay. We find, however that incorporating adoption thresholds, defined by the fraction of social connections that adopt a technology before the individual adopts, improves the network model fit to the urban scaling of early adopters. Controlling for the threshold distribution enables us to eliminate the bias induced by local network structure on predicting local adoption peaks. Finally, we show that geographical features such as distance from the innovation origin and town size influence prediction of adoption peak at local scales in all model specifications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Diffusion characteristics of water molecules in a lamellar structure formed by triblock copolymers

The distribution and diffusion of water molecules are playing important roles in determining self-assembly and transport properties of polymeric systems. Small-angle neutron scattering (SANS) experiments and molecular dynamics (MD) simulation have been applied to understand the distribution of water molecules and their dynamics in the lamellar membrane formed by Pluronic L62 block copolymers. Penetration of water molecules into the polyethylene oxide (PEO) layers of the membranes has been estimated using scattering length density (SLD) profiles obtained from SANS measurements, which agree well with the molecular distribution observed from MD simulations. The water diffusion coefficient at different regions of the lamellar membrane was further investigated using MD simulation. The diffusion characteristic shows a transition from normal to anomalous diffusion as the position of the water molecule changes from the bulk to PEO and to the polypropylene oxide (PPO) layer. Here we find that water molecules within the PEO or PPO layers follow subdiffusive dynamics, which can be interpreted by the model of fractional Brownian motion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The impact of nanoparticle softness on its tracer diffusion coefficient in all polymer nanocomposites

The diffusion of nanoparticles in a polymer matrix is an area of current interest. However, a complete understanding is still limited as it is often difficult to quantify the much slower motion of nanoparticles in a polymer matrix. To combat this problem, we have developed a protocol to measure the diffusion coefficient of soft nanoparticles in a linear polymer matrix. Recently developed synthetic control over soft nanoparticle structures combined with this protocol provides a pathway to separately elucidate the effects of the molecular weight and nanoparticle softness on its diffusive behavior. These results indicate that the nanoparticle softness and deformability dictate its motion. Increasing the cross-linking density of the nanoparticle for all molecular weights increases its hardness and suppresses its motion in the linear matrix. Additionally, the nanoparticle molecular weight dependence deviates from the exponential dependence for star polymers suggesting that these nanoparticles benefit from the cooperative motion of the matrix to open pathways for the nanoparticle. Finally, comparison of these experimentally determined values to the Stokes–Einstein theory demonstrates that the nanoparticles diffuse much slower than a hard sphere. This is interpreted to indicate that there exist additional interactions between the nanoparticle and polymer matrix that are not captured by Stokes–Einstein, including threading or entanglement of the linear chain with the nanoparticle.

Rostom, Sahar↗
DOE OSTI2023

Diffusion of Sn donors in β-Ga 2 O 3

Diffusion of the n-type dopant Sn in β-Ga 2 O 3 is studied using secondary-ion mass spectrometry combined with hybrid functional calculations. The diffusion of Sn from a Sn-doped bulk substrate with surface orientation (001) into an epitaxial layer is observed after heat treatments in the temperature range of 1050–1250 °C. Calculated formation energies of Sn-related and intrinsic defects show that the migration of Sn is mediated by Ga vacancies ( V Ga ) through the formation and dissociation of intermittent mobile V Ga Sn Ga complexes. The evolution of the Sn concentration vs depth profiles after heat treatments can be well described by a reaction–diffusion model. Using model parameters guided by the hybrid functional calculations, we extract a V Ga Sn Ga complex migration barrier of 3.0 ± 0.4 eV with a diffusion coefficient of 2 × 10 –1 cm 2 /s. The extracted migration barrier is consistent with our theoretical predictions using the nudged elastic band method, which shows migration barriers of 3.42, 3.15, and 3.37 eV for the [100], [010], and [001] directions, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ensemble flow reconstruction in the atmospheric boundary layer from spatially limited measurements through latent diffusion models

Due to costs and practical constraints, field campaigns in the atmospheric boundary layer typically only measure a fraction of the atmospheric volume of interest. Machine learning techniques have previously successfully reconstructed unobserved regions of flow in canonical fluid mechanics problems and two-dimensional geophysical flows, but these techniques have not yet been demonstrated in the three-dimensional atmospheric boundary layer. Here, we conduct a numerical analogue of a field campaign with spatially limited measurements using large-eddy simulation. We pose flow reconstruction as an inpainting problem, and reconstruct realistic samples of turbulent, three-dimensional flow with the use of a latent diffusion model. The diffusion model generates physically plausible turbulent structures on larger spatial scales, even when input observations cover less than 1% of the volume. Through a combination of qualitative visualization and quantitative assessment, we demonstrate that the diffusion model generates meaningfully diverse samples when conditioned on just one observation. These samples successfully serve as initial conditions for a large-eddy simulation code. We find that diffusion models show promise and potential for other applications for other turbulent flow reconstruction problems.

17 WIND ENERGY↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗