Search

Continuous random network (CRN) models are often used as models for elemental and binary tetrahedral semiconductors such as a-Si and a-GaAs. Here, we review algorithms to generate CRN models. We discuss their structural properties and compare with those models obtained via different computational approaches, as well as with experiment. Additionally, we discuss current results towards the generation of para-crystalline models.

Recently there have been attempts to create physically realistic models for para/poly-crystalline silicon (containing randomly oriented c-Si grains embedded in a disordered matrix) by means of empirical molecular dynamics. These models demonstrate acceptable geometrical and vibrational properties but fail to reproduce the correct electronic bandgap due to the presence of numerous "frozen-in" coordination defects. We propose a new procedure for the preparation of more realistic models of paracrystalline silicon based on a modification of the bond-switching method of Wooten, Winer and Weaire. Our new method allows us to create interfaces between the crystalline and disordered phases of Si with no coordination defects. Models with 400, 1000, and 4000 atoms were constructed. All the models have ~10 atomic % of the crystalline phase. The two smaller models contain a single crystalline grain and the largest model contains 4 randomly oriented grains. Our models show good geometrical and vibrational properties compared to good continuous random networks models of a-Si and also display excellent optical properties, correctly reproducing the electronic bandgap of amorphous silicon.

Modifications are proposed to the Stillinger–Weber (SW) potential, an empirical interaction potential for silicon. The modifications are specifically intended to improve the description of the amorphous phase and are obtained by a direct fit to the amorphous structure. The potential is adjusted to reproduce the location of the transverse optic (TO) and transverse acoustic (TA) peaks of the vibrational density of states (VDOS), properties insensitive to the details of experimental preparation. These modifications also lead to excellent agreement with structural properties. Comparison with other empirical potentials shows that amorphous silicon configurations generated with the modified potential have overall better vibrational and structural properties.

Activated processes, i.e., rare events requiring thermal fluctuations many times larger than the average thermal energy, play a central role in controlling the relaxation and diAusion mechanisms of disordered materials such as amorphous and glassy solids, polymers and bio-molecules. As the time scales involved are much longer than those associated with thermal vibrations, these processes cannot be studied eAciently with standard real-space methods such as molecular dynamics (MD). They can be investigated much more eAciently by working in the potential energy space. Instead of defining moves in terms of atomic displacements, the activation‐relaxation technique (ART) follows paths directly in the energy landscape, from local minima to adjacent saddle points, giving full freedom for the system to create events of any complexity. In this paper, we review the technique in detail and present some recent applications to amorphous semiconductors and glasses. ” 2001 Elsevier Science B.V. All rights reserved.

Oil and gas infrastructures are submitted to extreme conditions and off-shore rigs and petrochemical installations require expensive high-quality materials to limit damaging failures. Yet, due to a lack of microscopic understanding, most of these materials are developed and selected based on empirical evidence leading to over-qualified infrastructures. Computational efforts are necessary, therefore, to identify the link between atomistic and macroscopic scales and support the development of better targeted materials for this and other energy industry. As a first step towards understanding carburization and metal dusting, we assess the capabilities of an embedded atom method (EAM) empirical force field as well as those of a ReaxFF force field using two different parameter sets to describe carbon diffusion at the surface of Fe, comparing the adsorption and diffusion of carbon into the 110 surface and in bulk of α-iron with equivalent results produced by density functional theory (DFT). The EAM potential has been previously used successfully for bulk Fe–C systems. Our study indicates that preference for C adsorption site, the surface to subsurface diffusion of C atoms and their migration paths over the 110 surface are in good agreement with DFT. The ReaxFF potential is more suited for simulating the hydrocarbon reaction at the surface while the subsequent diffusion to subsurface and bulk is better captured with the EAM potential. This result opens the door to a new approach for using empirical potentials in the study of complex material set-ups.

Diffusion and relaxation of defects in bulk systems is a complex process that can only be accessed directly through simulations. We characterize the mechanisms of low-temperature aging in self-implanted crystalline silicon, a model system used extensively to characterize both amorphization and return to equilibrium processes, over 11 orders of magnitudes in time, from 10 ps to 1 s, using a combination of molecular dynamics and kinetic activation-relaxation technique simulations. These simulations allow us to reassess the atomistic mechanisms responsible for structural relaxations and for the overall logarithmic relaxation, a process observed in a large number of disordered systems and observed here over the whole simulation range. This allows us to identify three microscopic regimes, annihilation, aggregation, and reconstruction, in the evolution of defects and to propose atomistic justification for an analytical model of logarithmic relaxation. Furthermore, we show that growing activation barriers and configurational space exploration are kinetically limiting the system to a logarithmic relaxation. Overall, our long-time simulations do not support the amorphous cluster model but point rather to a relaxation driven by elastic interactions between defect complexes of all sizes.

Department of Physics and Astronomy, Condensed Matter and Surface Science Program, Ohio University, Athens, Ohio 45701-2979~Received 7 June 2000!We report on ab initio calculations of electronic states of two large and realistic models of amorphous silicongenerated using a modified version of the Wooten-Winer-Weaire algorithm and relaxed, in both cases, with aKeating and a modified Stillinger-Weber potentials. The models have no coordination defects and a verynarrow bond-angle distribution. We compute the electronic density-of-states and pay particular attention to thenature of the band-tail states around the electronic gap. All models show a large and perfectly clean optical gapand realistic Urbach tails. Based on these results and the extended quasi-one-dimensional stringlike structuresobserved for certain eigenvalues in the band tails, we postulate that the generation of model a-Si withoutlocalized states might be achievable under certain circumstances.I. INTRODUCTION

Knowledge of the dynamics in amorphous silicon that occurs through a sequence of discrete activated events is essential to predict many of the associated physical and chemical properties. Using the recently introduced nudged elastic band method of J\'onsson, Mills, and Jacobsen and a modified empirical Stillinger-Weber potential, we investigate, in detail, 802 perfect events generated with the activation-relaxation technique. We find that a large number of the high-energy events contain, in fact, two or more ``subevents.'' With this result included, the average barrier height goes down to about 3.0 eV, in line with experimental values and we also find that the bond-exchange mechanism of Wooten, Winer, and Weaire is, by far, the most important one for nondefect based dynamics in a-Si.

Many properties of alloyed chalcogenide glasses can be closely correlated with the average coordination of these compounds. This is the case, for example, of the ultrasonic constants, dilatometric softening temperature and the vibrational densities of states. What is striking, however, is that these properties are nevertheless almost independent of the composition at given average coordination. Here, we report on some numerical verification of this experimental rule as applied to vibrational density of states., Comment: 7 pages, including 3 figures

A full understanding of glasses requires an accurate atomistic picture of the complex activated processes that constitute the low-temperature dynamics of these materials. To this end, we generate over five thousand activated events in silica glass, using the activation-relaxation technique; these atomistic mechanisms are analysed and classified according to their activation energies, their topological properties and their spatial extend. We find that these are collective processes, involving ten to hundreds of atoms with a continuous range of activation energies; that diffusion and relaxation occurs through the creation, annihilation and motion of single dangling bonds; and that silicon and oxygen have essentially the same diffusivity., Comment: 4 pages, 3 figures

The Raman spectra of nine 216-atom models of amorphous silicon (a-Si) are calculated using the bond polarizability approximation of Raman scattering. These a-Si models, generated by the activation relaxation technique, have different concentrations of coordination defects, ring statistics and local strain distributions, which cause changes in the vibrational density of states and the Raman scattering. Analysis of the vibrational modes indicates that an increase in the number of coordination defects leads to an increase in the high-frequency localization and to mixing of the TA modes with other high-frequency modes. Calculation of partial Raman spectra indicates that five-coordinated Si atoms enhance the high-frequency part of the LO Raman peak at about 400 cm-1 and lead to characteristic band at about 600 cm-1 on the high-frequency side of the TO Raman peak. For their part, the three-coordinated Si atoms contribute to the low-frequency part of the LO peak. A weak correlation between the number of four-membered rings and the intensity of the LO Raman peak is also established although there is no correlation between the number of three- and four-membered rings and the total strain energy.

Maps are not reserved for geography. Chemical reactions, atomic diffusion and protein folding all involve atomic displacements determined by the topography of a complex energy landscape. These landscapes are largely unexplored, and our first priority is to identify their key features: the energy minima and the connecting paths between them. Such a study represents a formidable task. The effort needed to map a space increases exponentially with its dimensionality and becomes rapidly out of reach for the high-dimensional problems of interest in physics, chemistry and biology. Therefore, we have to satisfy ourselves with only a very crude knowledge of these energy landscapes. Recently, many researchers have been developing algorithms for exploring and mapping the potential energy landscapes of systems as diverse as polypeptides, chemical reactions, Lennard-Jones clusters and silica glass. In this article, we address some of the general issues and present an algorithm, called the activation-relaxation technique (ART), which we developed for mapping high-dimensional landscapes.

The rate of diffusion of a Cu adatom on the Cu(100) surface is calculated using thermodynamic integration within the transition state theory. The results are found to be in excellent agreement with the essentially exact values from molecular-dynamics simulations. The activation energy and related entropy are shown to be effectively independent of temperature, thus establishing the validity of the Arrhenius law over a wide range of temperatures. Our study demonstrates the equivalence of diffusion rates calculated using thermodynamic integration within the transition state theory and direct molecular-dynamics simulations., 4 pages (revtex), two figures (postscript)

Tight-binding (TB) molecular dynamics (MD) has emerged as a powerful method for investigating the atomic-scale structure of materials – in particular the interplay between structural and electronic properties – bridging the gap between empirical methods which, while fast and efficient, lack transferability, and ab initio approaches which, because of excessive computational workload, suffer from limitations in size and run times. In this short review article, we examine several recent applications of TBMD in the area of defects in covalently bonded semiconductors and the amorphous phases of these materials.

The dynamics of amorphous silicon at low temperatures can be characterized by a sequence of discrete activated events, through which the topological network is locally reorganized. Using the activation-relaxation technique, we create more than 8000 events, providing an extensive database of relaxation and diffusion mechanisms. The generic properties of these events - size, number of atoms involved, activation energy, etc. - are discussed and found to be compatible with experimental data. We introduce a complete and unique classification of defects based on their topological properties and apply it to study of events involving only four-fold coordinated atoms. For these events, we identify and present in detail three dominant mechanisms., Comment: 4 pages, three figures, submitted to PRL

Frustration is introduced in randomly connected totalistic cellular automata via mixing rules leading to incompatible periods. As the respective concentration of rules is varied, these cellular automata go through eight phases, many of which with symmetries different from the two rules mixed in. The complex phase diagram so created is similar to those seen in frustrated systems in static equilibrium. It shows that a minimized free energy is not necessary for frustration to produce this rich behaviour.

The huntingtin protein is characterized by a segment of consecutive glutamines (Q(N)) that is responsible for its fibrillation. As with other amyloid proteins, misfolding of huntingtin is related to Huntington's disease through pathways that can involve interactions with phospholipid membranes. Experimental results suggest that the N-terminal 17-amino-acid sequence (htt(NT)) positioned just before the Q(N) region is important for the binding of huntingtin to membranes. Through all-atom explicit solvent molecular dynamics simulations, we unveil the structure and dynamics of the htt(NT)Q(N) fragment on a phospholipid membrane at the atomic level. We observe that the insertion dynamics of this peptide can be described by four main steps-approach, reorganization, anchoring, and insertion-that are very diverse at the atomic level. On the membrane, the htt(NT) peptide forms a stable α-helix essentially parallel to the membrane with its nonpolar side-chains-mainly Leu-4, Leu-7, Phe-11 and Leu-14-positioned in the hydrophobic core of the membrane. Salt-bridges involving Glu-5, Glu-12, Lys-6, and Lys-15, as well as hydrogen bonds involving Thr-3 and Ser-13 with the phospholipids also stabilize the structure and orientation of the htt(NT) peptide. These observations do not significantly change upon adding the Q(N) region whose role is rather to provide, through its hydrogen bonds with the phospholipids' head group, a stable scaffold facilitating the partitioning of the htt(NT) region in the membrane. Moreover, by staying accessible to the solvent, the amyloidogenic Q(N) region could also play a key role for the oligomerization of htt(NT)Q(N) on phospholipid membranes.

We study ion-damaged crystalline silicon by combining nanocalorimetric experiments with an off-lattice kinetic Monte Carlo simulation to identify the atomistic mechanisms responsible for the structural relaxation over long time scales. We relate the logarithmic relaxation, observed in a number of disordered systems, with heat-release measurements. The microscopic mechanism associated with this logarithmic relaxation can be described as a two-step replenish and relax process. As the system relaxes, it reaches deeper energy states with logarithmically growing barriers that need to be unlocked to replenish the heat-releasing events leading to lower-energy configurations.

The nature of structural relaxation in disordered systems such as amorphous silicon (a-Si) remains a fundamental issue in our attempts at understanding these materials. While a number of experiments suggest that mechanisms similar to those observed in crystals, such as vacancies, could dominate the relaxation, theoretical arguments point rather to the possibility of more diverse pathways. Using the kinetic activation-relaxation technique, an off-lattice kinetic Monte Carlo method with on-the-fly catalog construction, we resolve this question by following 1000 independent vacancies in a well-relaxed a-Si model at 300 K over a timescale of up to one second. Less than one percent of these survive over this period of time and none diffuse more than once, showing that relaxation and diffusion mechanisms in disordered systems are fundamentally different from those in the crystal.

Effects of quenched disorder on a coupled map model of earthquakes are studied. In its original version, this model is known to display a self-organized critical distribution of avalanches. However, when some finite amount of quenched disorder is introduced, the bulk sites synchronize fully and a single stable system-wide avalanche appears. This synchronization is found for a wide band of disorder and goes against some recent predictions about integrate-and-fire models. {copyright} {ital 1996 The American Physical Society.}

We introduce and study frustrated cellular automata (CA) obtained by quenching competing Chate - Manneville rules. A period-two (P2) rule and a quasi-periodic one with period close to three (QP3) are frozen at random on the lattice sites. We find that the periodic and quasi-periodic cycles are resilient to internal frustration as well as to external unbounded noise. A low concentration of impurities improves the (quasi-)periodicity of the CA, damping the chaotic background noise significantly. Starting from pure QP3 CA, a first phase transition happens at a concentration of rule P2, , leading to a macroscopic fixed point. A second phase transition, at , brings the P2 phase. Although macroscopically stable, the central phase displays a stretched exponential relaxation of the site - site autocorrelations, indicating the presence of a new type of glass with slow dynamics superimposed on the natural cyclic dynamics of the CA rules. These results appear to be quite general and are found for many pairs of rules.

We study the effect of removing detailed balance from the axial next-nearest-neighbour Ising (ANNNI) model on its phase diagram. Although the concepts of free energy or Gibbsian thermodynamical equilibrium no longer apply, we find numerically that the phase diagram is preserved even when the interactions are completely unidirectional. We also find that the value of the multiphase point varies with the degree of asymmetry in the rules.

We study the effects of size-mismatch disorder on the surface relaxation of semiconductor solid solutions. Assuming a Kirkwood-type potential, we obtain an analytic solution for the nearest-neighbor distances and their distributions as a function of the distance from the surface as well as the displacements at the (111) and (100) surfaces. This solution is also valid for bond-mismatch disorder and is checked against computer simulations for two-dimensional triangular networks along (10) and (11) surfaces. Predictions are made for the topography of the (111) surface of a SiGe alloy.

Adsorption and dissociation of hydrocarbons on metallic surfaces represent crucial steps to carburization of metal. Here, we use density functional theory total energy calculations with the climbing-image nudged elastic band method to estimate the adsorption energies and dissociation barriers for different CO coverages with surface supercells of different sizes. For the absorption of CO, the contribution from van der Waals interaction in the computation of adsorption parameters is found important in small systems with high CO-coverages. The dissociation process involves carbon insertion into the Fe surface causing a lattice deformation that requires a larger surface system for unrestricted relaxation. We show that, in larger surface systems associated with dilute CO-coverages, the dissociation barrier is significantly decreased. The elastic deformation of the surface is generic and can potentially applicable for all similar metal-hydrocarbon reactions and therefore a dilute coverage is necessary for the simulation of these reactions as isolated processes., 12 pages, 6 figures. Submitted to Journal of Applied Physics

Adsorption and dissociation of gaseous carbon monoxide (CO) on metal surfaces is one of the most frequently occurring processes of carburisation, known as primary initiator of metal dusting corrosion. Among the various factors that can significantly influence the carburisation process are the intrinsic surface defects such as single surface vacancies occurring at high concentrations due to their low formation energy. Intuitively, adsorption and dissociation barriers of CO are expected to be lowered in the vicinity of a surface vacancy, due to the strong attractive interaction between the vacancy and the C atom. Here the adsorption energies and dissociation pathways of CO on clean and defective Fe 110 surface are explored by means of density functional theory. Interestingly, we find that the O adatom, resulting from the CO dissociation, is unstable in the electron-deficit neighbourhood of the vacancy due to its large electron affinity, and raises the barrier of the carburisation pathway. Still, a full comparative study between the clean surface and the vacancy-defected surface reveals that the complete process of carburisation, starting from adsorption to subsurface diffusion of C, is more favourable in the vicinity of a vacancy defect.

International audience; Using the ART NOUVEAU method, we study the initial stages of silicon oxide formation. After validating the method's parameters with the characterization of point defects diffusion mechanisms in pure Stillinger-Weber silicon, which allows us to recover some known results and to detail vacancy and self-interstitial diffusion paths, the method is applied onto a system composed of an oxygen layer deposited on a silicon substrate. We observe the oxygen atoms as they move rapidly into the substrate. From these ART NOUVEAU simulations, we extract the energy barriers of elementary mechanisms involving oxygen atoms and leading to the formation of an amorphouslike silicon oxide. We show that the kinetics of formation can be understood in terms of the energy barriers between various coordination environments.

The amyloid-β protein (Aβ) oligomers are believed to be the main culprits in the cytoxicity of Alzheimer’s disease (AD) and p3 peptides (Aβ17–42 fragments) are present in AD amyloid plaques. Many small-molecule or peptide-based inhibitors are known to slow down Aβ aggregation and reduce the toxicity in vitro, but their exact modes of action remain to be determined since there has been no atomic level of Aβ(p3)–drug oligomers. In this study, we have determined the structure of Aβ17–42 trimers both in aqueous solution and in the presence of five small-molecule inhibitors using a multiscale computational study. These inhibitors include 2002-H20, curcumin, EGCG, Nqtrp, and resveratrol. First, we used replica exchange molecular dynamics simulations coupled to the coarse-grained (CG) OPEP force field. These CG simulations reveal that the conformational ensemble of Aβ17–42 trimer can be described by 14 clusters with each peptide essentially adopting turn/random coil configurations, although the most populated cluster is characterized by one peptide with a β-hairpin at Phe19–Leu31. Second, these 14 dominant clusters and the less-frequent fibril-like state with parallel register of the peptides were subjected to atomistic Autodock simulations. Our analysis reveals that the drugs have multiple binding modes with different binding affinities for trimeric Aβ17–42 although they interact preferentially with the CHC region (residues 17–21). The compounds 2002-H20 and Nqtrp are found to be the worst and best binders, respectively, suggesting that the drugs may interfere at different stages of Aβ oligomerization. Finally, explicit solvent molecular dynamics of two predicted Nqtrp–Aβ17–42 conformations describe at atomic level some possible modes of action for Nqtrp.

A Comment on the Letter by Yue Fan et al., Phys. Rev. Lett. 106, 125501 (2011). The authors of the Letter offer a reply.

We present an adaptation of the ART-nouveau energy surface sampling method to the problem of loop structure prediction. This method, previously used to study protein folding pathways and peptide aggregation, is well suited to the problem of sampling the conformation space of large loops by targeting probable folding pathways instead of sampling exhaustively that space. The number of sampled conformations needed by ART nouveau to find the global energy minimum for a loop was found to scale linearly with the sequence length of the loop for loops between 8 and about 20 amino acids. Considering the linear scaling dependence of the computation cost on the loop sequence length for sampling new conformations, we estimate the total computational cost of sampling larger loops to scale quadratically compared to the exponential scaling of exhaustive search methods.

The small amyloid-forming GNNQQNY fragment of the prion sequence has been the subject of extensive experimental and numerical studies over the last few years. Using unbiased molecular dynamics with the OPEP coarse-grained potential, we focus here on the onset of aggregation in a 20-mer system. With a total of 16.9 of simulations at 280 K and 300 K, we show that the GNNQQNY aggregation follows the classical nucleation theory (CNT) in that the number of monomers in the aggregate is a very reliable descriptor of aggregation. We find that the critical nucleus size in this finite-size system is between 4 and 5 monomers at 280 K and 5 and 6 at 300 K, in overall agreement with experiment. The kinetics of growth cannot be fully accounted for by the CNT, however. For example, we observe considerable rearrangements after the nucleus is formed, as the system attempts to optimize its organization. We also clearly identify two large families of structures that are selected at the onset of aggregation demonstrating the presence of well-defined polymorphism, a signature of amyloid growth, already in the 20-mer aggregate., Author Summary Protein aggregation plays an important pathological role in numerous neurodegenerative diseases such as Alzheimer's, Parkinson's, Creutzfeldt-Jakob, the Prion disease and diabetes mellitus. In most cases, misfolded proteins are involved and aggregate irreversibly to form highly ordered insoluble macrostructures, called amyloid fibrils, which deposit in the brain. Studies have revealed that all proteins are capable of forming amyloid fibrils that all share common structural features and therefore aggregation mechanisms. The toxicity of amyloid aggregates is however not attributed to the fibrils themselves but rather to smaller more disordered aggregates, oligomers, forming parallel to or prior to fibrils. Understanding the assembly process of these amyloid oligomers is key to understanding their toxicity mechanism in order to devise a possible treatment strategy targeting these toxic aggregates. Our approach here is to computationally study the aggregation dynamics of a 20-mer of an amyloid peptide GNNQQNY from a prion protein. Our findings suggest that the assembly is a spontaneous process that can be described as a complex nucleation and growth mechanism and which can lead to two classes of morphologies for the aggregates, one of which resembles a protofibril-like structure. Such numerical studies are crucial to understanding the details of fast biological processes and complement well experimental studies.

The evolution of many systems is dominated by rare activated events that occur on timescale ranging from nanoseconds to the hour or more. For such systems, simulations must leave aside the full thermal description to focus specifically on mechanisms that generate a configurational change. We present here the activation relaxation technique (ART), an open-ended saddle point search algorithm, and a series of recent improvements to ART nouveau and kinetic ART, an ART-based on-the-fly off-lattice self-learning kinetic Monte Carlo method.

We present a detailed description of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice, self-learning kinetic Monte Carlo algorithm with on-the-fly event search. Combining a topological classification for local environments and event generation with ART nouveau, an efficient unbiased sampling method for finding transition states, k-ART can be applied to complex materials with atoms in off-lattice positions or with elastic deformations that cannot be handled with standard KMC approaches. In addition to presenting the various elements of the algorithm, we demonstrate the general character of k-ART by applying the algorithm to three challenging systems: self-defect annihilation in c-Si (crystalline silicon), self-interstitial diffusion in Fe and structural relaxation in a-Si (amorphous silicon)., 13 pages, 11 figures. Final version as published, Figs. 6 and 7 exchanged, minor typographical and stylistic corrections

The activation-relaxation technique $\mathrm{nouveau}$ (ART$n$), a method for the systematic search of the minima and saddle-point configurations, is applied to the study of interstitial-cluster defects in iron. Some simple modifications to improve the efficiency of the ART$n$ method for these types of applications are proposed. The energy landscapes at 0 K of defect clusters with up to four self-interstitial atoms obtained using the Ackland-Mendelev potential for iron are presented. The efficiency of the method is demonstrated in the case of monointerstitials. The number of different bound configurations increases very rapidly with cluster size from di- to quadri-interstitials. All these clusters can be analyzed as assemblies of dumbbells mostly with $\ensuremath{\langle}$110$\ensuremath{\rangle}$ orientation. The lowest-energy configurations found with the present method and potential are made of parallel dumbbells. The mechanisms associated with the lowest saddle-point energies are analyzed. They include local rearrangements that do not contribute to long-range diffusion. The translation-rotation mechanism is confirmed for the migration of mono- and di-interstitials. For the tri-interstitial the migration is dominated by three mechanisms that do not involve the lowest-energy configuration. The migration of quadri-interstitials occurs by an on-site reorientation of the dumbbells in the $\ensuremath{\langle}$111$\ensuremath{\rangle}$ direction, followed by the conventional easy glide. Finally, the minimum energy paths are investigated for the transformation toward the lowest-energy configuration of two specific clusters, including a quadri-interstitial cluster with a ring configuration, which was shown to exhibit an unexpected low mobility in previous molecular-dynamics simulations.

The loss of the insulin-producing β-cells in the pancreatic islets of Langerhans, responsible for type-II diabetes, is associated with islet amyloid deposits. The main component of these deposits is the amyloid fibrils formed by the 37-residue human islet amyloid polypeptide (hIAPP also known as amylin). Although the fibrils are well characterized by cross β structure, the structure of the transient oligomers formed in the early stage of aggregation remains elusive. In this study, we apply the Hamiltonian-temperature replica exchange molecular dynamics to characterize the structure and thermodynamics of a full-length hIAPP dimer in both the presence and the absence of the Cys2-Cys7 disulfide bond. We compare these results with those obtained on the monomeric and dimeric forms of rat IAPP (rIAPP) with a disulfide bridge which differ from the hIAPP by 6 amino acids in the C-terminal region, but it is unable to form fibrils. Using a coarse-grained protein force field (OPEP-the Optimized Potential for Efficient peptide structure Prediction) running for a total of 10-28 μs per system studied, we show that sequences sample α-helical structure in the N-terminal region but that the length of this secondary element is shorter and less stable for the chains without the disulfide bridge (residues 5-16 for hIAPP with the bridge vs 10-16 for hIAPP without the bridge). This α-helix is known to be an important transient stage in the formation of oligomers. In the C-terminal, the amyloidogenic region of hIAPP, β-strands are seen for residues 17-26 and 30-35. On the contrary, no significant β-sheet content in the C-terminal is observed for either the monomeric or the dimeric rIAPP. These numerical results are fully consistent with recent experimental findings that the N-terminal residues are not part of the fibril by forming α-helical structure but rather play a significant role in stabilizing the amyloidogenic region available for the fibrillation.

The formation of amyloid fibrils is associated with numerous neurodegenerative diseases such as Alzheimer's, Parkinson's, the Prion disease but also with diseases such as diabetes mellitus. Little is known about the aggregation dynamics of amyloid proteins and a detailed atomic characterization of this process is necessary to better understand their toxicity mechanism. More than 20 short amyloid peptides fragments have been identified to have the ability to drive an entire protein into an amyloid fibrillar state. In particular, the amyloid peptide GNNQQNY from the budding yeast's Prion protein Sup35 has been observed to form fibrils by X-ray crystallography. The main structural element of those GNNQQNY fibrils is a cross-β structure consisting of two parallel β-sheet stacked in-register, with side-chains interdigitating between the sheets to provide stability to the structure. We have conducted a computational study of the GNNQQNY peptide aggregation mechanism by replica-exchange molecular dynamics, using first a coarse-grained potential (OPEP) followed by an all-atom refinement of the side-chains using GROMACS. This combination of numerical methods allows us to accelerate the sampling and thus study bigger systems over longer time scales compared to the other numerical methods generally used. Here, we have investigated the aggregation process of the trimer, dodecamer and 20-mer GNNQQNY, starting from random conformations, and our simulations show a rich diversity of structural arrangements for aggregates of all sizes. For the 20-mer, we observe the formation of 3 to 4-stranded building blocks that assemble in various orientations to form transiently fibril-like structures or more disordered globular oligomers, showing a rich polymorphism.

The self-organization of peptides into amyloidogenic oligomers is one of the key events for a wide range of molecular and degenerative diseases. Atomic-resolution characterization of the mechanisms responsible for the aggregation process and the resulting structures is thus a necessary step to improve our understanding of the determinants of these pathologies. To address this issue, we combine the accelerated sampling properties of replica exchange molecular dynamics simulations based on the OPEP coarse-grained potential with the atomic resolution description of interactions provided by all-atom MD simulations, and investigate the oligomerization process of the GNNQQNY for three system sizes: 3-mers, 12-mers and 20-mers. Results for our integrated simulations show a rich variety of structural arrangements for aggregates of all sizes. Elongated fibril-like structures can form transiently in the 20-mer case, but they are not stable and easily interconvert in more globular and disordered forms. Our extensive characterization of the intermediate structures and their physico-chemical determinants points to a high degree of polymorphism for the GNNQQNY sequence that can be reflected at the macroscopic scale. Detailed mechanisms and structures that underlie amyloid aggregation are also provided., Author Summary The formation of amyloid fibrils is associated with many neurodegenerative diseases such as Alzheimer's, Creutzfeld-Jakob, Parkinson's, the Prion disease and diabetes mellitus. In all cases, proteins misfold to form highly ordered insoluble aggregates called amyloid fibrils that deposit intra- and extracellularly and are resistant to proteases. All proteins are believed to have the instrinsic capability of forming amyloid fibrils that share common specific structural properties that have been observed by X-ray crystallography and by NMR. However, little is known about the aggregation dynamics of amyloid assemblies, and their toxicity mechanism is therefore poorly understood. It is believed that small amyloid oligomers, formed on the aggregation pathway of full amyloid fibrils, are the toxic species. A detailed atomic characterization of the oligomerization process is thus necessary to further our understanding of the amyloid oligomer's toxicity. Our approach here is to study the aggregation dynamics of a 7-residue amyloid peptide GNNQQNY through a combination of numerical techniques. Our results suggest that this amyloid sequence can form fibril-like structures and is polymorphic, which agrees with recent experimental observations. The ability to fully characterize and describe the aggregation pathway of amyloid sequences numerically is key to the development of future drugs to target amyloid oligomers.

We have investigated the response of amorphous silicon (a-Si), in particular crystallization, to external mechanical shear deformations using classical molecular dynamics (MD) simulations and the empirical Environment Dependent Inter-atomic Potential (EDIP) [Phys. Rev. B 56, 8542 (1997)]. In agreement with previous results we find that, at low shear velocity and low temperature, shear deformations increase disorder and defect density. At high temperatures, however, the deformations are found to induce crystallization, demonstrating a dynamical transition associated with both shear rate and temperature. The properties of a-Si under shear deformations and the extent at which the system crystallizes are analyzed in terms of the potential energy difference (PED) between the sheared and non-sheared material, as well as the fraction of defects and the number of particles that possess a crystalline environment., Comment: 8 pages, 12 figures

There are serious contradictions between extended x-ray-absorption fine structure (EXAFS) measurements of the Si-Ge and Ge-Ge bond lengths in both crystalline and amorphous silicon-germanium alloys, and in theoretical and simulation predictions. In particular, results from EXAFS experiments show that the Si-Ge and Ge-Ge bond lengths are independent of the alloy composition, indicating that there is no topological rigidity in the lattice. These EXAFS results on Si-Ge alloys are in sharp disagreement with all previous EXAFS results on III-V and II-VI semiconductor alloys. We discuss the implications of the EXAFS results regarding the local and global structure of the alloys. We also propose a structural model to serve as a focus for further experiments. In order to satisfy the overall floppiness of the network, we suggest that the Si-Ge samples may contain a large density of planar cracks, lined with hydrogen, and separated by \ensuremath{\sim}10 \AA{}. Some measurements that could confirm (or discredit) this model are suggested.

The link between the energy surface of bulk systems and their dynamical properties is generally difficult to establish. Using the activation-relaxation technique (ART nouveau), we follow the change in the barrier distribution of a model of amorphous silicon as a function of the degree of relaxation. We find that while the barrier-height distribution, calculated from the initial minimum, is a unique function that depends only on the level of distribution, the reverse-barrier height distribution, calculated from the final state, is independent of the relaxation, following a different function. Moreover, the resulting gained or released energy distribution is a simple convolution of these two distributions indicating that the activation and relaxation parts of a the elementary relaxation mechanism are completely independent. This characterized energy landscape can be used to explain nano-calorimetry measurements., Comment: 5 pages, 4 figures

Expansion of polyglutamine (polyQ) beyond the pathogenic threshold (35-40 Gln) is associated with several neurodegenerative diseases including Huntington's disease, several forms of spinocerebellar ataxias and spinobulbar muscular atrophy. To determine the structure of polyglutamine aggregates we perform replica-exchange molecular dynamics simulations coupled with the optimized potential for effective peptide forcefield. Using a range of temperatures from 250 to 700 K, we study the aggregation kinetics of the polyglutamine monomer and dimer with chain lengths from 30 to 50 residues. All monomers show a similar structural change at the same temperature from alpha-helical structure to random coil, without indication of any significant beta-strand. For dimers, by contrast, starting from random structures, we observe spontaneous formation of antiparallel beta-sheets and triangular and circular beta-helical structures for polyglutamine with 40 residues in a 400 ns 50 temperature replica-exchange molecular dynamics simulation (total integrated time 20 micros). This approximately 32 A diameter structure reorganizes further into a tight antiparallel double-stranded approximately 22 A nanotube with 22 residues per turn close to Perutz' model for amyloid fibers as water-filled nanotubes. This diversity of structures suggests the existence of polymorphism for polyglutamine with possibly different pathways leading to the formation of toxic oligomers and to fibrils.

Mechanical shear deformations lead, in some cases, to effects similar to those resulting from ion irradiation. Here we characterize the effects of shear velocity and temperature on amorphous silicon (\aSi) modelled using classical molecular dynamics simulations based on the empirical Environment Dependent Inter-atomic Potential (EDIP). With increasing shear velocity at low temperature, we find a systematic increase in the internal strain leading to the rapid appearance of structural defects (5-fold coordinated atoms). The impacts of externally applied strain can be almost fully compensated by increasing the temperature, allowing the system to respond more rapidly to the deformation. In particular, we find opposite power-law relations between the temperature and the shear velocity and the deformation energy. The spatial distribution of defects is also found to strongly depend on temperature and strain velocity. For low temperature or high shear velocity, defects are concentrated in a few atomic layers near the center of the cell while, with increasing temperature or decreasing shear velocity, they spread slowly throughout the full simulation cell. This complex behavior can be related to the structure of the energy landscape and the existence of a continuous energy-barrier distribution., Comment: 10 pages, 17 figures