MISPR: an open-source package for high-throughput multiscale molecular simulations.

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure-Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure-property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

Distributions of pore sizes and atomic densities in binary mixtures revealed by molecular dynamics simulations.

We report on the results of a molecular dynamics simulation study of porous glassy media, formed in the process of isochoric rapid quenching from a high-temperature liquid state. The transition to a porous solid occurs due to the concurrent processes of phase separation and material solidification. The study is focused on topographies of the model porous structures and their dependence on temperature and average density. To quantify the pore-size distributions, we put forth a scaling relation that provides a satisfactory data collapse in systems with high porosity. We also find that the local density of the solid domains in the porous structures is broadly distributed, and, with increasing average density, a distinct peak in the local density distribution is displaced toward higher values.

Evolution of the pore size distribution in sheared binary glasses.

Molecular dynamics simulations are carried out to investigate mechanical properties and porous structure of binary glasses subjected to steady shear. The model vitreous systems were prepared via thermal quench at constant volume to a temperature well below the glass transition. The quiescent samples are characterized by a relatively narrow pore size distribution whose mean size is larger at lower glass densities. We find that in the linear regime of deformation, the shear modulus is a strong function of porosity, and the individual pores become slightly stretched while their structural topology remains unaffected. By contrast, with further increasing strain, the shear stress saturates to a density-dependent plateau value, which is accompanied by pore coalescence and a gradual development of a broader pore size distribution with a discrete set of peaks at large length scales.

Interfacial adhesive properties between a rigid-rod pyromellitimide molecular layer and a covalent semiconductor via atomistic simulations.

We conducted a comprehensive atomistic simulation study of the adhesive properties of aromatic rigid-rod poly-[(4,4'diphenylene) pyromellitimide] on a dimer-reconstructed silicon surface. We describe the structural developments within the adherent's interfacial region at the atomistic scale, and evaluate the energetics of the adhesive interactions between bimaterial constituents. In particular, we observe a transition between noncontact and contact adhesion regimes as a function of the interfacial bonding strength between the polyimide repeat units and the silicon substrate. This transition is manifest by a three- to four-fold increase in adhesive energy, which is entirely attributable to structural relaxation in the organic layer near the interface, revealing the importance of accurately describing structural details at interfaces for reliable interfacial strength predictions. The underlying molecular reconfigurations in the pyromellitimide layer include preferred orientation of the rigid-rod molecules, molecular stacking, ordering, and the local densification. The role of each of these factors in the adhesive behavior is analyzed and conclusively described. Where possible, simulation results are compared with theoretical model predictions or experimental data.

Computational nanomechanics and thermal transport in nanotubes and nanowires.

Representative results of computer simulation and/or modeling studies of the nanomechanical and thermal transport properties of an individual carbon nanotube, silicon nanowire, and silicon carbide nanowire systems have been reviewed and compared with available experimental observations. The investigated nanomechanical properties include different elastic moduli of carbon nanotubes, silicon nanowires, and silicon carbide nanowires, all obtained within their elastic limits. Moreover, atomistic mechanisms of elastic to plastic transition under external stresses and yielding of carbon nanotubes under experimentally feasible temperature and strain rate conditions are discussed in detail. The simulation and/or modeling results on thermal properties, presented in this work, include vibrational modes, thermal conductivity and heat pulse transport through single carbon nanotubes, and thermal conductivity of silicon nanowires.

Calculation of vertical correlation probability in Ge/Si(001) shallow island quantum dot multilayer systems.

We investigate the behavior of the island vertical pairing probability in multilayer systems of Ge island quantum dots (QDs) in Si(001). By combining a simple kinetic rate model with our previously reported atomistic simulation results on the nature of the stress field from buried shallow Ge islands having {105}-oriented sidewalls, we derive an analytical expression for correlation probability as a function of the parameters characterizing the multi-QD systems. The approach is based upon continuum mechanochemical potential model, which allows one to introduce necessary elements of the kinetics of island formation in a simple way. We compare the model predictions with available experimental data and find that the model provides a satisfactory description of the coupling probability. The correlation probability behavior as a function of capping layer thickness, Ge island size, interisland distance, and Ge adatom diffusion length is investigated within the framework of the developed model.

Emergence of large-scale vorticity during diffusion in a random potential under an alternating bias.

Conventional wisdom indicates that the presence of an alternating driving force will not change the long-term behavior of a Brownian particle moving in a random potential. Although this is true in one dimension, here we offer direct evidence that the inevitable local symmetry breaking present in a two-dimensional random potential leads to the emergence of a local ratchet effect that generates large-scale vorticity patterns consisting of steady-state net diffusive currents. For small fields the spatial correlation function of the current follows a logarithmic distance dependence, while for large external fields both the vorticity and the correlations gradually disappear. We uncover the scaling laws characterizing this unique pattern formation process, and discuss their potential relevance to real systems.