Many simple diatomic and triatomic molecules such as N2 and CO2 have the potential to form extended “polymeric” solids under extreme conditions, which can store a large sum of chemical energy in its three-dimensional network structures made of strong covalent bonds. Diatomic nitrogen is particularly of interest because of the uniquely large energy difference between that of the single bond (160 kJ/mol) and that of the triple bond (954 kJ/mol). As such, the transformation of a singly bonded polymeric nitrogen back to triply-bonded diatomic nitrogen molecules can release nearly 5 times the energy of TNT without any negative environmental impact. In this paper, we will describe our recent research efforts to synthesize novel extended phases of isoelectronic systems of N2 and CO, as well as those of N2+CO mixtures to lower the transition pressures and enhance the stability of recovered products at ambient condition.

New emergent materials of novel electromagnetic properties are discussed, based primarily on our recent works. The use of pressure effects in terms of self oxidization, inner compression and pure doping in discovering new emergent materials is highlighted. Materials addressed include (I) new correlated oxides such as high-T c cuprate superconductors; (II) new intermetallic materials such as diluted magnetic semiconductors with independent spin & charge doping; the “111” type iron based superconducting systems; (III) compounds with strong spin orbit coupling, such as itinerant ferromagnetic ruthenates etc.

Molecular dynamics simulations of the melting process of bulk copper were performed using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) with the interatomic potentials being described by the embedded atom method. The aim of the study was to understand the effects of high pressures and defects on the melting temperature. The simulations were visualised using Visual Molecular Dynamics (VMD). The melting temperature of a perfect copper crystal, was found to be slightly higher than the experimentally observed value. The melting temperature as a function of pressure was determined and compared with experiment. Point and line defects, in the form of dislocations, were then introduced into crystal and the new melting temperature of the crystal determined. We find that the melting temperature decreases as the defect density is increased. Additionally, the slope of the melting temperature curve was found to decrease as the pressure was increased while the vacancy formation energy increases with pressure.

In coarse grained molecular dynamics (CGMD) simulations, small groups of atoms are treated as single particles (beads) and the forces between these particles are derived from the interatomic forces. The effect of this is to severely reduce the number of particles in a simulation, thereby allowing for the consideration of a larger number of atoms. It has also proven to be a valuable tool in probing time and length scales of systems beyond that used in all-atom molecular dynamics (AAMD) simulations. The down side of this is that the inter-particle interactions are less accurate. However, if these coarse grained particles are chosen carefully, such simulations can provide much useful information. There are different levels of how the coarse grains are constructed. For example, CG systems have been developed using tens or hundreds of atoms per CG bead in some studies of amino acids in biological science. By contrast, for other systems, a single CG bead is used to replace just two or three atoms.

In this paper, the interaction of a carbon nanotube (CNT) with a lipid bilayer membrane is studied using both coarse grained and atomistic MD in an effort to understand the usefulness of the CGMD method for such simulations. Our preliminary studies of the interaction of a CNT with a lipid bilayer points indicates that such nano-tubes inserted into a membrane could be stable. This means that it could be used as an agent in the delivery of drugs. It would be good if these simulations could be repeated using AAMD simulations to confirm the validity of these results.

Failure of metallic materials due to plastic and/or creep deformation occur by the emergence of necking, microvoids, and cracks at heterogeneities in the material microstructure. While many traditional deformation modeling approaches have difficulty capturing these emergent phenomena, the discrete element method (DEM) has proven effective for the simulation of materials whose properties and response vary over multiple spatial scales, e.g., bulk granular materials. The DEM framework inherently provides a mesoscale simulation approach that can be used to model macroscopic response of a microscopically diverse system. DEM naturally captures the heterogeneity and geometric frustration inherent to deformation processes. While DEM has recently been adapted successfully for modeling the fracture of brittle solids, to date it has not been used for simulating metal deformation. In this paper, we present our progress in reformulating DEM to model the key elastic and plastic deformation characteristics of FCC polycrystals to create an entirely new crystal plasticity modeling methodology well-suited for the incorporation of heterogeneities and simulation of emergent phenomena.

This paper presents a parametric study to investigate the effect of relevant design variables on mechanochemical reaction and mechanical properties of a mechanophore-embedded thermoset polymer matrix. Mechanophores emit fluorescence when a specific covalent bond breaks due to external stress, and thus have attracted immense research interest as a damage sensor. Recently, a mechanophore named dimeric 9-anthracene carboxylic acid (Di-AC) was synthesized successfully and incorporated into epoxy-based thermoset polymer matrix to detect damage precursor. However, there is significant potential in modeling the complex mechanochemistry associated with the Di-AC to obtain a better understanding of this mechanophore and its interaction with the host thermoset material. In this study, a hybrid MD simulation methodology is employed to explore this complex mechanochemistry along with the investigation of the effect of design parameters on the mechanophore performance. The hybrid MD simulation method enables the simulation of Di-AC synthesis, epoxy curing, and mechanical loading test; therefore, the experimental process performed can be emulated accurately. Previously, the hybrid MD method showed the capability of capturing experimentally observed phenomena such as early signal detection and yield strength variation between neat epoxy system and epoxy with 5 wt% Di-AC thermoset polymer. In this paper, the effect of curing temperature on mechanophore activation and mechanical properties is investigated. A series of temperatures are used in the curing simulation, which are experimentally achievable. Results show that curing temperature below glass transition temperature maintains early signal detection and yield strength decreases when the curing temperature increases above the glass transition temperature. Good correlation is observed with experimental results.

Carbon nanotube (CNT) sock formation is required for the continuous synthesis of CNT thread or sheet using the gas phase pyrolysis method. Nanometer diameter CNTs form and are carried along the reactor tube by gas flow. During the flow, the CNT stick to each other and form bundles of about 10-100 nm diameter. Coupling of the CNT bundles in the flow leads to the formation of a centimeter diameter CNT sock with a wall that is hundreds of nanometers thick. Understanding the multiscale phenomena of sock formation is vital for optimizing the CNT synthesis and manufacturing process. In this work, we present a multiscale model for the CNT bundle agglomeration inside a horizontal gas phase pyrolysis reactor. The interaction between CNT bundles was analyzed by representing the attraction forces between CNTs using a discrete phase modeling method. Flow in the synthesis reactor was studied using a computational fluid dynamics (CFD) technique with multiphase flow analysis. A model was proposed to represent the coupling between CNT bundles and the gas flow. The effect of different CNT bundles on the agglomeration phenomenon was analyzed. The modeling results were also compared with experimental observations.

We examine how stress has the potential to shape the character of the electron transport that occurs within ZnO. In order to narrow the scope of this analysis, we focus on a determination of the velocity-field characteristics associated with bulk wurtzite ZnO. Monte Carlo simulations of the electron transport are pursued for the purposes of this analysis. Rather than focusing on the impact of stress in of itself, instead we focus on the changes that occur to the energy gap through the application of stress, i.e., energy gap variations provide a proxy for the amount of stress. Our results demonstrate that stress plays a significant role in shaping the form of the velocity-field characteristics associated with ZnO. This dependence could potentially be exploited for device application purposes.

In this note we discuss two aspects of screw dislocations dynamics: their behavior near the boundary and a way to confine them inside the material. In the former case, we obtain analytical results on the estimates of collision times (one dislocation with the boundary and two dislocations with opposite Burgers vectors with each other); numerical evidence is also provided. In the latter, we obtain analytical results stating that, under imposing a certain type of boundary conditions, it is energetically favorable for dislocations to remain confined inside the domain.

With the advent of amorphous oxide semiconductors (AOS) like amorphous indium gallium zinc oxide (a-IGZO), the analysis and prediction of amorphous structures has regained importance, more so, since first principles based studies are being increasingly employed to explain device behavior. Negative bias illumination stress in a-IGZO thin film transistors is one such example. However, the amorphous atomic structure is complex and defect or dopant studies require each site to be modeled independently and this leads to significant computational costs. Therefore, a simplification in the representation of the amorphous oxide network is effected so that it may lead to identifying similar atomic sites. The amorphous network is visualized as a network of polyhedra. The polyhedra has at its center a cation with the bonded oxygen atoms at the vertices and it comprises the short range interactions characterized by bond lengths and bond angles. Based on a first principles study of 10 a-IGZO models containing 36 cations each, it was found that the 360 polyhedra of the a-IGZO models can actually be described with only ten polyhedral motifs. These polyhedra are then connected to each other via a shared vertex or an edge; face-sharing was not observed in these models. Graph theory is used to map this network using either a graph of cationic polyhedra as the nodes or a bipartite graph (composed of cations and anions as individual nodes), each of which is described using the respective adjacency matrix. The second nearest interactions are characterized by the degree of each vertex and each atomic site is now characterized by a polyhedron and network metrics; and hence, can be compared with same-element sites. The changes in network itself, are quantified as the composition changes, when varying the ratio of In:Ga:Zn in a-IGZO. For example, the average vertex connectivity of a pair of indium sites reflects on the continuity of overlap between the In-5s orbitals which compose the conduction band minimum in a-IGZO, which, in turn, affects the transport properties of the semiconductor. Thus, the long range interactions of the physical amorphous network are described by the graph metrics. Moreover, evolutionary algorithm in conjunction with this graph theoretic representation can be used to generate new amorphous models. Two parent graph are chosen and then spliced and then bred. The new graph is then reverse-engineered to form an amorphous model which then undergoes ionic and volume relaxation in the framework of density functional theory. The resulting graph is the child and the new amorphous model, with the energy as the fitness criteria.