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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

On-lattice kinetic Monte Carlo approaches for modeling molecular anisotropy in resveratrol crystallization

Stilbenes are a class of organic compounds with broad-ranging pharmaceutical and agricultural applications, which are typically isolated and purified through recrystallization. We are motivated by reducing experimental waste and optimizing yield via developing predictive simulations for processing-dependent crystal morphologies. Using resveratrol as a model stilbene system, we have developed an approach for simulating crystallization with molecular resolution using on-lattice kinetic Monte Carlo. In this work, we highlight modifications to the Stochastic Parallel PARticle Kinetic Simulator (SPPARKS) software package, which were essential to this application. Key enhancements include the incorporation of non-orthogonal cell shapes and monomer anisotropy approximations using bound hard spheres. This new SPPARKS application has been applied to resveratrol with attachment energy libraries obtained from density functional theory, resulting in excellent agreement with experimental morphology prediction.

crystallization↗
DOE OSTI2022

Kinetic theory of particle-in-cell simulation plasma and the ensemble averaging technique

Abstract We derive the kinetic theory of fluctuations in physically and numerically stable particle-in-cell (PIC) simulations of electrostatic plasmas. The starting point is the single-time correlation at the start of the simulation between the statistical fluctuations of the weighted densities of macroparticle centers in the plasma particle phase-space. The fluctuations are associated with different initial conditions, typically due to the random initial conditions (in velocity space) of the macroparticles/simulation plasma, assigned according to their initial distribution of probability. The single-time correlations at all time steps and in each spatial grid cell are then determined from the Laplace–Fourier transforms of the discretized Klimontovich-like equation for the macroparticles and Maxwell’s equations for the fields, as computed by modern PIC codes. We recover the expressions for the electrostatic field and the plasma particle density fluctuation autocorrelation spectra as well as the kinetic equations describing the average evolution of PIC-simulated plasma particles, first derived by Langdon (1970b Proc. 4th Conf. Numerical Simulation of Plasmas ) using a test macroparticle approach perturbing a discretized Vlasovian plasma and then averaging the obtained physical quantity over the initial macroparticle velocity distribution. We generalize and extend these results to the modern algorithms in PIC codes using arbitrary macroparticle weights. Analytical estimates of statistical fluctuation amplitudes are derived as a function of the plasma simulation parameters, using the central limit theorem in the limit of a large number of macroparticles per cell. The theory is then used to analyze the ensemble averaging technique of PIC simulations where statistical averages are performed over ensembles of PIC simulations, modeling the same plasma physics problem but using different statistical realizations of the initial distribution functions of the macroparticles. This method is illustrated by linear Landau damping uncovering (from noise, which is usually considered numerical) the physical fluctuations driven by a single small amplitude electrostatic wave perturbing a PIC simulation plasma in equilibrium.

fluctuations correlations↗
DOE OSTI2026

Drift-kinetic effects of tungsten on plasma response to RMP in ITER

Here, effects of high- Z ( Z is the particle charge number) tungsten impurity ions on the plasma response to the resonant magnetic perturbation (RMP) field are numerically investigated for the ITER 15 MA baseline scenario, where the tungsten contribution to the plasma response is computed with a drift-kinetic model while the bulk thermal particle contributions follow the fluid approximation. The study yields three highlights: (i) the drift-kinetic contribution of the tungsten impurity exerts minor influence on the plasma response compared to that computed by the pure fluid model without tungsten; (ii) a new figure of merit, based on the resonant spectrum perturbation at the plasma boundary surface, results in different optimal coil phasing compared to that previously obtained by maximizing the edge-peeling plasma response; (iii) the optimal $n = 3$ RMP (for edge localized mode (ELM) control, $n$ is the toroidal mode number) is found to induce a large tungsten particle influx near the plasma edge associated with the neoclassical toroidal viscosity. The study thus provides useful data on the compatibility of the full tungsten wall with RMP ELM control in ITER.

ITER↗
DOE OSTI2022

Molecular beam mass spectrometry measurements of vibrationally excited N 2 in the effluent of an atmospheric plasma jet: a comparison with a state-to-state kinetic model

Vibrationally excited N 2 molecules are suggested to be one of the possible key species responsible for the observed synergistic effects in plasma catalysis for NH 3 synthesis. To assess the impact of vibrationally excited species in plasma-catalysis, quantitative measurements near interfaces are required, which remains challenging. In this letter, we report spatially resolved measurements of vibrationally excited N 2 in the effluent of an atmospheric pressure plasma jet by molecular beam mass spectrometry (MBMS). The mass spectrometry signals as a function of electron energy of the ionizer were fitted with the effective electron-impact ionization cross section of N 2 (v) considering the vibrational distribution function as determined by a detailed vibrational level resolved plasma kinetic calculation. Here, the reported method presented in this letter shows the capability of MBMS to measure vibrationally excited species of N 2 near interfaces when the vibrational distribution function is known or assumed and shows excellent agreement with state-to-state kinetic models of N 2 (v).

42 ENGINEERING↗
DOE OSTI2024

Energy-dependent implementation of secondary electron emission models in continuum kinetic sheath simulations

The plasma-material interactions present in multiple fusion and propulsion concepts between the flow of plasma through a channel and a material wall drive the emission of secondary electrons. This emission is capable of altering the fundamental structure of the sheath region, significantly changing the expected particle fluxes to the wall. The emission spectrum is separated into two major energy regimes, a peak of elastically backscattered primary electrons at the incoming energy, and cold secondary electrons inelastically emitted directly from the material. The ability of continuum kinetic simulations to accurately represent the secondary electron emission is limited by relevant models being formulated in terms of monoenergetic particle interactions which cannot be applied directly to the discrete distribution function. As a result, rigorous implementation of energy-dependent physics is often neglected in favor of simplified, constant models. We present here a novel implementation of semi-empirical models in the boundary of continuum kinetic simulations which allows the full range of this emission to be accurately captured in physically-relevant regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Global gyrokinetic simulation with kinetic electron for collisionless damping of zonal flow in stellarators

Global gyrokinetic simulations with kinetic electrons for collisionless damping of zonal flows in LHD and W7-X stellarators show that the helical components of the equilibrium magnetic field responsible for helically trapped particles have significant impacts on zonal flow. Kinetic electrons reduce zonal flow residue and increase the frequency of low frequency oscillation (LFO). Here, the LFO is induced by dominant helical harmonics of magnetic field strength. Furthermore, linear toroidal coupling of multiple toroidal n-harmonics barely affects the zonal flows, but can generate long wavelength toroidal harmonics with the same toroidal number as the helical magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Nonlinear saturation of reverse shear Alfvén eigenmodes induced by kinetic electrons

A strong nonlinear saturation mechanism of the reverse shear Alfvén eigenmode (RSAE) induced by thermal electrons is observed in gyrokinetic $\delta$$f$ particle-in-cell simulation. This nonlinear effect occurs at moderate mode amplitude, $\delta$$B$ ⟂ /$B$ < 10 -3 , and is associated with the electron parallel streaming along the perturbed magnetic field lines, the term v $\|$ $\frac{δΒ_{⟂}}{B}$ ∙ ∇$\delta$$f$, in the electron drift-kinetic equation. In the case of an n = 4 RSAE, where n is the toroidal mode number, this magnetic fluttering nonlinearity leads to strong mode coupling and broadening of the saturation spectrum. The nonlinear components, which are highly damped through the interaction between thermal electrons and the parallel electric field, modifies the RSAE mode structure and suppresses energetic particle drive significantly. The split-weight scheme (Chen and Parker 2007 J. Comput. Phys. 220 839–55) is used to simulate kinetic electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Machine learning-based real-time kinetic profile reconstruction in DIII-D

Abstract Kinetic equilibrium reconstruction plays a vital role in the physical analysis of plasma stability and control in fusion tokamaks. However, the traditional approach is subjective and prone to human biases. To address this, the consistent automatic kinetic equilibrium reconstruction (CAKE) method was introduced, providing objective results. Nonetheless, its offline nature limits its application in real-time plasma control systems (PCSs). To address this limitation, we present RTCAKENN, a machine learning model that approximates 7 CAKE-level output profiles, namely pressure, inverse q , toroidal current density, electron temperature and density, carbon ion impurity temperature and rotation profiles, using real-time available inputs. The deep neural network consists of an encoder layer, where the scalars and interdependent inputs such as plasma boundary coordinates and motional Stark effect data are encoded using multi-layer perceptrons (MLPs), while profile inputs are encoded by 1D convolutional layers. The encoded data is passed through a MLP for latent feature extraction, before being decoded in the decoding layers, which consist of upsampling and convolutional layers. RTCAKENN has been implemented in the DIII-D PCS and our model achieves accuracy comparable to CAKE and surpasses existing real-time alternatives. Through clever dropout training, RTCAKENN exhibits robustness and can operate even in the absence of Thomson scattering data or charge exchange recombination data. It executes in under 8 ms in the real-time environment, enabling future application in real-time control and analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Probing enhanced lithium-ion transport kinetics in 2D holey nanoarchitectured electrodes

Nanostructuring has been proved effective towards improving many energy storage and conversion devices, and is feasible for a wide range of materials. In particular, secondary nanoarchitectured materials exhibit collective advantages compared with nano-sized primary building blocks. Despite the manifold efforts in designed nanoarchitectures and synthetic routes, the underlying ion diffusion kinetics and phase transformation behaviours within nanoarchitectures still remain less explored. Herein, we probed enhanced lithium-ion transport behaviours using 2D holey zinc ferrite (ZFO) nanosheets as a model material, to demonstrate how self-assembled 2D holey nanoarchitectured electrodes can feature efficient ion diffusion channels, robust yet continuous electron transfer framework, and enlarged surface area, contributing to the superior performance over the ZFO nanoparticles without secondary structures. By revealing kinetic parameters through combined spectroscopic measurements and electrochemical techniques, our study manifests increased lithium-ion diffusion coefficients, higher capacitive charge storage contribution and reduced charge transfer impedance in holey nanosheets compared to randomly aggregated nanoparticles. Furthermore, our results promote deeper understanding of significantly enhanced electrochemical energy storage properties of these 2D holey nanoarchitectured electrodes resulted from more uniform and complete phase transformation and better active material utilization.

25 ENERGY STORAGE↗
DOE OSTI2018

Multiscale convergence properties for spectral approximations of a model kinetic equation

Here in this work, we prove rigorous convergence properties for a semi-discrete, moment-based approximation of a model kinetic equation in one dimension. This approximation is equivalent to a standard spectral method in the velocity variable of the kinetic distribution and, as such, is accompanied by standard algebraic estimates of the form N -q , where N is the number of modes and q > 0 depends on the regularity of the solution. However, in the multiscale setting, the error estimate can be expressed in terms of the scaling parameter ϵ, which measures the ratio of the mean-free-path to the characteristic domain length. We show that, for isotropic initial conditions, the error in the spectral approximation is $\mathcal{O}$($ϵ^{N+1}$). More surprisingly, the coefficients of the expansion satisfy super convergence properties. In particular, the error of the ℓ th coefficient of the expansion scales like $\mathcal{O}$($ϵ^{2N}$ ) when ℓ = 0 and $\mathcal{O}$($ϵ^{2N+2-ℓ}$ ) for all 1 ≤ ℓ ≤ N. This result is significant, because the low-order coefficients correspond to physically relevant quantities of the underlying system. All the above estimates involve constants depending on N, the time t, and the initial condition. We investigate specifically the dependence on N, in order to assess whether increasing N actually yields an additional factor of ϵ in the error. Numerical tests will also be presented to support the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Linking stem rehydration kinetics to hydraulic traits using a novel method and mechanistic model

Background: Despite the recognized importance of hydraulic capacitance as a mechanism used by plants to maintain hydraulic functioning during high transpiration, characterizing the dynamics of capacitance remains a challenge. Methods: For this work, we used a novel ‘two-balance method’ to investigate relationships between stem rehydration kinetics and other hydraulic traits in multiple tree species, and we developed a model to explore stem rehydration kinetics further. Key Results: We found that: (1) rehydration time constants and the amount of water uptake occurring during rehydration differed significantly across species; (2) time constants did not change with declining water potential (Ψ), while water uptake increased at lower Ψ in some species; (3) longer time constants were associated with lower wood density, higher capacitance and less negative stem pressures causing 50 % loss of hydraulic conductivity (P 50 ); (4) greater water uptake occurred in stems with lower wood density and less negative P 50 values; and (5) the model could estimate the total hydraulic resistance of the rehydration path, which cannot be measured directly. Conclusions: Overall, the two-balance method can be used to examine rehydration dynamics quickly and thoroughly in detached woody stems. This method has the potential to improve our understanding of how capacitance functions across tree species, which is an often-overlooked component of whole-plant hydraulics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Interfacial mixing in high-energy-density matter with a multiphysics kinetic model

We have extended here a recently developed multispecies, multitemperature Bhatnagar-Gross-Krook model [Haack et al., J. Stat. Phys. 168, 822 (2017)], to include multiphysics capabilities that enable modeling of a wider range of physical conditions. In terms of geometry, we have extended from the spatially homogeneous setting to one spatial dimension. In terms of the physics, we have included an atomic ionization model, accurate collision physics across coupling regimes, self-consistent electric fields, and degeneracy in the electronic screening. We apply the model to a warm dense matter scenario in which the ablator-fuel interface of an inertial confinement fusion target is heated, but for larger length and time scales and for much higher temperatures than can be simulated using molecular dynamics. Relative to molecular dynamics, the kinetic model greatly extends the temperature regime and the spatiotemporal scales over which we are able to model. In our numerical results we observe hydrogen from the ablator material jetting into the fuel during the early stages of the implosion and compare the relative size of various diffusion components (Fickean diffusion, electrodiffusion, and barodiffusion) that drive this process. We also examine kinetic effects, such as anisotropic distributions and velocity separation, in order to determine when this problem can be described with a hydrodynamic model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Neutron scattering from myelin revisited: bilayer asymmetry and water-exchange kinetics

The structure of internodal myelin in the rodent central and peripheral nervous systems has been determined using neutron diffraction. The kinetics of water exchange in these tissues is also described. Rapid nerve conduction in the central and peripheral nervous systems (CNS and PNS, respectively) of higher vertebrates is brought about by the ensheathment of axons with myelin, a lipid-rich, multilamellar assembly of membranes. The ability of myelin to electrically insulate depends on the regular stacking of these plasma membranes and on the presence of a number of specialized membrane-protein assemblies in the sheath, including the radial component, Schmidt–Lanterman incisures and the axo–glial junctions of the paranodal loops. The disruption of this fine-structure is the basis for many demyelinating neuropathies in the CNS and PNS. Understanding the processes that govern myelin biogenesis, maintenance and destabilization requires knowledge of myelin structure; however, the tight packing of internodal myelin and the complexity of its junctional specializations make myelin a challenging target for comprehensive structural analysis. This paper describes an examination of myelin from the CNS and PNS using neutron diffraction. This investigation revealed the dimensions of the bilayers and aqueous spaces of myelin, asymmetry between the cytoplasmic and extracellular leaflets of the membrane, and the distribution of water and exchangeable hydrogen in internodal multilamellar myelin. It also uncovered differences between CNS and PNS myelin in their water-exchange kinetics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2024

Ignition Delay Times and Chemical Kinetic Model Validation for Hydrogen and Ammonia Blending With Natural Gas at Gas Turbine Relevant Conditions

Ignition delay times from undiluted mixtures of natural gas (NG)/H 2 /Air and NG/NH 3 /Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000 and 1500 K near a constant pressure of 25 bar. As mentioned, mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data are compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H 2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH 3 fuel addition made no noticeable difference in ignition time. NG/NH 3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis. Here, the reaction CH 3 + O 2 = CH 3 O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Surface structure and surface kinetics of InN grown by plasma-assisted atomic layer epitaxy: A HREELS study

The surface bonding configuration and kinetics of hydrogen desorption from InN grown by plasma-assisted atomic layer epitaxy have been investigated. High resolution electron energy loss spectra exhibited loss peaks assigned to a Fuchs–Kliewer surface phonon, N-N and N-H surface species. The surface N-N vibrations are attributed to surface defects. The observation of N-H but no In-H surface species suggested N-terminated InN. Isothermal desorption data were best fit by the first-order desorption kinetics with an activation energy of (0.88 ± 0.06) eV and pre-exponential factor of (1.5 ± 0.5) × 10{sup 5 }s{sup −1}.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Hydrogen desorption kinetics for aqueous hydrogen fluoride and remote hydrogen plasma processed silicon (001) surfaces

The desorption kinetics of molecular hydrogen (H{sub 2}) from silicon (001) surfaces exposed to aqueous hydrogen fluoride and remote hydrogen plasmas were examined using temperature programmed desorption. Multiple H{sub 2} desorption states were observed and attributed to surface monohydride (SiH), di/trihydride (SiH{sub 2/3}), and hydroxide (SiOH) species, subsurface hydrogen trapped at defects, and hydrogen evolved during the desorption of surface oxides. The observed surface hydride species were dependent on the surface temperature during hydrogen plasma exposure with mono, di, and trihydride species being observed after low temperature exposure (150 °C), while predominantly monohydride species were observed after higher temperature exposure (450 °C). The ratio of surface versus subsurface H{sub 2} desorption was also found to be dependent on the substrate temperature with 150 °C remote hydrogen plasma exposure generally leading to more H{sub 2} evolved from subsurface states and 450 °C exposure leading to more H{sub 2} desorption from surface SiH{sub x} species. Additional surface desorption states were observed, which were attributed to H{sub 2} desorption from Si (111) facets formed as a result of surface etching by the remote hydrogen plasma or aqueous hydrogen fluoride treatment. The kinetics of surface H{sub 2} desorption were found to be in excellent agreement with prior investigations of silicon surfaces exposed to thermally generated atomic hydrogen.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Kinetics of magnetization reversal in a heterophase nanomagnet with spatially modulated anisotropy

Magnetization reversal modes in a thin-film NiFeCuMo ferromagnet (FM) with periodically varying in-plane anisotropy are studied by the magneto-optical indicator film (MOIF) technique. The uni-directional anisotropy in FM regions exchange-coupled to a FeMn antiferromagnet (AFM) film in the form of square mesh stripes is alternated by the uniaxial anisotropy in the FM regions inside this mesh. It is shown that the boundaries formed along the edges of these stripes, which separate FM regions with different anisotropy, crucially influence the kinetics of domain-structure transformation in both types of FM regions. It is established that the lateral exchange anisotropy in the ferromagnet, which is determined by the stabilization of the spin distribution in the FM layer along the FM-(FM/AFM) interface, leads to the asymmetry of the magnetization reversal in FM regions bordered with an FM/AFM structure. Anisotropy of the mobility of 180-degree “charged” and “uncharged” domain walls situated, respectively, perpendicular and parallel to the unidirectional anisotropy axis is revealed. The difference observed between the mobilities of charged and uncharged domain walls is attributed to the difference in the spin distribution in these walls with respect to the unidirectional anisotropy axis and is a key factor for the difference between the magnetization reversal kinetics in horizontal and vertical exchange-biased FM stripes. Drastic differences are revealed in the asymmetry of magnetization reversal processes in mutually perpendicular narrow stripes of FM/AFM structures. Possible mechanisms of magnetization reversal in low-dimensional FM-(FM/AFM) heterostructures are discussed with regard to the effect of domain walls localized on the edges of AFM layers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗