Thermal Jamming of Ions in the Superionic State of UO2

MRS Advances ◽  
2018 ◽  
Vol 3 (31) ◽  
pp. 1777-1781 ◽  
Author(s):  
Dillon Sanders ◽  
Jacob Eapen
Keyword(s):  
Hard Sphere ◽  
Atomistic Simulations ◽  
Dynamical Heterogeneity ◽  
Oxygen Ions ◽  
Superionic State ◽  
Simulation Results ◽  
Characteristic Features ◽  
Low Dimensional ◽  
Superionic Conduction ◽  
Jammed State

ABSTRACTThe oxygen ions in the high temperature superionic state of uranium dioxide (UO2) are known to be in an arrested or jammed state, exhibiting characteristic features of jammed kinetics such as low dimensional string-like ion hopping and dynamical heterogeneity (DH). This thermally-jammed state entails a configurational entropic cost. Using atomistic simulations and the 2PT method, we compute the solid-like (vibrational) and hard sphere-like (configurational) contributions to the total entropy across a temperature range of 1500 K to 2800 K that envelop both the onset of superionic conduction (2000 K) and the second order λ-transition (2610 K). To properly account for the thermally jammed state of the ions, we use an equation of state that is appropriate for the metastable fluid branch. Our simulation results are in excellent agreement with the entropy data extracted from specific heat experiments with a mean error of less than 2%.

SIMULATION AND MODELING OF EVOKED RESPONSE ELECTROENCEPHALOGRAPH SIGNAL

1999 ◽  
Vol 10 (04) ◽  
pp. 759-776
Author(s):  
D. R. KULKARNI ◽  
J. C. PARIKH ◽  
R. PRATAP
Keyword(s):  
Small Range ◽  
Eeg Signal ◽  
Simulation And Modeling ◽  
State Space Reconstruction ◽  
Eyes Closed ◽  
Normal Individuals ◽  
Eeg Data ◽  
Closed Data ◽  
Simulation Results ◽  
Low Dimensional

Electroencephalograph (EEG) data for normal individuals with eyes-closed and under stimuli is analyzed. The stimuli consisted of photo, audio, motor and mental activity. We use several measures from nonlinear dynamics to analyze and characterize the data. We find that the dynamics of the EEG signal is deterministic and chaotic but it is not a low dimensional chaotic system. The evoked responses lead to a redistribution of strengths relative to eyes-closed data. Basically, strength in α waves decreases whereas that in β wave increases. We also carried out simulations separately and in combination for δ, θ, α and β waves to understand the data. From the simulation results, it appears that the characteristics of EEG data are consequences of filtering the data with a relatively small range of frequency (0.5–32 Hz). In view of this, we believe that calculation of known nonlinear measures is not likely to be very useful for studying the dynamics of EEG data. We have also successfully modeled the EEG time series using the concept of state space reconstruction in the framework of artificial neural network. It gives us confidence that one would be able to understand, in a more basic way, how collectivity in EEG signal arises.

scholarly journals An Order-Independent Algorithm for Learning Chain Graphs

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Mohammad Ali Javidian ◽  
Marco Valtorta ◽  
Pooyan Jamshidi
Keyword(s):  
Directed Acyclic Graphs ◽  
High Dimensional ◽  
P Values ◽  
Order Dependence ◽  
Error Measures ◽  
Acyclic Graphs ◽  
Simulation Results ◽  
Improved Performance ◽  
Low Dimensional ◽  
Chain Graphs

LWF chain graphs combine directed acyclic graphs and undirected graphs. We propose a PC-like algorithm, called PC4LWF, that finds the structure of chain graphs under the faithfulness assumption to resolve the problem of scalability of the proposed algorithm by Studeny (1997). We prove that PC4LWF is order dependent, in the sense that the output can depend on the order in which the variables are given. This order dependence can be very pronounced in high-dimensional settings. We propose two modifications of the PC4LWF algorithm that remove part or all of this order dependence. Simulation results with different sample sizes, network sizes, and p-values demonstrate the competitive performance of the PC4LWF algorithms in comparison with the LCD algorithm proposed by Ma et al. (2008) in low-dimensional settings and improved performance (with regard to error measures) in high-dimensional settings.

Solvation force in a hard-sphere fluid

1999 ◽  
Vol 77 (8) ◽  
pp. 585-590 ◽  
Author(s):  
M Moradi ◽  
M Kavosh Tehrani
Keyword(s):  
Correlation Function ◽  
Hard Sphere ◽  
Hard Core ◽  
Spherical Approximation ◽  
Mean Spherical Approximation ◽  
Direct Correlation Function ◽  
Functional Theory ◽  
Hard Sphere Fluid ◽  
Generalized Mean ◽  
Simulation Results

The solvation force in a hard-sphere fluid is obtained by the denisty functional theory proposed by Rickayzen and Augousti. The direct correlation function (DCF) with the tail introduced by Tang and Lu is used. This DCF (hereafter TL DCF ) is postulated to hold the Yukawa form outside the hard core; and the generalized mean spherical approximation (GMSA) approach has been applied. The results are compared with those obtained by using the Percus-Yevick (PY) DCF. These results are also compared with those of Monte Carlo simulations. At low densities and fairly high densities the results are in agreement. But at high densities there is more oscillation in the solvation force obtained by using TL DCF in comparison with the PY DCF. There are no simulation results at high densities to be compared with these results.PACS No. 61.20

Study of Nanocutting Using Atomic Model

2008 ◽  
Vol 33-37 ◽  
pp. 963-968
Author(s):  
Chun Yi Chu ◽  
Chung Ming Tan ◽  
Yung Chuan Chiou
Keyword(s):  
Molecular Dynamics ◽  
Energy Minimization ◽  
Atomic Scale ◽  
Scale Model ◽  
Atomistic Simulations ◽  
Cutting Depth ◽  
Cutting Deformation ◽  
Simulation Results ◽  
Model Approach

The stress induced in a workpiece under nanocutting are analyzed by an atomic-scale model approach that is based on the energy minimization. Certain aspects of the deformation evolution during the process of nanocutting are addressed. This method needs less computational efforts than traditional molecular dynamics (MD) calculations. The simulation results demonstrate that the microscopic cutting deformation mechanism in the nanocutting process can be regarded as the instability of the crystalline structure in our atomistic simulations and the surface quality of the finished workpiece varies with the cutting depth.

Study of Niobium Diffusion and Clusterization in hcp Zr-Nb Dilute Alloys

2017 ◽  
Vol 375 ◽  
pp. 167-174 ◽  
Author(s):  
Daria Smirnova ◽  
Sergey Starikov
Keyword(s):  
Cluster Size ◽  
Cluster Formation ◽  
Atomistic Simulations ◽  
Octahedral Position ◽  
Niobium Atom ◽  
Self Diffusion ◽  
Dilute Alloys ◽  
Simulation Results

We perform atomistic simulations aimed on study of diffusion of constituents and niobium precipitation in hcp Zr-Nb. We report diffusivities of Zr and Nb in hcp Zr-Nb alloys computed for the models containing up to 5 at.% of niobium. The calculated diffusivity of niobium rises with increase of its content in the alloy. The simulations also show that for a studied concentration range addition of niobium slightly enhances self-diffusion of zirconium in the alloys. The work is also devoted to description of niobium incorporation and clusterization in hcp zirconium. It is confirmed that for a single niobium atom incorporated in hcp zirconium lattice the octahedral position is the most favorable. We estimated the energy describing niobium cluster formation in pure hcp zirconium. According to the simulation results, we can suggest that the minimum niobium cluster size that can be expected in hcp Zr corresponds to about 80 atoms.

Understanding ion beam synthesis of nanostructures: Modeling and atomistic simulations

2000 ◽  
Vol 647 ◽  
Author(s):  
M. Strobel ◽  
K.-H. Heinig ◽  
W. Möller
Keyword(s):  
Ion Implantation ◽  
Ion Beam ◽  
Monte Carlo Model ◽  
Atomistic Simulations ◽  
Ion Energy ◽  
Lattice Monte Carlo ◽  
Supersaturated Solid Solutions ◽  
Ion Beam Synthesis ◽  
Thermodynamic Effects ◽  
Low Dimensional

AbstractIon implantation, specified by parameters like ion energy, ion fluence, ion flux and sub-strate temperature, has become a well-established tool to synthesize buried low-dimensional nanostructures. In general, in ion beam synthesis the evolution of nanostructures is determined by the competition between ballistic and thermodynamic effects. A kinetic 3D lattice Monte-Carlo model is introduced, which allows for a proper incorporation of collisional mixing and phase separation within supersaturated solid-solutions. It is shown, that for both the ballistically and thermodynamically dominated regimes, the Gibbs-Thomson relation is the key ingredient in understanding nanocluster evolution. Various aspects of precipitate evolution during implantation, formation of ordered arrays of nanophase domains by focused ion implantation and compound nanocluster synthesis are discussed.

New Approximate Analytical Formula for the Solute-Solvent Contact Distribution Function in an Infinitely Dilute Binary Hard-Sphere Mixture

2008 ◽  
Vol 73 (3) ◽  
pp. 314-321 ◽  
Author(s):  
Stanislav Labík ◽  
William R. Smith
Keyword(s):  
Distribution Function ◽  
Hard Sphere ◽  
Pair Distribution Function ◽  
Analytical Formula ◽  
Diameter Ratio ◽  
Scaled Particle Theory ◽  
Perfect Agreement ◽  
Simulation Results ◽  
Contact Distribution ◽  
Contact Distribution Function

A new analytical expression for the contact value of the solute-solvent pair distribution function of a binary hard-sphere mixture at infinite dilution is proposed, based on scaled-particle-theory-like arguments. For high solute-solvent diameter ratio it predicts perfect agreement with the simulation results.

EQUATION OF STATE AND FREEZING OF GMSA HARD SPHERES

2003 ◽  
Vol 17 (31n32) ◽  
pp. 6057-6065 ◽  
Author(s):  
M. MORADI ◽  
H. SHAHRI
Keyword(s):  
Equation Of State ◽  
Hard Sphere ◽  
Density Functional ◽  
Hard Spheres ◽  
Spherical Approximation ◽  
Mean Spherical Approximation ◽  
Direct Correlation Function ◽  
Generalized Mean ◽  
Simulation Results ◽  
Good Agreement

The modified-weighted-density-functional approximation (MWDA) proposed by Denton and Ashcroft, is applied to study the equation of sate and freezing of the hard spheres using the generalized mean spherical approximation (GMSA) direct correlation function (DCF). Because of the attractive tail in the DCF, the perturbation method similar to that introduced by Yoon and Kim is applied. The free energy, freezing parameters and the equation of state of the hard sphere FCC crystal are obtained. The results are compared with some other previous theories and Monte Carlo simulation. Our results are in good agreement with the simulation results.

Using Space-Time Correlations to Identify Transient Defects

MRS Advances ◽  
2018 ◽  
Vol 3 (31) ◽  
pp. 1755-1760
Author(s):  
William Lowe ◽  
Jacob Eapen
Keyword(s):  
Dynamical Behavior ◽  
Atomistic Simulations ◽  
Dynamic Tension ◽  
Time Resolved ◽  
Scale Free ◽  
Self Organized ◽  
Time Correlations ◽  
Simulation Results ◽  
Early Radiation ◽  
Cubic Silicon Carbide

ABSTRACTAtomistic simulations are employed to investigate the dynamical behavior of atoms in cubic silicon carbide (SiC) following a 5 keV radiation knock. Specifically, we have computed the time-resolved van Hove self-correlation function, Gs(r,t), separately for the silicon and carbon sub-lattices. Our goal is to probe the early radiation damage mechanisms using a dynamical methodology. The simulation results show that the carbon atoms engage in a dynamic hopping mechanism as the system recovers from the radiation knock. The silicon atoms, however, exhibit a strikingly different behaviour: the time variation of 4πr2Gs(r,t) indicates a dynamic tension between the crystalline and disordered regions of the Si sub-lattice. The power-law tail of the 4πr2Gs(r,t) correlation for silicon atoms suggests a scale-free self-organized critical (SOC) state – a possible precursor to the collapse of the Si sub-lattice.

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