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Gerard T. Barkema

Publications and source records attributed to Gerard T. Barkema.

At least 19 recordsLinked to original sources

Dynamical critical behavior of the two-dimensional three-state Potts model

We investigate the dynamical critical behavior of the two-dimensional three-state Potts model with single spin-flip dynamics in equilibrium. We focus on the mean-squared deviation of the magnetization $M$ (MSD$_{M}$) as a function of time, as well as on the autocorrelation function of $M$. Our simulations reveal the existence of two crossover behaviors at times $τ_1 \sim L^{z_1}$ and $τ_2 \sim L^{z_2}$, separating three dynamical regimes. MSD$_{M}$ appears to shift from ordinary diffusion in the first regime, to anomalous diffusion in the second, and finally to be constant in the third regime. The magnetization autocorrelation function on the other hand is found to fluctuate between exponential decay, stretched-exponential decay, and then again exponential decay along these three regimes. This behavior is in agreement with the one reported recently for the two-dimensional Ising ferromagnet [Phys. Rev. E {\bf 108}, 034118 (2023)], indicating that the existence of two dynamic critical exponents is not a peculiarity of the Ising model itself. A comparison of both MSD$_{M}$ and the magnetization's autocorrelation function suggests that within our numerical accuracy the exponents $z_1$ and $z_2$ are shared between the Ising and three-state Potts models at least for the particular case of single spin-flip dynamics studied here, even though their equilibrium universality classes are clearly distinct. Continuity of MSD$_{M}$ requires that $α(z_2 - z_1) = γ/ν- z_1$, in which $α$ is the anomalous exponent in the intermediate regime. Since the ratio $γ/ν$ is not shared between the two models, it follows that $α$ is not shared either, an aspect well verified in our simulations. Finally, we also discuss the relevance of our main findings using another useful observable, namely the line magnetization $M_{l}$.

cond-mat.stat-mech

Structural dynamics of a model of amorphous silicon

We perform extensive simulations and systematic statistical analyses of the structural dynamics of amorphous silicon. The simulations follow the dynamics introduced by Wooten, Winer and Weaire: the energy is obtained with the Keating potential, and the dynamics consists of bond transpositions proposed at random locations and accepted with the Metropolis acceptance ratio. The structural quantities we track are the variations in time of the lateral lengths ($L_x$,$L_y$,$L_z$) of the cuboid simulation cell. We transform these quantities into the volume $V$ and two aspect ratios $B_1$ and $B_2$. Our analysis reveals that at short times, the mean squared displacement (MSD) for all of them exhibits normal diffusion. At longer times, they cross over to anomalous diffusion, with a temperature-dependent anomalous exponent $α<1$. We analyze our findings in the light of two standard models in statistical physics that feature anomalous dynamics, $viz.$, continuous time random walker (CTRW) and fractional Brownian motion (fBm). We obtain the distribution of waiting times, and find that the data are consistent with a stretched-exponential decay. We also show that the three quantities, $V$, $B_1$ and $B_2$ exhibit negative velocity autocorrelation functions. These observations together suggest that the dynamics of the material belong to the fBm class.

cond-mat.soft

Domain coarsening in polycrystalline graphene

Graphene is a two-dimensional carbon material which exhibits exceptional properties, making it highly suitable for a wide range of applications. Practical graphene fabrication often yields a polycrystalline structure with many inherent defects, which significantly influence its performance. In this study, we utilize a Monte Carlo approach based on the optimized Wooten, Winer and Weaire (WWW) algorithm to simulate the crystalline domain coarsening process of polycrystalline graphene. Our sample configurations show excellent agreement with experimental data. We conduct statistical analyses of the bond and angle distribution, temporal evolution of the defect distribution, and spatial correlation of the lattice orientation that follows a stretched exponential distribution. Furthermore, we thoroughly investigate the diffusion behavior of defects and find that the changes in domain size follow a power-law distribution. We briefly discuss the possible connections of these results to (and differences from) domain growth processes in other statistical models, such as the Ising dynamics. We also examine the impact of buckling of polycrystalline graphene on the crystallization rate under substrate effects. Our findings may offer valuable guidance and insights for both theoretical investigations and experimental advancements.

cond-mat.dis-nn

Critical dynamical behavior of the Ising model

We investigate the dynamical critical behavior of the two- and three-dimensional Ising model with Glauber dynamics in equilibrium. In contrast to the usual standing, we focus on the mean-squared deviation of the magnetization $M$, MSD$_M$, as a function of time, as well as on the autocorrelation function of $M$. These two functions are distinct but closely related. We find that MSD$_M$ features a first crossover at time $τ_1 \sim L^{z_{1}}$, from ordinary diffusion with MSD$_M$ $\sim t$, to anomalous diffusion with MSD$_M$ $\sim t^α$. Purely on numerical grounds, we obtain the values $z_1=0.45(5)$ and $α=0.752(5)$ for the two-dimensional Ising ferromagnet. Related to this, the magnetization autocorrelation function crosses over from an exponential decay to a stretched-exponential decay. At later times, we find a second crossover at time $τ_2 \sim L^{z_{2}}$. Here, MSD$_M$ saturates to its late-time value $\sim L^{2+γ/ν}$, while the autocorrelation function crosses over from stretched-exponential decay to simple exponential one. We also confirm numerically the value $z_{2}=2.1665(12)$, earlier reported as the single dynamic exponent. Continuity of MSD$_M$ requires that $α(z_{2}-z_{1})=γ/ν-z_1$. We speculate that $z_{1} = 1/2$ and $α= 3/4$, values that indeed lead to the expected $z_{2} = 13/6$ result. A complementary analysis for the three-dimensional Ising model provides the estimates $z_{1} = 1.35(2)$, $α=0.90(2)$, and $z_{2} = 2.032(3)$. While $z_{2}$ has attracted significant attention in the literature, we argue that for all practical purposes $z_{1}$ is more important, as it determines the number of statistically independent measurements during a long simulation.

cond-mat.stat-mech

Structural dynamics of polycrystalline graphene

The exceptional properties of the two-dimensional material graphene make it attractive for multiple functional applications, whose large-area samples are typically polycrystalline. Here, we study the mechanical properties of graphene in computer simulations and connect these to the experimentally relevant mechanical properties. In particular, we study the fluctuations in the lateral dimensions of the periodic simulation cell. We show that over short time scales, both the area A and the aspect ratio B of the rectangular periodic box show diffusive behavior under zero external field during dynamical evolution, with diffusion coefficients DA and DB that are related to each other. At longer times, fluctuations in A are bounded, while those in B are not. This makes the direct determination of DB much more accurate, from which DA can then be derived indirectly. We then show that the dynamic behavior of polycrystalline graphene under external forces can also be derived from DA and DB via the Nernst-Einstein relation. Additionally, we study how the diffusion coefficients depend on structural properties of the polycrystalline graphene, in particular, the density of defects.

cond-mat.mtrl-sci

A comparison of cluster algorithms for the bond-diluted Ising model

Monte Carlo cluster algorithms are popular for their efficiency in studying the Ising model near its critical temperature. We might expect that this efficiency extends to the bond-diluted Ising model. We show, however, that this is not always the case by comparing how the correlation times $τ_w$ and $τ_{\rm sw}$ of the Wolff and Swendsen-Wang cluster algorithms scale as a function of the system size $L$ when applied to the two-dimensional bond-diluted Ising model. We demonstrate that the Wolff algorithm suffers from a much longer correlation time than in the pure Ising model, caused by isolated (groups of) spins which are infrequently visited by the algorithm. With a simple argument we prove that these cause the correlation time $τ_w$ to be bounded from below by $L^{z_w}$ with a dynamical exponent $z_w=γ/ ν\approx 1.75$ for a bond concentration $p < 1$. Furthermore, we numerically show that this lower bound is actually taken for several values of $p$ in the range $0.5 < p < 1$. Moreover, we show that the Swendsen-Wang algorithm does not suffer from the same problem. Consequently, it has a much shorter correlation time, shorter than in the pure Ising model even. Numerically at $p = 0.6$, we find that its dynamical exponent is $z_{\rm sw} = 0.09(4)$.

cond-mat.stat-mech

Dynamic Sampling from a Discrete Probability Distribution with a Known Distribution of Rates

In this paper, we consider several efficient data structures for the problem of sampling from a dynamically changing discrete probability distribution, where some prior information is known on the distribution of the rates, in particular the maximum and minimum rate, and where the number of possible outcomes N is large. We consider three basic data structures, the Acceptance-Rejection method, the Complete Binary Tree and the Alias method. These can be used as building blocks in a multi-level data structure, where at each of the levels, one of the basic data structures can be used, with the top level selecting a group of events, and the bottom level selecting an element from a group. Depending on assumptions on the distribution of the rates of outcomes, different combinations of the basic structures can be used. We prove that for particular data structures the expected time of sampling and update is constant when the rate distribution follows certain conditions. We show that for any distribution, combining a tree structure with the Acceptance-Rejection method, we have an expected time of sampling and update of $O\left(\log\log{r_{max}}/{r_{min}}\right)$ is possible, where $r_{max}$ is the maximum rate and $r_{min}$ the minimum rate. We also discuss an implementation of a Two Levels Acceptance-Rejection data structure, that allows expected constant time for sampling, and amortized constant time for updates, assuming that $r_{max}$ and $r_{min}$ are known and the number of events is sufficiently large. We also present an experimental verification, highlighting the limits given by the constraints of a real-life setting.

cs.CE

Super slowing down in the bond-diluted Ising model

In models in statistical physics, the dynamics often slows down tremendously near the critical point. Usually, the correlation time $τ$ at the critical point increases with system size $L$ in power-law fashion: $τ\sim L^z$, which defines the critical dynamical exponent $z$. We show that this also holds for the 2D bond-diluted Ising model in the regime $p>p_c$, where $p$ is the parameter denoting the bond concentration, but with a dynamical critical exponent $z(p)$ which shows a strong $p$-dependence. Moreover, we show numerically that $z(p)$, as obtained from the autocorrelation of the total magnetisation, diverges when the percolation threshold $p_c=1/2$ is approached: $z(p)-z(1) \sim (p-p_c)^{-2}$. We refer to this observed extremely fast increase of the correlation time with size as {\it super slowing down}. Independent measurement data from the mean-square deviation of the total magnetisation, which exhibits anomalous diffusion at the critical point, supports this result.

cond-mat.stat-mech

Discontinuous evolution of the structure of stretching polycrystalline graphene

Polycrystalline graphene has an inherent tendency to buckle, i.e. develop out-of-plane, three-dimensional structure. A force applied to stretch a piece of polycrystalline graphene influences the out-of-plane structure. Even if the graphene is well-relaxed, this happens in non-linear fashion: occasionally, a tiny increase in stretching force induces a significant displacement, in close analogy to avalanches, which in turn can create vibrations in the surrounding medium. We establish this effect in computer simulations: by continuously changing the strain, we follow the displacements of the carbon atoms that turn out to exhibit a discontinuous evolution. Furthermore, the displacements exhibit a hysteretic behavior upon the change from low to high stress and back. These behaviors open up a new direction in studying dynamical elasticity of polycrystalline quasi-two-dimensional systems, and in particular the implications on their mechanical and thermal properties.

cond-mat.mtrl-sci

Critical Dynamical Exponent of the Two-Dimensional Scalar $ϕ^4$ Model with Local Moves

We study the scalar one-component two-dimensional (2D) $ϕ^4$ model by computer simulations, with local Metropolis moves. The equilibrium exponents of this model are well-established, e.g. for the 2D $ϕ^4$ model $γ= 1.75$ and $ν= 1$. The model has also been conjectured to belong to the Ising universality class. However, the value of the critical dynamical exponent $z_c$ is not settled. In this paper, we obtain $z_c$ for the 2D $ϕ^4$ model using two independent methods: (a) by calculating the relative terminal exponential decay time $τ$ for the correlation function $\langle ϕ(t)ϕ(0)\rangle$, and thereafter fitting the data as $τ\sim L^{z_c}$, where $L$ is the system size, and (b) by measuring the anomalous diffusion exponent for the order parameter, viz., the mean-square displacement (MSD) $\langle Δϕ^2(t)\rangle\sim t^c$ as $c=γ/(νz_c)$, and from the numerically obtained value $c\approx 0.80$, we calculate $z_c$. For different values of the coupling constant $λ$, we report that $z_c=2.17\pm0.03$ and $z_c=2.19\pm0.03$ for the two methods respectively. Our results indicate that $z_c$ is independent of $λ$, and is likely identical to that for the 2D Ising model. Additionally, we demonstrate that the Generalised Langevin Equation (GLE) formulation with a memory kernel, identical to those applicable for the Ising model and polymeric systems, consistently capture the observed anomalous diffusion behavior.

cond-mat.stat-mech

Generalised Langevin Equation Formulation for Anomalous Diffusion in the Ising Model at the Critical Temperature

We consider the two- (2D) and three-dimensional (3D) Ising model on a square lattice at the critical temperature $T_c$, under Monte-Carlo spin flip dynamics. The bulk magnetisation and the magnetisation of a tagged line in the 2D Ising model, and the bulk magnetisation and the magnetisation of a tagged plane in the 3D Ising model exhibit anomalous diffusion. Specifically, their mean-square displacement increases as power-laws in time, collectively denoted as $\sim t^c$, where $c$ is the anomalous exponent. We argue that the anomalous diffusion in all these quantities for the Ising model stems from time-dependent restoring forces, decaying as power-laws in time --- also with exponent $c$ --- in striking similarity to anomalous diffusion in polymeric systems. Prompted by our previous work that has established a memory-kernel based Generalised Langevin Equation (GLE) formulation for polymeric systems, we show that a closely analogous GLE formulation holds for the Ising model as well. We obtain the memory kernels from spin-spin correlation functions, and the formulation allows us to consistently explain anomalous diffusion as well as anomalous response of the Ising model to an externally applied magnetic field in a consistent manner.

cond-mat.stat-mech

Rupture of amorphous graphene via void formation

Apart from its unique and exciting electronic properties, many sensor based applications of graphene are purely based on its mechanical and structural properties. Here we report a numerical and analytical study of a void in amorphous (small domain polycrystalline) graphene, and show that the energetics of a void is a balance between the line tension cost versus the increased area gain. Using the concepts of classical nucleation theory, we show that the critical radius of a void formed in amorphous graphene at constant pressure is simply the ratio of line tension at the void and the applied pressure. The values of the critical radius of the void for flat and buckled graphene are 3.48Å~and 3.31Å, respectively at 2 eV/Å${^2}$ pressure. We also show that the dominant finite size correction to the line tension is inversely proportional to the radius of the void in both flat and buckled cases. Contrary to conventional wisdom, with the help of a simple analytical model we find that the shear modulus sets the lower limit of the line tension in the samples. This makes our study relevant for other two-dimensional amorphous materials such as h-BN, phosphorene, borophene, and transition metal dichalcogenides. Our results are useful for the better understanding of polycrystalline graphene under tension and therefore have direct implications on the very fascinating field of strain engineering known as "straintronics" to manipulate or improve graphene's properties.

cond-mat.mtrl-sci

Exact enumeration of self-avoiding walks on BCC and FCC lattices

Self-avoiding walks on the body-centered-cubic (BCC) and face-centered-cubic (FCC) lattices are enumerated up to lengths 28 and 24, respectively, using the length-doubling method. Analysis of the enumeration results yields values for the exponents $γ$ and $ν$ which are in agreement with, but less accurate than those obtained earlier from enumeration results on the simple cubic lattice. The non-universal growth constant and amplitudes are accurately determined, yielding for the BCC lattice $μ=6.530520(20)$, $A=1.1785(40)$, and $D=1.0864(50)$, and for the FCC lattice $μ=10.037075(20)$, $A=1.1736(24)$, and $D=1.0460(50)$.

cond-mat.stat-mech

Structural characterization of carbon nanotubes via the vibrational density of states

The electrical and chemical properties of carbon nanotubes vary significantly with different chirality and diameter, making the experimental determination of these structural properties important. Here, we show that the vibrational density of states (VDOS) contains information on the structure of carbon nanotubes, particularly at low frequencies. We show that the diameter and chirality of the nanotubes can be determined from the characteristic low frequency $L$ and $L'$ modes in the VDOS. For zigzag nanotubes, the $L$ peak splits into two peaks giving rise to another low energy $L"$ peak. The significant changes in the frequencies and relative intensities of these peaks open up a route to distinguish among structurally different nanotubes. A close study of different orientations of Stone-Wales defects with varying defect density reveals that different structural defects also leave distinct fingerprints in the VDOS, particularly in the $L$ and $L'$ modes. With our results, more structural information can be obtained from experiments which can directly measure the VDOS, such as inelastic electron and inelastic neutron spectroscopy.

cond-mat.mtrl-sci

Probing the Shape of a Graphene Nanobubble

Gas molecules trapped between graphene and various substrates in the form of bubbles are observed experimentally. The study of these bubbles is useful in determining the elastic and mechanical properties of graphene, adhesion energy between graphene and substrate, and manipulating the electronic properties via strain engineering. In our numerical simulations, we use a simple description of elastic potential and adhesion energy to show that for small gas bubbles ($\sim 10$ nm) the van der Waals pressure is in the order of 1 GPa. These bubbles show universal shape behavior irrespective of their size, as observed in recent experiments. With our results the shape and volume of the trapped gas can be determined via the vibrational density of states (VDOS) using experimental techniques such as inelastic tunneling and inelastic neutron scattering. The elastic energy distribution in the graphene layer which traps the nanobubble is homogeneous apart from its edge, but the strain depends on the bubble size thus variation in bubble size allows control of the electronic and optical properties.

cond-mat.mtrl-sci

Structure of twisted and buckled bilayer graphene

We study the atomic structure of twisted bilayer graphene, with very small mismatch angles ($θ\sim 0.28^0$), a topic of intense recent interest. We use simulations, in which we combine a recently presented semi-empirical potential for single-layer graphene, with a new term for out-of-plane deformations, [Jain et al., J. Phys. Chem. C, 119, 2015] and an often-used interlayer potential [Kolmogorov et al., Phys. Rev. B, 71, 2005]. This combination of potentials is computationally cheap but accurate and precise at the same time, allowing us to study very large samples, which is necessary to reach very small mismatch angles in periodic samples. By performing large scale atomistic simulations, we show that the vortices appearing in the Moiré pattern in the twisted bilayer graphene samples converge to a constant size in the thermodynamic limit. Furthermore, the well known sinusoidal behavior of energy no longer persists once the misorientation angle becomes very small ($θ<1^0$). We also show that there is a significant buckling after the relaxation in the samples, with the buckling height proportional to the system size. These structural properties have direct consequences on the electronic and optical properties of bilayer graphene.

cond-mat.mtrl-sci

Boundaries Determine the Formation Energies of Lattice Defects in Two-Dimensional Buckled Materials

Lattice defects are inevitably present in two-dimensional materials, with direct implications on their physical and chemical properties. We show that the formation energy of a lattice defect in buckled two-dimensional crystals is not uniquely defined as it takes different values for different boundary conditions even in the thermodynamic limit, as opposed to their perfectly planar counterparts. Also, the approach to the thermodynamic limit follows a different scaling: inversely proportional to the logaritm of the system size for buckled materials, rather than the usual power-law approach. In graphene samples of $\sim 1000$ atoms, different boundary conditions can cause differences exceeding 10 eV. Besides presenting numerical evidence in simulations, we show that the universal features in this behavior can be understood with simple bead-spring models. Fundamentally, our findings imply that it is necessary to specify the boundary conditions for the energy of the lattice defects in the buckled two-dimensional crystals to be uniquely defined, and this may explain the lack of agreement in the reported values of formation energies in graphene. We argue that boundary conditions may also have impact on other physical observables such as the melting temperature.

cond-mat.mtrl-sci

Dynamics of a double-stranded DNA segment in a shear flow

We study the dynamics of a double-stranded DNA (dsDNA) segment, as a semiflexible polymer, in a shear flow, the strength of which is customarily expressed in terms of the dimensionless Weissenberg number Wi. Polymer chains in shear flows are well-known to undergo tumbling motion. When the chain lengths are much smaller than the persistence length, one expects a (semiflexible) chain to tumble as a rigid rod. At low Wi, a polymer segment shorter than the persistence length does indeed tumble as a rigid rod. However, for higher Wi the chain does not tumble as a rigid rod, even if the polymer segment is shorter than the persistence length. In particular, from time to time the polymer segment may assume a buckled form, a phenomenon commonly known as Euler buckling. Using a bead-spring Hamiltonian model for extensible dsDNA fragments, we first analyze Euler buckling in terms of the oriented deterministic state (ODS), which is obtained as the steady-state solution of the dynamical equations by turning off the stochastic (thermal) forces at a fixed orientation of the chain. The ODS exhibits symmetry breaking at a critical Weissenberg number Wi$_{\text c}$, analogous to a pitchfork bifurcation in dynamical systems. We then follow up the analysis with simulations and demonstrate symmetry breaking in computer experiments, characterized by a unimodal to bimodal transformation of the probability distribution of the second Rouse mode with increasing Wi. Our simulations reveal that shear can cause strong deformation for a chain that is shorter than its persistence length, similar to recent experimental observations.

cond-mat.soft