A self-learning algorithm for biased molecular dynamics

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences.

A Molecular Dynamics Study of the Early Stages of Calcium Carbonate Growth

The precipitation of calcium carbonate in water has been examined using a combination of molecular dynamics and umbrella sampling. During 20 ns molecular dynamics trajectories at elevated calcium carbonate concentrations, amorphous particles are observed to form and appear to be composed of misaligned domains of vaterite and aragonite. The addition of further calcium ions to these clusters is found to be energetically favorable and virtually barrierless. By contrast, there is a large barrier to the addition of calcium to small calcite crystals. Thus, even though calcite nanocrystals are stable in solution, at high supersaturations, particles of amorphous material form because this material grows much faster than ordered calcite nanocrystals.

A Neutron Diffraction and Molecular Dynamics Investigation of Acetate-based Ionic Liquids as Solvents for Glucose

The liquid state structure of the ionic liquid, 1-ethyl-3-methylimidazolium acetate, and the solute/solvent structure of glucose dissolved in the ionic liquid at a 1: 6 molar ratio have been investigated at 323 K by molecular dynamics simulations and neutron diffraction experiments using H/D isotopically substituted materials. Interactions between hydrogen-bond donating cation sites and polar, directional hydrogen-bond accepting acetate anions are examined. Ion-ion radial distribution functions for the neat ionic liquid, calculated from both MD and derived from the empirical potential structure refinement model to the experimental data, show the alternating shell-structure of anions around the cation, as anticipated. Spatial probability distributions reveal the main anion-to-cation features as in-plane interactions of anions with imidazolium ring hydrogens and cation-cation planar stacking. Interestingly, the presence of the polarised hydrogen-bond acceptor anion leads to increased anion-anion tail-tail structuring within each anion shell, indicating the onset of hydrophobic regions within the anion regions of the liquid.

Molecular dynamics simulation model for the quantitative assessment of tool wear during single point diamond turning of cubic silicon carbide

Silicon carbide (SiC) is a material of great technological interest for engineering applications concerning hostile environments where silicon-based components cannot work (beyond 623 K). Single point diamond turning (SPDT) has remained a superior and viable method to harness process efficiency and freeform shapes on this harder material. However, it is extremely difficult to machine this ceramic consistently in the ductile regime due to sudden and rapid tool wear. It thus becomes non trivial to develop an accurate understanding of tool wear mechanism during SPDT of SiC in order to identify measures to suppress wear to minimize operational cost.

In this paper, molecular dynamics (MD) simulation has been deployed with a realistic analytical bond order potential (ABOP) formalism based potential energy function to understand tool wear mechanism during single point diamond turning of SiC. The most significant result was obtained using the radial distribution function which suggests graphitization of diamond tool during the machining process. This phenomenon occurs due to the abrasive processes between these two ultra hard materials. The abrasive action results in locally high temperature which compounds with the massive cutting forces leading to sp3–sp2 order–disorder transition of diamond tool. This represents the root cause of tool wear during SPDT operation of cubic SiC. Further testing led to the development of a novel method for quantitative assessment of the progression of diamond tool wear from MD simulations.

Simulations of Biased Agonists in the β2 Adrenergic Receptor with Accelerated Molecular Dynamics

The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signalling pathway a GPCR promotes intracellular signals though ß-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that a GPCR forms a distinct ensemble of conformations signalling through the G protein and ß-arrestin. Here we report on the dynamics of the ß2 adrenergic receptor bound to the ß-arrestin and G protein biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring the transition within the nanosecond timescale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the ß-arrestin biased agonist, N-cyclopentylbutanepherine we observe a different pattern of motions in helix 7 when compared to simulations with the G protein biased agonist, Salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs. © 2013 American Chemical Society

Molecular dynamics simulation of nanoindentation of Fe3C and tetrahedral Fe4C

Study of nanomechanical response of iron carbides is important because presence of iron carbides greatly influences the performance and longevity of steel components. This work contributes to the literature by exploring nanoindentation of nanocrystalline Fe3C and tetrahedral-Fe4C using molecular dynamics simulation. The chemical interactions of iron and carbon were described through an analytical bond order inter-atomic potential (ABOP) energy function. The indentations were performed at an indentation speed of 50 m/sec and a repeat trial was performed at 5 m/sec. Load-displacement (P-h) curve for both these carbides showed residual indentation depth and maximum indentation depth (hf/hmax) ratio to be higher than 0.7 i.e. a circumstance where Oliver and Pharr method was not appropriate to be applied to evaluate the material properties. Alternate evaluation revealed Fe3C to be much harder than Fe4C. Gibbs free energy of formation and radial distribution function, coupled with state of the average local temperature and von Mises stresses indicate the formation of a new phase of iron-carbide. Formation of this newer phase was found to be due to deviatoric strain rather than the high temperature induced in the substrate during nanoindentation

Nanoindentation of polysilicon and single crystal silicon: Molecular dynamics simulation and experimental validation

This paper presents novel advances on the deformation behaviour of polycrystalline and single crystal silicon using molecular dynamics (MD) simulation and validation of the same via nanoindentation experiments. In order to unravel the mechanism of deformation, four simulations were performed: Indentation of polycrystalline silicon substrate with a (i) Berkovich pyramidal and a (ii) spherical (arc) indenter, and indentation of a single crystal silicon substrate with these two indenters. The simulation results reveal that high pressure phase transformation (HPPT) in silicon (Si-I to Si-II phase transformation) occurred in all cases, however, its extent and the manner in which it occurred differed significantly between polycrystalline silicon and single crystal silicon, and was the main driver of differences in nanoindentation deformation behaviour between the two types of silicon. An interesting observation was that in polycrystalline silicon, the HPPT was observed to occur preferentially along the grain boundaries than across the grain boundaries. An automated dislocation extraction algorithm (DXA) revealed no dislocations in the deformation zone, suggesting HPPT to be the primary mechanism in inducing plasticity in silicon.

Diamond machining of silicon: A review of advances in molecular dynamics simulation

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

Generalized Langevin equation: An efficient approach to nonequilibrium molecular dynamics of open systems

The generalized Langevin equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general nonequilibrium processes. In this approach, a part of the whole system (an open system), which interacts and exchanges energy with its dissipative environment, is studied. Because the GLE is derived by projecting out exactly the harmonic environment, the coupling to it is realistic, while the equations of motion are non-Markovian. Although the GLE formalism has already found promising applications, e. g., in nanotribology and as a powerful thermostat for equilibration in classical molecular dynamics simulations, efficient algorithms to solve the GLE for realistic memory kernels are highly nontrivial, especially if the memory kernels decay nonexponentially. This is due to the fact that one has to generate a colored noise and take account of the memory effects in a consistent manner. In this paper, we present a simple, yet efficient, algorithm for solving the GLE for practical memory kernels and we demonstrate its capability for the exactly solvable case of a harmonic oscillator coupled to a Debye bath.

Robust nonadiabatic molecular dynamics for metals and insulators

We present a new formulation of the correlated electron-ion dynamics (CEID) scheme, which systematically improves Ehrenfest dynamics by including quantum fluctuations around the mean-field atomic trajectories. We show that the method can simulate models of nonadiabatic electronic transitions and test it against exact integration of the time-dependent Schrodinger equation. Unlike previous formulations of CEID, the accuracy of this scheme depends on a single tunable parameter which sets the level of atomic fluctuations included. The convergence to the exact dynamics by increasing the tunable parameter is demonstrated for a model two level system. This algorithm provides a smooth description of the nonadiabatic electronic transitions which satisfies the kinematic constraints (energy and momentum conservation) and preserves quantum coherence. The applicability of this algorithm to more complex atomic systems is discussed.

Protection of DNA against low-energy electrons by amino acids: A first-principles molecular dynamics study

Using first-principles molecular dynamics simulations, we have investigated the notion that amino acids can play a protective role when DNA is exposed to excess electrons produced by ionizing radiation. In this study we focus on the interaction of glycine with the DNA nucleobase thymine. We studied thymine-glycine dimers and a condensed phase model consisting of one thymine molecule solvated in amorphous glycine. Our results show that the amino acid acts as a protective agent for the nucleobase in two ways. If the excess electron is initially captured by the thymine, then a proton is transferred in a barrier-less way from a neighboring hydrogen-bonded glycine. This stabilizes the excess electron by reducing the net partial charge on the thymine. In the second mechanism the excess electron is captured by a glycine, which acts as a electron scavenger that prevents electron localization in DNA. Both these mechanisms introduce obstacles to further reactions of the excess electron within a DNA strand, e.g. by raising the free energy barrier associated with strand breaks.

Influence of temperature on the anisotropic cutting behaviour of single crystal silicon: A molecular dynamics simulation investigation

Using molecular dynamics (MD) simulation, this paper investigates anisotropic cutting behaviour of single crystal silicon in vacuum under a wide range of substrate temperatures (300 K, 500 K, 750 K, 850 K, 1173 K and 1500 K). Specific cutting energy, force ratio, stress in the cutting zone and cutting temperature were the indicators used to quantify the differences in the cutting behaviour of silicon. A key observation was that the specific cutting energy required to cut the (111) surface of silicon and the von Mises stress to yield the silicon reduces by 25% and 32%, respectively, at 1173 K compared to what is required at 300 K. The room temperature cutting anisotropy in the von Mises stress and the room temperature cutting anisotropy in the specific cutting energy (work done by the tool in removing unit volume of material) were obtained as 12% and 16% respectively. It was observed that this changes to 20% and 40%, respectively, when cutting was performed at 1500 K, signifying a very strong correlation between the anisotropy observed during cutting and the machining temperature. Furthermore, using the atomic strain criterion, the width of primary shear zone was found to vary with the orientation of workpiece surface and temperature i.e. it remains narrower while cutting the (111) surface of silicon or at higher machining temperatures. A major anecdote of the study based on the potential function employed in the study is that, irrespective of the cutting plane or the cutting temperature, the state of the cutting edge of the diamond tool did not show direct diamond to graphitic phase transformation.

The diamond pyramid structure in electroless copper deposit, its atomic model and molecular dynamics simulation

In this seminar, I will talk about the discovery of the diamond pyramid structures in the electroless copper deposits on both epoxy and stainless steel substrates. The surface morphology of the structure was characterized with scanning electron microscopy (SEM). According to the morphological feature of the structure, an atom model was brought forward in order to describe the possible mechanism of forming such structure. Molecular dynamics simulations were then carried out to investigate the growing process of the diamond pyramid structure. The final structures of the simulation were compared with the SEM images and the atomic model. The radial distribution function of the final structures of the simulation was compared with that calculated from the X-ray diffraction pattern of the electroless copper deposit sample.

Molecular dynamics simulation (MDS) to study nanoscale machining processes

Molecular Dynamics Simulations (MDS) are constantly being used to make important contributions to our fundamental understanding of material behaviour, at the atomic scale, for a variety of thermodynamic processes. This chapter shows that molecular dynamics simulation is a robust numerical analysis tool in addressing a range of complex nanofinishing (machining) problems that are otherwise difficult or impossible to understand using other methods. For example the mechanism of nanometric cutting of silicon carbide is influenced by a number of variables such as machine tool performance, machining conditions, material properties, and cutting tool performance (material microstructure and physical geometry of the contact) and all these variables cannot be monitored online through experimental examination. However, these could suitably be studied using an advanced simulation based approach such as MDS. This chapter details how MD simulation can be used as a research and commercial tool to understand key issues of ultra precision manufacturing research problems and a specific case was addressed by studying diamond machining of silicon carbide. While this is appreciable, there are a lot of challenges and opportunities in this fertile area. For example, the world of MD simulations is dependent on present day computers and the accuracy and reliability of potential energy functions [109]. This presents a limitation: Real-world scale simulation models are yet to be developed. The simulated length and timescales are far shorter than the experimental ones which couples further with the fact that contact loading simulations are typically done in the speed range of a few hundreds of m/sec against the experimental speed of typically about 1 m/sec [17]. Consequently, MD simulations suffer from the spurious effects of high cutting speeds and the accuracy of the simulation results has yet to be fully explored. The development of user-friendly software could help facilitate molecular dynamics as an integral part of computer-aided design and manufacturing to tackle a range of machining problems from all perspectives, including materials science (phase of the material formed due to the sub-surface deformation layer), electronics and optics (properties of the finished machined surface due to the metallurgical transformation in comparison to the bulk material), and mechanical engineering (extent of residual stresses in the machined component) [110]. Overall, this chapter provided key information concerning diamond machining of SiC which is classed as hard, brittle material. From the analysis presented in the earlier sections, MD simulation has helped in understanding the effects of crystal anisotropy in nanometric cutting of 3C-SiC by revealing the atomic-level deformation mechanisms for different crystal orientations and cutting directions. In addition to this, the MD simulation revealed that the material removal mechanism on the (111) surface of 3C-SiC (akin to diamond) is dominated by cleavage. These understandings led to the development of a new approach named the “surface defect machining” method which has the potential to be more effective to implement than ductile mode micro laser assisted machining or conventional nanometric cutting.