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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

On how fast ions enhance the regulation of drift wave turbulence by zonal flows

Abstract This paper presents a mechanism for enhanced regulation of drift wave turbulence by zonal flows in the presence of a fast ion population. It demonstrates that dilution effects due to the energetic particles (EPs) have a far-reaching impact on all aspects of the nonlinear dynamics. The modulational growth of zonal flow shear and the corresponding evolution of drift wave energy are calculated with dilution effects. The coupled zonal flow growth and drift wave energy equations are reduced to a predator–prey model. This is solved for the fixed points, which represents the various states of the system. Results display a strong dependence on dilution, which leads to greatly reduced levels of saturated turbulence and transport. Implications for the FIRE mode plasma of KSTAR are discussed in detail. This model is perhaps the simplest dynamical one which captures the beneficial effects of EPs on confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System: Preprint

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗
DOE OSTI2021

Physics-based, neural network force fields for reactive molecular dynamics: Investigation of carbene formation from [EMIM + ][OAc - ]

Reactive molecular dynamics simulations enable detailed understanding of solvent effects on chemical reaction mechanisms and reaction rates. While classical molecular dynamics using reactive force fields allows significantly longer simulation time scales and larger system sizes compared with ab initio molecular dynamics, constructing reactive force fields is a difficult and complex task. In this work, we describe a general approach following the Empirical Valence Bond (EVB) framework for constructing ab initio reactive force fields for condensed phase simulations by combining physics-based methods with neural networks (PB/NN). The physics-based terms ensure correct asymptotic behavior of electrostatic, polarization, and dispersion interactions, and are compatible with existing solvent force fields. Neural networks are utilized for versatile description of short-range orbital interactions within the transition state region, and accurate rendering of vibrational motion of the reacting complex. Herein, we demonstrate our methodology for a simple deprotonation reaction of the 1-ethyl-3-methylimidazolium (EMIM+) cation with acetate to form 1-ethyl- 3-methylimidazol-2-ylidene and acetic acid. Our PB/NN force field exhibits ~ 1 kJ/mol MAE accuracy within the transition state region for the gas-phase complex. To characterize solvent modulation of the reaction profile, we compute potentials of mean force (PMFs) for the gas-phase reaction as well as the reaction within a four ion cluster, and benchmark against ab initio molecular dynamics simulations. We find that the surrounding ionic environment significantly destabilizes formation of the carbene product, and we show that this effect is accurately captured by the reactive force field. By construction, the PB/NN potential may be directly employed for simulations of other solvents/chemical environments without additional parameterization.

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

Unraveling capacity fading in lithium-ion batteries using advanced cyclic tests: A real-world approach

Battery lifespan estimation is essential for effective battery management systems, aiding users and manufacturers in strategic planning. However, accurately estimating battery capacity is complex, owing to diverse capacity fading phenomena tied to factors such as temperature, charge-discharge rate, and rest period duration. In this work, we present an innovative approach that integrates real-world driving behaviors into cyclic testing. Unlike conventional methods that lack rest periods and involve fixed charge-discharge rates, our approach involves 1000 unique test cycles tailored to specific objectives and applications, capturing the nuanced effects of temperature, charge-discharge rate, and rest duration on capacity fading. This yields comprehensive insights into cell-level battery degradation, unveiling growth patterns of the solid electrolyte interface (SEI) layer and lithium plating, influenced by cyclic test parameters. Here, the results yield critical empirical relations for evaluating capacity fading under specific testing conditions.

25 ENERGY STORAGE↗
DOE OSTI2022

Unraveling the role of EGR olefins at advanced combustion conditions in the presence of nitric oxide: Ethylene, propene and isobutene

We report the role of EGR (exhaust gas recirculation) olefinic constituents at advanced combustion conditions in the presence of nitric oxide is unraveled in this study through experimental and modeling efforts using a twin-piston rapid compression machine operating at a stochiometric fuel loading with 20% EGR by mass, pressures of 20 and 40 bar, and temperatures from 680 to 950 K. Five different levels of olefin addition, focusing on ethylene, propene and isobutene, with a fixed amount of NO at 70 ppm are doped into test mixtures of PACE-20, a multi-component gasoline surrogate, where olefin addition effects are characterized through changes in ignition times and heat release rates. Experiments indicate that all three EGR olefins inhibit autoignition reactivity and low-temperature heat release at Tc < 850 K, with isobutene exhibiting the greatest impact, while at Tc > 850 K, low ethylene and propene additions promote reactivity. A recently updated chemical kinetic model, with detailed gasoline/NO x interacting and olefin/NO x interacting chemistry incorporated, is adopted to simulate the experiments. Simulation results are somewhat inconsistent with the experiments, where the model captures the inhibiting effects of all olefins on first-stage ignition reactivity, while consistently predicting a promoting effect on main ignition reactivity. Sensitivity and rate of production analyses reveal that adding olefins greatly alters the role of the consuming pathways for the olefins and their primary derivatives at the initial stage of the oxidation process, particularly with the presence of NO, where the olefins and their derivatives interact with both NO x species such as NO 2 and other species such as OH and HO 2 . The olefin/NO x interactions are particularly pronounced with propene and isobutene addition, where these lead to increased ignition reactivity by facilitating NO production and are mostly responsible for the disagreement between the model and experiments. Further investigations of olefin interacting chemistry, particularly those with NOx species, are needed for chemistry models to accurately predict the complicated effects of EGR.

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

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗
NASA NTRS1985

A nonoscillatory shock capturing scheme using flux limited dissipation

A method for modifying the third order dissipative terms by the introduction of flux limiters is proposed. The first order dissipative terms can then be eliminated entirely, and in the case of a scalar conservation law the scheme is converted into a total variation diminishing scheme provided that an appropriate value is chosen for the dissipative coefficient. Particular attention is given to: (1) the treatment of the scalar conservation law; (2) the treatment of the Euler equations for inviscid compressible flow; (3) the boundary conditions; and (4) multistage time stepping and multigrid schemes. Numerical results for transonic flows suggest that a central difference scheme augmented by flux limited dissipative terms can lead to an effective nonoscillatory shock capturing method.

Jameson, A.↗
NASA NTRS1997

Binary Oscillatory Crossflow Electrophoresis

Electrophoresis has long been recognized as an effective analytic technique for the separation of proteins and other charged species, however attempts at scaling up to accommodate commercial volumes have met with limited success. In this report we describe a novel electrophoretic separation technique - Binary Oscillatory Crossflow Electrophoresis (BOCE). Numerical simulations indicate that the technique has the potential for preparative scale throughputs with high resolution, while simultaneously avoiding many problems common to conventional electrophoresis. The technique utilizes the interaction of an oscillatory electric field and a transverse oscillatory shear flow to create an active binary filter for the separation of charged protein species. An oscillatory electric field is applied across the narrow gap of a rectangular channel inducing a periodic motion of charged protein species. The amplitude of this motion depends on the dimensionless electrophoretic mobility, alpha = E(sub o)mu/(omega)d, where E(sub o) is the amplitude of the electric field oscillations, mu is the dimensional mobility, omega is the angular frequency of oscillation and d is the channel gap width. An oscillatory shear flow is induced along the length of the channel resulting in the separation of species with different mobilities. We present a model that predicts the oscillatory behavior of charged species and allows estimation of both the magnitude of the induced convective velocity and the effective diffusivity as a function of a in infinitely long channels. Numerical results indicate that in addition to the mobility dependence, the steady state behavior of solute species may be strongly affected by oscillating fluid into and out of the active electric field region at the ends of the cell. The effect is most pronounced using time dependent shear flows of the same frequency (cos((omega)t)) flow mode) as the electric field oscillations. Under such conditions, experiments indicate that solute is drawn into the cell from reservoirs at both ends of the cell leading to a large mass build up. As a consequence, any initially induced mass flux will vanish after short times. This effect was not captured by the infinite channel model and hence numerical and experimental results deviated significantly. The revised model including finite cell lengths and reservoir volumes allowed quantitative predictions of the time history of the concentration profile throughout the system. This latter model accurately describes the fluxes observed for both oscillatory flow modes in experiments using single protein species. Based on the results obtained from research funded under NASA grant NAG-8-1080.S, we conclude that binary separations are not possible using purely oscillatory flow modes because of end effects associated with the cos((omega)t) mode. Our research shows, however, that a combination of cos(2(omega)t) and steady flow should lead to efficient separation free of end effects. This possibility is currently under investigation.

Molloy, Richard F.↗
NASA NTRS1990

Numerical prediction of turbulent flow over airfoil sections with a new nonequilibrium turbulence model

A new nonequilibrium turbulence closure model has been developed for computing wall bounded two-dimensional turbulent flows. This two-layer eddy viscosity model was motivated by the success of the Johnson-King model in separated flow regions. The influence of history effects are described by an ordinary differential equation developed from the turbulent kinetic energy equation. The performance of the present model has been evaluated by solving the flow around three airfoils using the Reynolds time-averaged Navier-Stokes equations. Excellent results were obtained for both attached and separated turbulent flows about the NACA 0012 airfoil, the RAE 2822 airfoil, and the Integrated Technology A 153W airfoil. Based on the comparison of the numerical solutions with the available experimental data, it is concluded that the new nonequilibrium turbulence model accurately captures the history effects of convection and diffusion on turbulence.

Ahmed, S.↗
NASA NTRS2020

Polyvinyl Alcohol and Medium Density Polyethylene Composite Materials for Neutron Radiation Shielding

Manned spacecraft venturing beyond the Earth’s Van Allen Belts will be subjected to high levels of radiation from both energetic particles emanating from the sun and from galactic atomic events, such as supernovae. The metal shell of a spacecraft offers some protection from gamma radiation and high energy particles originating from both the sun and cosmic sources. The interaction of these high energy particles and radiation with the spacecraft hull create secondary radiation and neutrons, additional hazards for astronauts and electronic systems. Shielding of neutrons is the most challenging of the high energy radiation, since neutrons have zero charge and are least affected by electrical fields, magnetic fields, and atomic forces. Previous studies showed that polyethylene is an effective neutron shielding material, due to its high hydrogen content. High energy neutrons are slowed to thermal neutrons through multiple collisions with the hydrogen atoms, increasing the effectiveness of neutron capture by boron-10 atoms. This study discusses the fabrication and testing of polyvinyl alcohol (PVOH) samples as a neutron shielding material, with comparison to medium density polyethylene (MDPE) composite samples to be used for neutron shielding for spacecraft. PVOH, an aqueous polymer, was chosen for hydrogen content and for enabling the use of organic reinforcement such as cellulose for secondary structural composites. OLTARIS (On-Line Tool for the Assessment of Radiation in Space) was used for radiation shielding simulation and compared with experimental data. Modeling indicates that the most effective shielding from radiation was in an aluminum layer backed by a polymer layer, either MDPE or PVOH. Cross-linked PVOH was also included in the OLTARIS modeling. All 3 polymer cases showed shielding improvement over aluminum alone, with similar dose equivalent reduction for galactic cosmic radiation(GCR)and for radiation from a solar particle event (SPE). Fourier Transform Infrared (FTIR) Spectroscopy was used to confirm the cross-linking in the PVOH sample and to determine the uniformity through the thickness. PVOH, cross-linked PVOH, and MDPE samples were tested for neutron shielding effectiveness using a 1 curie Americium-Beryllium neutron source. Test results indicated the most shielding in the cross-linked PVOH, followed by the pristine PVOH, and MDPE. Neutron testing suggests that polyvinyl alcohol is a good alternative to polyethylene for neutron shielding. The neutron shielding materials, PVOH and cross-linked PVOH developed under this research will enable the safe operation of spacecraft beyond the Earth’s protective Van Allen Radiation Belts. It will be crucial for NASA’s manned missions to the Moon or Mars to protect the health of astronauts and equipment from the harmful effects of excessive radiation.

neutron, shielding, radiation, polyvinyl alcohol, ↗
DOE OSTI2024

Device Feasibility Analysis of Multi-level FeFETs for Neuromorphic Computing

As an emerging non-volatile memory device technology, Ferroelectric Field-Effect Transistors (FeFETs) can enable low-power, adaptive intelligent system design. However, device dimension and operating voltage dependent reliability issues of scaled FeFETs can ultimately lead to degraded performance in solving machine learning tasks. In this article, detailed experimental characterization of FeFET devices of different dimensions have been carried out to explicitly evaluate the non-ideal behavior in device conductance programming properties like number of programming states, cycle-to-cycle (C2C) variations, device-to-device (D2D) variations, and state retention. A hardware-aware software simulation approach has been adopted to capture the adversarial effects of the non-idealities on recognition accuracy through algorithm-level performance assessment by including them in NeuroSim, a popular neural network hardware simulator, to execute a neural network model considering all other hardware constraints. With the added non-idealities, significant accuracy degradation has been observed compared to the ideal scenarios where D2D variations play the most critical role. Thereafter, feasibility of a variation-aware training method has been evaluated to tackle the accuracy drop.

42 ENGINEERING↗
DOE OSTI2022

The role of coverage effects on the structure–sensitivity of formic acid electrooxidation on Pd surfaces

Direct formic acid (FA) fuel cells (DFAFCs) with Pd anode catalysts are promising for small portable applications. During the electrooxidation of formic acid (FAO), CO accumulates on the Pd electrocatalyst, thereby decreasing its performance. In this work, we use density functional theory (DFT; RPBE) to elucidate the significance of coverage effects on the structure–sensitivity of FAO over four low–index Pd surfaces: Pd(1 1 1), Pd(1 0 0), Pd(1 1 0), and Pd(2 1 1). We construct coverage–dependent Gibbs free energy diagrams and in agreement with experiment, predict that Pd(1 0 0) and Pd(2 1 1) are the most active surfaces. Additionally, we find that the presence of CO spectator species can alter the preferred electrooxidation pathway under different applied potentials. Furthermore, such pathway transitions appear to be critical for rationalizing experimental trends regarding electrocatalytic activity and are only captured when coverage effects are accounted for. Insights derived from this work may facilitate the design of improved FAO electrocatalysts.

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

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Network Effects of Risk Behavior Change Following Prophylactic Interventions

We formulated a network-based model to understand how risk behavior change in conjunction with failure of prophylactic interventions can lead to unintended outcomes where ‘‘less (intervention) is more (effective).’’ Our model captures the distinction between one- and two-sided risk behavior change. In one-sided situations (e.g. influenza/H1N1) it is sufficient for either individual in an interaction to exhibit risk behavior change whereas in two-sided situations (e.g. AIDS/HIV) it is necessary for both individuals in the interaction to exhibit risk behavior change, for a potential transmission of the disease. A central discovery is that this phenomenon occurs at differing levels of intervention coverage depending upon the ‘‘sidedness’’ of the interaction. We find that for one-sided interactions, sufficiently high vaccination coverage is necessary for mitigating the effects of risk behavior; for two-sided interactions, it is essential to combine prophylactic treatments with programs aimed at reducing risky behavior. Furthermore, again dependent on the ‘‘sidedness,’’ targeting highly connected nodes can be strictly worse than uniformly random interventions at the same level of coverage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Cosmic-Ray Nucleosynthesis of p -nuclei: Yields and Routes

We review the cosmic-ray nucleosynthesis (CRN) of proton-rich stable nuclides (p-nuclides). We calculate the cosmic-ray (CR) energy spectra of heavy nuclides with mass number $A=[74,209]$, taking into account the detailed nuclear spallation, decay, energy loss, and escape from the Galaxy during the CR propagation. We adopt the latest semiempirical formula SPACS for the spallation cross sections and the latest data on nuclear decay. Effective electron-capture decay rates are calculated using the proper cross sections for recombination and ionization in the whole CR energy region. Measured CR spectral shapes vary for different nuclides. Abundances of proton-rich unstable nuclides increase in CRs with increasing energy relative to those of other nuclides. Yields of the primary and secondary spallation processes and differential yields from respective seed nuclides are calculated. We find that the CR energy region of $\leqslant { \mathcal O }(100)$ MeV/nucleon predominantly contributes to the total yields. The atomic cross sections in the low-energy range adopted in this study are then necessary. Effects of CRN on the Galactic chemical evolution of p-nuclides are calculated. Critical seed nuclides are identified for respective p-nuclides. The contribution of CRN is significant for 180m Ta, accounting for about 20% of the solar abundance. About 87% of the 180m Ta CRN yield can be attributed to the primary process. The most important production routes are reactions of 181 Ta, 180 Hf, and 182 W. CRN yields of other p-nuclides are typically about ${ \mathcal O }$(10 –4 –10 –2 ) of solar abundances.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Functional Response of a Near-Surface Soil Microbial Community to a Simulated Underground CO 2 Storage Leak

Understanding the impacts of leaks from geologic carbon sequestration, also known as carbon capture and storage, is key to developing effective strategies for carbon dioxide (CO 2 ) emissions management and mitigation of potential negative effects. Here, we provide the first report on the potential effects of leaks from carbon capture and storage sites on microbial functional groups in surface and near-surface soils. Using a simulated subsurface CO 2 storage leak scenario, we demonstrate how CO 2 flow upward through the soil column altered both the abundance (DNA) and activity (mRNA) of microbial functional groups mediating carbon and nitrogen transformations. These microbial responses were found to be seasonally dependent and correlated to shifts in atmospheric conditions. While both DNA and mRNA levels were affected by elevated CO 2 , they did not react equally, suggesting two separate mechanisms for soil microbial community response to high CO 2 levels. The results did not always agree with previous studies on elevated atmospheric (rather than subsurface) CO 2 using FACE (Free-Air CO 2 Enrichment) systems, suggesting that microbial community response to CO 2 seepage from the subsurface might differ from its response to atmospheric CO 2 increases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Surface Charge in Electrical Double Layer as a Kinetic Descriptor of Electrocatalytic Reactions

The successful commercialization of electrochemical energy-conversion systems hinges on a deeper understanding of electrocatalytic reaction kinetics. Despite extensive research, a key descriptor that characterizes electrolyte effects on reaction kinetics remains elusive. Here, surface charge in electrical double layers (EDLs) is introduced as a descriptor for electrolyte-dependent kinetics. The surface charge is calculated with a continuum EDL model parameterized by density-functional theory. The model is validated by reproducing the anomalously low slope of Pt(111) in Parsons-Zobel plots. Strong correlations are observed between calculated surface charge and experimental kinetic currents for hydrogen evolution, oxygen reduction, and CO 2 -reduction reactions across various pH levels and cationic species. These correlations can be either promotional or inhibitory, depending on solute-intermediate interactions. In acidic media, incorporating adsorbate charge captures specific adsorption effects in oxygen reduction reaction. In conclusion, these findings establish surface charge density as a key descriptor for electrolyte-dependent kinetics, which will guide the design of the electrode/electrolyte interface.

Adsorption↗
DOE OSTI2016

Quantitatively in Situ Imaging Silver Nanowire Hollowing Kinetics

We report the in-situ investigation of the morphological evolution of silver nanowires to hollow silver oxide nanotubes using transmission x-ray microscopy (TXM). Complex silver diffusion kinetics and hollowing process via the Kirkendall effect have been captured in real time. Further quantitative x-ray absorption analysis reveals the difference between the longitudinal and radial diffusions. In conclusion, the diffusion coefficient of silver in its oxide nanoshell is, for the first time, calculated to be 1.2 × 10 -13 cm 2 /s from the geometrical parameters extracted from the TXM images.

36 MATERIALS SCIENCE↗