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At least 343 records · Page 19

Theory, observations, and simulations of kinetic entropy in a magnetotail electron diffusion region

In this work, we examine velocity-space kinetic entropy, a spatially local measure of entropy for systems out of thermal equilibrium, during an encounter of an electron diffusion region at a magnetic reconnection site in Earth’s magnetotail by the Magnetospheric Multiscale (MMS) mission. We start by generalizing the theory of kinetic entropy to the case of non-uniform velocity space grids and transforming the equations into spheri- cal energy coordinates useful to experimental plasma detectors. The theory is then applied to MMS data and compared to particle-in-cell simulations of reconnection. We demonstrate that the entropy-based non-Maxwellianity measure from the MMS data is of sufficiently high precision to reliably identify non-Maxwellian distributions and therefore the measurements when kinetic effects are most significant. By comparing two different non-Maxwellian measures, we show that total entropy density suffers from “information loss” because it lacks a dependence on the velocity space grid, and so has lost information about how well a distribution function is resolved. Local velocity-space kinetic entropy density recovers this information. We quantify information loss and argue that the considerations needed to minimize it are crucial for instruments designed to measure distribution functions in situ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparing the kinetics of ionized and neutral atoms from single and multi-element laser-produced plasmas

In this work, kinetics of ion and neutral atom emission features were compared for nanosecond laser-produced plasmas generated from several metal targets (i.e., Al, Ti, Zr, Nb, Ta) and an alloy containing all of these as principal alloying elements. Plasmas were produced by focusing 6 ns, 1064 nm pulses from an Nd:YAG laser on the targets of interest in a vacuum. A Faraday cup was used for collecting ion temporal features while spatially and temporally resolved emission spectroscopy was used for measuring the optical time of flight of various neutral atomic transitions. Our results highlight that most probable ion and atom velocities decay with increasing atomic mass. Trends for ions from the alloy target represent a weighted average where all ions contribute. For both ions and atoms, velocities decrease with increasing heat of vaporization and melting temperature, consistent with the thermal mechanisms that contribute to nanosecond laser ablation. Kinetic energies for neutral atoms from pure metal targets have some variability with atomic mass, whereas kinetic energies for atoms from the alloy target are more similar. These more similar kinetic energies observed for neutral atoms in the multi-element plasma may be attributed to collisions between species from all elements in the Knudsen layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Influence of surface adsorption on MoS 2 memtransistor switching kinetics

Sulfur-deficient polycrystalline two-dimensional (2D) molybdenum disulfide (MoS 2 ) memtransistors exhibit gate-tunable memristive switching to implement emerging memory operations and neuromorphic computing paradigms. Grain boundaries and sulfur vacancies are critical for memristive switching; however, the underlying physical mechanisms are not fully understood. Furthermore, the adsorption of water and gaseous species strongly perturbs electronic transport in monolayer MoS 2 , and little work has been done to explore the influence of surface interactions on defect-related kinetics that produces memristive switching. Here, we study the switching kinetics of back-gated MoS 2 memtransistors using current transient measurements in a controlled atmosphere chamber. Here, we observe that adsorbed water molecules lead to suppression of the electronic trap-filling processes concomitant with the resistive switching process, resulting in altered kinetics of the resistive switching. Additionally, using the transient response from “bunched” drain voltage pulse trains performed as a function of temperature, we extract the energy of the affected trap state and find that it places the trap roughly midgap [E T = E C – 0.7 (±0.4) eV]. Our results highlight the importance of controlling for surface interactions that may affect switching kinetics in 2D memtransistors, synaptic transistors, and related memory devices.

36 MATERIALS SCIENCE↗

On Galilean invariance of mean kinetic helicity

While kinetic helicity is not Galilean invariant locally, it is known [Moffatt, J. Fluid Mech. 35, 117 (1969)] that its spatial integral quantifies the degree of knottedness of vorticity field lines. Being a topological property of the flow, mean kinetic helicity is Galilean invariant. Here, we provide a direct mathematical proof that kinetic helicity is Galilean invariant when spatially integrated over regions enclosed by vorticity surfaces, i.e., surfaces of zero vorticity flux. Here, we also discuss so-called relative kinetic helicity, which is Galilean invariant when integrated over any region in the flow.

42 ENGINEERING↗

A DFT-based kinetic Monte Carlo simulation of multiphase oxide-metal thin film growth

Functional thin films of nanoscale metal pillars in oxide or nitride matrices known as vertically aligned nanocomposite (VAN) have gained much interest owing to their unique strain-coupled and highly anisotropic properties. So far, the deposition of these films has been explored mostly experimentally. In this work, a density functional theory (DFT)-based kinetic Monte Carlo simulation model using Bortz–Kalos–Lebowitz algorithm was developed to understand the growth of VAN films deposited by pulsed laser technique on mismatching substrates. The model has been parameterized and applied to understand the kinetics of growth thin films consisting of Au pillars in CeO2 matrix deposited on SrTiO3 substrates. The effects of pulsed laser deposition (PLD) conditions including the pulse frequency, deposition flux, and substrate temperature were explored. The simulations indicate that the Au pillar size and shape exhibit significant dependence on the PLD conditions. Namely, increasing the temperature increases the average pillar size and lowers the pillar density, and vice versa. In addition, the simulations revealed that increasing the deposition rate results in lowering the average pillar size and increasing the density. Particularly, the DFT results suggest that Au pillar size can be tuned during the initial growth of the first monolayer due to the significantly low activation barrier. Our analysis showed that the relationship between the average pillar size and pillar density is influenced by the kinetics. Furthermore, autocorrelation analysis showed that pillars self-organize in quasi-ordered patterns at certain windows of the deposition conditions, which is attributed to the complex nature of the chemical interactions in the system, the kinetics, and the deposition parameters.

Physics↗

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗

Kinetics and selectivity of methane oxidation on an IrO 2 (110) film

Undercoordinated, bridging O-atoms (O br ) are highly active as H-acceptors in alkane dehydrogenation on IrO 2 (110) surfaces but transform to HO br groups that are inactive toward hydrocarbons. The low C–H activity and high stability of the HO br groups cause the kinetics and product selectivity during CH 4 oxidation on IrO 2 (110) to depend sensitively on the availability of O br atoms prior to the onset of product desorption. From temperature programmed reaction spectroscopy (TPRS) and kinetic simulations, we identified two O br -coverage regimes that distinguish the kinetics and product formation during CH 4 oxidation on IrO 2 (110). Under excess O br conditions, when the initial O br coverage is greater than that needed to oxidize all the CH 4 to CO 2 and HO br groups, complete CH 4 oxidation is dominant and produces CO 2 in a single TPRS peak between 450 and 500 K. However, under O br -limited conditions, nearly all the initial O br atoms are deactivated by conversion to HO br or abstracted after only a fraction of the initially adsorbed CH 4 oxidizes to CO 2 and CO below 500 K. Thereafter, some of the excess CH x groups abstract H and desorb as CH 4 above ~500 K while the remainder oxidize to CO 2 and CO at a rate that is controlled by the rate at which Obr atoms are regenerated from HObr during the formation of CH 4 and H 2 O products. We also show that chemisorbed O-atoms ('on-top O') on IrO 2 (110) enhance CO 2 production below 500 K by efficiently abstracting H from Obr atoms and thereby increasing the coverage of O br atoms available to completely oxidize CH x groups at low temperature. Furthermore, our results provide new insights for understanding factors which govern the kinetics and selectivity during CH 4 oxidation on IrO 2 (110) surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kinetic equilibrium reconstructions of plasmas in the MAST database and preparation for reconstruction of the first plasmas in MAST upgrade

Reconstructions of plasma equilibria using magnetic sensors were routine during operation of the Mega Ampere Spherical Tokamak (MAST) device, but reconstructions using kinetic profiles were not. These are necessary for stability and disruption analysis of the MAST database, as well as for operation in the upgrade to the device, MAST-U. The three-dimensional (3D) code VALEN is used to determine eddy currents in the 3D vessel structures for vacuum coil test shots, which are then mapped to effective resistances in the two-dimensional vessel groupings in the EFIT equilibrium reconstruction code to be used in conjunction with nearby loop voltage measurements for estimated currents in the structures during reconstruction. Kinetic equilibrium reconstructions with EFIT, using all available magnetic sensors as well as Thomson scattering measurements of electron temperature and density, charge exchange recombination spectroscopy measurements of ion temperature, and internal magnetic field pitch angle measurements from a motional Stark effect (MSE) diagnostic are performed for a large database of MAST discharges. Excellent convergence errors are obtained for the portions of the discharges where the stored energy was not too low, and it is found that reconstructions performed with temperature and density measurements but without MSE data usually already match the pitch angle measurements well. A database of 275 kinetic equilibria is used to test the ideal MHD stability calculation capability for MAST. In conclusion, the necessary changes to conducting structure in VALEN, and diagnostic setup in EFIT have been completed for the upgrade from MAST to MAST-U, enabling kinetic reconstructions to commence from the first plasma discharges of the upgraded device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accuracy of kinetic equilibrium reconstruction of NSTX and NSTX-U plasmas and its impact on the transport and stability analysis

An accurate magnetohydrodynamic (MHD) equilibrium reconstruction is an essential starting point for stability and transport plasma analysis. Herein this work describes an approach for obtaining kinetic equilibrium reconstructions using the OMFIT framework, which has been applied for the first time to spherical tokamak data from NSTX and NSTX-U. The EFIT equilibrium solver is integrated with experimental data analysis procedures and subsequent TRANSP transport simulations to enhance the accuracy of the reconstruction, in particular, at the edge region, by adding constraints on the total pressure and current density profiles, based on the transport code solution. The accuracy of the equilibrium reconstruction depends on the uncertainty and number of constraints, as well as the choice of basis functions to represent the pressure and current density profiles. Improved fidelity of the equilibrium reconstruction is demonstrated by reducing the variability of the magnetic axis and boundary locations from several centimeters, for reconstructions based on magnetic and experimental pressure constraints, to only several millimeters, for kinetic reconstructions based on transport code constraints, when different representations of basis functions were tested. The variability of the safety factor on axis was reduced ten times in the same sensitivity study. The accuracy of the equilibrium reconstruction and subsequent mapping of the experimental kinetic profile data have a significant impact on the trapped gyro Landau fluid and linear CGYRO turbulence simulations, which predict different spectra of unstable modes and turbulent fluxes for cases with different numbers of constraints in the equilibrium reconstruction. Conversely, the stability analysis performed using the GATO code shows plasmas that are stable to n = 1 MHD modes in both equilibria using magnetic and experimental pressure constraints as well as the transport code constrained equilibrium. However, a scan of parameters away from these conditions shows considerable deviation in the threshold of unstable modes between these reconstructions. Therefore, for reliable plasma analysis and use in turbulence and stability calculations, a high-fidelity equilibrium reconstruction with accurate kinetic constraints based on transport code solutions is necessary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of kinetic ions on the toroidal double-tearing modes

We investigate the effects of kinetic ions on double-tearing modes (DTMs) using the gyrokinetic particle-in-cell simulation code GEM with a gyrokinetic ion/fluid electron hybrid model. It is found that the ion kinetic effects can decrease the growth rate of the DTMs. This effect is more significant for stronger coupling of DTMs with smaller distance between the rational surfaces. Kinetic ions can also enhance the coupling effect between the two rational surfaces. Energy transfer analyses between particles and wave fields show that the stabilizing effect of kinetic ions comes mainly from the perpendicular magnetic drift of ions in the coupling region and around the outer rational surface.

Physics↗

Explicit structure-preserving geometric particle-in-cell algorithm in curvilinear orthogonal coordinate systems and its applications to whole-device 6D kinetic simulations of tokamak physics

Explicit structure-preserving geometric particle-in-cell (PIC) algorithm in curvilinear orthogonal coordinate systems is developed. The work reported represents a further development of the structure-preserving geometric PIC algorithm achieving the goal of practical applications in magnetic fusion research. The algorithm is constructed by discretizing the field theory for the system of charged particles and electromagnetic field using Whitney forms, discrete exterior calculus, and explicit non-canonical symplectic integration. In addition to the truncated infinitely dimensional symplectic structure, the algorithm preserves exactly many important physical symmetries and conservation laws, such as local energy conservation, gauge symmetry and the corresponding local charge conservation. As a result, the algorithm possesses the long-term accuracy and fidelity required for first-principles-based simulations of the multiscale tokamak physics. The algorithm has been implemented in the SymPIC code, which is designed for high-efficiency massively-parallel PIC simulations in modern clusters. The code has been applied to carry out whole-device 6D kinetic simulation studies of tokamak physics. A self-consistent kinetic steady state for fusion plasma in the tokamak geometry is numerically found with a predominately diagonal and anisotropic pressure tensor. The state also admits a steady-state sub-sonic ion flow in the range of 10 km s -1 , agreeing with experimental observations and analytical calculations Kinetic ballooning instability in the self-consistent kinetic steady state is simulated. It is shown that high-n ballooning modes have larger growth rates than low-n global modes, and in the nonlinear phase the modes saturate approximately in 5 ion transit times at the 2% level by the E × B flow generated by the instability. These results are consistent with early and recent electromagnetic gyrokinetic simulations.

43 PARTICLE ACCELERATORS↗

Kinetics of solid–liquid interface motion in molecular dynamics and phase-field models: crystallization of chromium and silicon

The results of molecular dynamics (MD) simulations of the crystallization process in one-component materials and solid solution alloys reveal a complex temperature dependence of the velocity of the crystal–liquid interface featuring an increase up to a maximum at 10–30% undercooling below the equilibrium melting temperature followed by a gradual decrease of the velocity at deeper levels of undercooling. At the qualitative level, such non-monotonous behaviour of the crystallization front velocity is consistent with the diffusion-controlled crystallization process described by the Wilson–Frenkel model, where the almost linear increase of the interface velocity in the vicinity of melting temperature is defined by the growth of the thermodynamic driving force for the phase transformation, while the decrease in atomic mobility with further increase of the undercooling drives the velocity through the maximum and into a gradual decrease at lower temperatures. At the quantitative level, however, the diffusional model fails to describe the results of MD simulations in the whole range of temperatures with a single set of parameters for some of the model materials. The limited ability of the existing theoretical models to adequately describe the MD results is illustrated in the present work for two materials, chromium and silicon. It is also demonstrated that the MD results can be well described by the solution following from the hodograph equation, previously found from the kinetic phase-field model (kinetic PFM) in the sharp interface limit. The ability of the hodograph equation to describe the predictions of MD simulation in the whole range of temperatures is related to the introduction of slow (phase field) and fast (gradient flow) variables into the original kinetic PFM from which the hodograph equation is obtained. The slow phase-field variable is responsible for the description of data at small undercoolings and the fast gradient flow variable accounts for local non-equilibrium effects at high undercoolings. The introduction of these two types of variables makes the solution of the hodograph equation sufficiently flexible for a reliable description of all nonlinearities of the kinetic curves predicted in MD simulations of Cr and Si. This article is part of the theme issue ‘Transport phenomena in complex systems (part 1)’.

Science & Technology - Other Topics↗

Morphology selection in dealloying: A phase field study of the coupling among kinetic mechanisms

A phase field model is used to investigate how the corrosion rate and morphology of a dealloying metal is controlled by the kinetic rates of bulk solid diffusion, interfacial diffusivity, and interface dissolution. A specific focus is investigating the manner by which variations in these kinetic parameters synergistically influence the onset of a morphological instability at the solid-liquid interface, which is known to precede rapid dealloying corrosion towards highly topologically complex structures such as bicontinuous porous solids. This work demonstrates that this instability can be suppressed by either an increase of interdiffusion in the solid alloy, or by a decreasing rate of dissolution at the solid-liquid interface. When the instability is suppressed, the result is a relatively planar, passivated dealloying front. Importantly, however, coupled changes in kinetic parameters can also promote the morphological instability and sustain fine-scale ligament and pore formation. Finally, the relevance of the solid-liquid interfacial diffusion for determining the rate of dealloying and ligament formation is highlighted. By elucidating the mechanistic influence of bulk and interfacial kinetic factors on the dealloyed morphology, this work helps to rationalize the contrasting morphologies observed in various dealloying systems.

Diffusion↗

Emergent topological quasiparticle kinetics in constricted nanomagnets

The ubiquitous domain wall kinetics under magnetic field or current application describes the dynamic properties in nanostructured magnets. However, when the geometrical size of a nanomagnetic system is constricted to the limiting domain wall length scale, the competing energetics between anisotropy, exchange, and dipolar interactions can cause emergent kinetics due to quasiparticle relaxation, similar to bulk magnets of atomic origin. This paper presents a joint experimental and theoretical study to support this argument: constricted nanomagnets, made of antiferromagnetic and paramagnetic neodymium thin film with honeycomb motif, reveal fast kinetic events at picosecond timescales due to the relaxation of topological quasiparticles that persist to low temperature in the absence of any external stimuli. This discovery is especially important considering the fact that paramagnets or antiferromagnets have no net magnetization. Yet, the kinetics in neodymium nanostructures is quantitatively similar to that found in ferromagnetic counterparts and only varies with the thickness of the specimen. This suggests that a universal, topological quasiparticle-mediated dynamical behavior can be prevalent in nanoscopic magnets, irrespective of the nature of the underlying magnetic material.

Guo, Jiasen↗

Conversion kinetics of container glass batch melting

Abstract Understanding the batch‐to‐glass conversion process is fundamental to optimizing the performance of glass‐melting furnaces and ensuring that furnace modeling can correctly predict the observed outcome when batch materials or furnace conditions change. To investigate the kinetics of silica dissolution, gas evolution, and primary foam formation and collapse, we performed X‐ray diffraction, thermal gravimetry, feed expansion tests, and evolved gas analysis of batch samples heated at several constant heating rates. We found that gas evolving reactions, foaming, and silica dissolution depend on the thermal history of the batch in a similar manner: the kinetic parameters of each process were linear functions of the square root of the heating rate. This kinetic similarity reflects the stronger‐than‐expected interdependence of these processes. On the basis of our results, we suggest that changes in furnace operating conditions, such as firing or boosting, influence the melting rate less than what one would expect without consideration of batch conversion kinetics.

Ueda, Nanako↗

Inducing thermodynamically blocked atomic ordering via strongly driven nonequilibrium kinetics

Ultrafast light-matter interactions enable inducing exotic material phases by promoting access to kinetic processes blocked in equilibrium. Despite potential opportunities, actively using nonequilibrium kinetics for material discovery is limited by the poor understanding on intermediate states of driven systems. Here, using single-pulse time-resolved imaging with x-ray free-electron lasers, we found intermediate states of photoexcited bismuth nanoparticles that showed kinetically reversed surface ordering during ultrafast melting. This entropy-lowering reaction was further investigated by molecular dynamics simulations to reveal that observed kinetics were thermodynamically buried in equilibrium, which emphasized the critical role of electron-mediated ultrafast free-energy modification in inducing exotic material phases. This study demonstrated that ultrafast photoexcitations of electrons provide an efficient strategy to induce hidden material phases by overcoming thermodynamic barriers via nonequilibrium reaction pathways.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Controlling Interfacial Charge Separation Energetics and Kinetics

The overall goal is to probe electron transfer kinetics of the Marcus inverted region at interfaces. This project specifically uses a dye‐semiconductor interface with a reversible electron transfer reagent in solution where the semiconductor conduction band and electron transfer reagent ideally have a potential energy difference firmly within the Marcus inverted region. The goals of this project are: (Goal 1) Identify dye design elements that give dyes with low energy ground‐state oxidation potentials while retaining desirable electron transfer kinetics at the semiconductor interface. (Goal 2) Identify dye designs with excited‐state oxidation potentials set to fixed energies through molecular design while the dye ground‐state oxidation potentials are varied to allow for the evaluation of varied electron transfer reagents/redox shuttles (RS) with different free energies for electron transfer. (Goal 3) Within the context of the functionality identified in goals 1 and 2, goal 3 seeks to design dyes with features maximizing charge carrier lifetimes by minimizing recombination losses at metal oxide interfaces with high voltage systems. (Goal 4) Probe electron transfer kinetics in a high voltage‐dye sensitized solar cell with both the oxidized dye and RS firmly within the Marcus inverted region with regard to the TiO2 CB. (Goal 5) Identify tailored sensitizer/redox shuttle pairs with desirable electron transfer kinetics in defined spectral regions capable of “banding off” incident solar irradiation to give high voltage multijunction systems capable of exceeding the Shockley‐Queisser limit and powering catalytic processes.

14 SOLAR ENERGY↗

Applications of Kinetic Methods in Thermal Analysis: A Review

Determining kinetic parameters such as activation energy (Ea), pre-exponential factor (A), rate constants, and reaction order (n) via thermal analysis techniques is important to material synthesis and fabrication, industrial production, biomedicals, energy storage, catalysis, etc. Various kinetic methods based on the non-isothermal techniques have been developed to obtain the kinetic parameters. In this review, we focus on introducing various kinetic methods in non-isothermal analysis and their applications in different reactions, including thermal decomposition, solid-state phase transformation, crystallization, thermal ignition, curing process, etc.

Zhang, Xin↗