Generalized Poisson-Nernst-Planck-Based Physical Model of the O2|LSM|YSZ Electrode

The paper presents a generalized Poisson-Nernst-Planck model of an yttria-stabilized zirconia electrolyte developed from first principles of nonequilibrium thermodynamics which allows for spatial resolution of the space charge layer. It takes into account limitations in oxide ion concentrations due to the limited availability of oxygen vacancies. The electrolyte model is coupled with a reaction kinetic model describing the triple phase boundary with electron conducting lanthanum strontium manganite and gaseous phase oxygen. By comparing the outcome of numerical simulations based on different formulations of the kinetic equations with the results of EIS and CV measurements we attempt to discern the existence of separate surface lattice sites for oxygen adatoms and surface oxides from the assumption of shared ones. Moreover, we show that the mass-action kinetics model is sensitive to oxygen partial pressure unlike exponential kinetics models. The resulting model is fitted to a dataset of EIS and CVs spanning multiple temperatures and pressures, using various relative weights of EIS and CV data in the fitness function. The model successfully describes the physics of the interface around the OCV.

Conductivity Tensor in Cylindrical Quantum Wire with Parabolic Potential for the Case of Electron-Acoustic Phonon Scattering

Conductivity tensor is an important concept in materials, this work studies conductivity tensors in cylindrical quantum wires with parabolic potential in the presence of two external fields, a linearly polarized electromagnetic wave, and a laser field. This work is also only considered for the case of electron-acoustic phonon scattering. Research results are obtained by using quantum kinetic equations for the carrier system in a quantum wire. The conductivity tensor is calculated by solving the quantum kinetic equation of the system, which is a function of the external field frequency, the external field amplitude, the temperature of the helium, and parameters specific to the quantum wire. Results will also be examined and plotted for quantum wire GaAs / GaAsAl.

Cyclic Tension Induced Pattern Formation on [001] Single-Crystal Aluminum Foil

Cyclic tension of (100)[001]-oriented single-crystal aluminum foils with the frequency 5 Hz forms a tweed pattern. Its period is several microns and increases by a factor of 1.5 in the temperature range 233–363 K. A model is proposed for structural relaxation of the medium on spatial and time meso- and macroscales under cyclic loading. Conditions under which a steady pattern forms are found based on the analysis of kinetic equations. The number of bands in the steady pattern is found to be related to the strain rate. The process activation energy is determined.

Decoding Complexity in Structure-Sensitive Reactions

Structure-sensitive reactions involving the Mars and van Krevelen mechanism over metal and metal oxide catalysts are ubiquitous in reaction kinetics and engineering. The kinetic equations of such reactions are re-written to account for modern operando spectroscopy and microscopy observations. Emphasis is placed on reactions with nucleophilic (lattice) oxygen, oxygen reduction reversibility, an interconversion scheme, non-linear water adsorption, remote-control model, and non-uniform sites. The multiplicity of propane conversion over MoVTeNbOx catalysts is proven through a combination of non-linear competitive water adsorption, the presence of multiple active sites, a re-structuring active site, and oxygen adsorption. The modified remote-control kinetics for the Mars and van Krevelen mechanism can account for the observations of steady-state multiplicities and hysteresis. The results have implications for improving catalytic activity, reducing operating process costs, and active site engineering of selective oxidation catalysis.

Vaccination, Immunity and Breakthrough: Quantitative Effects in Individual Immune Responses Illustrated by a Simple Kinetic Model

The personal risks of infection, as well as the conditions for achieving herd immunity, are strongly dependent on an individual’s response to the infective agents on the one hand, and the individual’s reactions to vaccination on the other hand. The main goal of this work is to illustrate the importance of quantitative individual effects for disease risk in a simple way. The applied model was able to illustrate the quantitative effects, in the cases of different individual reactions, after exposition to viruses or bacteria and vaccines. The model was based on simple kinetic equations for stimulation of antibody production using different concentrations of the infective agent, vaccine and antibodies. It gave a qualitative explanation for the individual differences in breakthrough risks and different requirements concerning a second, third or further vaccinations, reconsidering different efficiencies of the stimulation of an immune reaction.

The effects of magnetic island on toroidal ion temperature gradient mode instability

In this work, we have investigated the influences of magnetic island (MI) on electrostatic toroidal ion temperature gradient (ITG) mode, where the ions are described by gyro-kinetic equations including MI, and adiabatic approximation is used for electrons. The eigen-equation for short-wavelength toroidal ITG mode in Fourier-ballooning representation is derived, and the corresponding eigen-value as well as mode structure are solved. Both the flattening effects of MI on plasma pressure and MI-scale shear flow are considered. It is found that when only considering the flattening effects of MI, ITG mode can be stabilized as compared to the case without MI. While, the effective drive of toroidal ITG mode could be enhanced by including MI-scale flow, which indicates the dominant destabilizing by MI-scale flow over the stabilizing by flattening profile and results in higher growth rate than the case without MI. It is also found that the total flow shearing may prevent the ITG turbulence spreading from X-point of MI but not strong enough to prevent spreading from the seperatrix across O-point of larger MI via comparison between the flow shearing rate and the linear growth rate. Furthermore, the corresponding width of lowest-order mode structure in ballooning angle is slightly widened (narrowed) for the case without (with) MI-scale flow, as compared to the case without MI. Besides, the shifted even symmetry in ballooning angle is not qualitatively influenced by the presence of MI. The mode structure is radially asymmetric, but is symmetric with respect to the phase of MI at the O-point.

An Online-Learned Neural Network Chemical Solver for Stable Long-Term Global Simulations of Atmospheric Chemistry

A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine-learned (ML) solvers can offer order-of-magnitude speedup relative to conventional implicit solvers, but past implementations have suffered from fast error growth and only run for short simulation times (<1 month). A successful ML solver for global models must avoid error growth over year-long simulations and allow for re-initialization of the chemical trajectory by transport at every time step. Here we explore the capability of a neural network solver equipped with an autoencoder to achieve stable full-year simulations of tropospheric oxidant chemistry in the global 3-D GEOS-Chem model, replacing its standard mechanism (228 species) by the Super-Fast mechanism (12 species) to avoid the curse of dimensionality. We find that online training of the ML solver within GEOS-Chem is essential for accuracy, whereas offline training from archived GEOS-Chem inputs/outputs produces large errors. After online training we achieve stable 1-year simulations with five-fold speedup compared to the standard implicit Rosenbrock solver with global tropospheric normalized mean biases of -0.3% for ozone, 1% for hydrogen oxide radicals, and -5% for nitrogen oxides. The ML solver captures the diurnal and synoptic variability of surface ozone at polluted and clean sites. There are however large regional biases for ozone and NOx under remote conditions where chemical aging leads to error accumulation. These regional biases remain a major limitation for practical application, and ML emulation would be more difficult in a more complex mechanism.

Neutrino Transport with the Monte Carlo Method. II. Quantum Kinetic Equations

Neutrinos have a unique quantum feature as flavor conversions. Recent studies suggested that collective neutrino oscillations play important roles in high-energy astrophysical phenomena. The quantum kinetic equation (QKE) is capable of describing the neutrino flavor conversion, transport, and matter collision self-consistently. However, we have experienced many technical difficulties in their numerical implementation. In this paper, we present a new QKE solver based on a Monte Carlo (MC) approach. This is an upgraded version of our classical MC neutrino transport solver; in essence, a flavor degree of freedom including mixing state is added into each MC particle. This extension requires updating numerical treatments of collision terms, in particular for scattering processes. We deal with the technical problem by generating a new MC particle at each scattering event. To reduce statistical noise inherent in MC methods, we develop the effective mean free path method. This suppresses a sudden change of flavor state due to collisions without increasing the number of MC particles. We present a suite of code tests to validate these new modules with comparison to the results reported in previous studies. Our QKE-MC solver is developed with fundamentally different philosophy and design from other deterministic and mesh methods, suggesting that it will be complementary to others and potentially provide new insights into physical processes of neutrino dynamics.