Research

Data-driven autonomous scale-bridging of dislocation dynamics from atomistics

Traditional methods for deriving mobility laws for mesoscale defect dynamics rely on phenomenological models of the underlying physics, whose free parameters are in turn fit to a small number of atomistic-scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome in case of materials with complex stress, temperature, and local environment dependence.

Strong entropic effects in kinetics of dislocation reactions

The kinetics of dislocation reactions, such as dislocation multiplication, controls the plastic deformation in crystals beyond their elastic limit. These reactions are however often very difficult to systematically characterize experimentally, and recent computational investigations suggest that very expensive and complex simulation methodologies are often essential for accurate predictions, greatly limiting their broad use. By combining an analytic approach to the estimation of changes in vibrational entropy along the pathway of dislocation reaction with a variational transition state theory (TST) approach, we demonstrate quantitatively accurate description of the nucleation kinetics of dislocations from free surfaces. 

With the help of a data-driven maximum likelihood based Bayesian type estimation of kinetic parameters and a simplified rate model, we uncover the underlying elusive physics behind unusual rate-prefactors observed single crystal nanowire deformation experiments. 

Electric field and thermal stress driven breakdown of metallic electrode surfaces

Understanding the underlying factors responsible for higher-than-anticipated local field enhancements that trigger vacuum breakdown on pristine metal surfaces is crucial for the development of devices capable of withstanding intense operational fields. In this study, we investigate the behavior of nominally flat copper electrode surfaces exposed to electric fields of hundreds of MV/m. Our novel approach considers curvature-driven diffusion processes to elucidate the formation of sharp breakdown precursors. To do so, we develop a mesoscale finite element model that accounts for driving forces arising from both electrostatic and surface-tension-induced contributions to the free energy.

Our findings reveal a dual influence: surface tension tends to mitigate local curvature, while the electric field drives mass transport toward regions of high local field density.

This phenomenon triggers the growth of sharper protrusions, ultimately leading to a rapid enhancement of local fields and, consequently, system instability. Furthermore, we delineate supercritical and subcritical regimes across a range of initial surface roughness. Our numerical results align closely with experimentally reported data, predicting critical precursor formation fields in the range of 200 MV/m to 500 MV/m.

Coupling electric fields with nanoscale defect dynamics via long-range charge equilibration MD

A notable impediment in maintaining high electric fields in accelerating structures is the onset of breakdown events. While bulk mechanical properties of the materials are known to significantly affect the breakdown propensity, the underlying mechanisms coupling electric fields to bulk plastic deformation in experimentally relevant thermal and electrical loading conditions remain to be identified at the atomic scale. We present the results of large-scale molecular dynamics simulations (MD) to investigate a possible mode of coupling. 

Implementing a charge-equilibration formalism incorporated in a classical MD model, we show that the creation of surface slipped steps can couple to electric fields in a way that enhances local stresses and facilitates further activation of existing dislocation sources. 

Bending and interlayer shear moduli of ultrathin boron nitride nanosheet

Here, we explore the bending rigidity of ultrathin hexagonal boron nitride nanosheet (BNNS) through quantifying its self-folded conformations on flat substrates by using atomic force microscopy and atomistic simulations. The bending stiffness of two to six layers of BNNS is found to follow a power function of its thickness with a power index of ~2.35 and is substantially higher than that of comparable graphene. In contrast, monolayer graphene possesses a higher stiffness than its h-BN counterpart. 

We attribute the high bending stiffness of multilayer BNNS to its partially ionic B–N bondings and corrugated electronic structures, which result in one order of magnitude stronger interlayer shear interaction in h-BN than in graphene. The higher out-of-plane bending and interlayer shear rigidities suggest that unlike graphene, BNNS is less prone to interlayer delamination-induced structural inhomogeneities (e.g. shearing, rippling and kinks) and thus is suitable as a building block for atomically thin electronics and a reinforcing filler for nanocomposites.

Mechanics of interfaces in graphene-based nanostructures

Interfaces are ubiquitous in graphene-based nanostructured materials. The resulting electrical, optical, chemical and mechanical properties are substantially governed by the type of interactions acting across these interfaces. For example, the interfacial interactions for an amorphous polymer matrix surrounding carbon-nanotube filaments could involve weak van der Waals forces or strong covalent interactions through the formation of cross-link bonds, thus resulting in the wide-ranging interfacial shear strength values reported by nanotube pull-out experiments. Crystalline close-packed metals such as titanium and aluminum also demonstrate contrasting adhesion properties along graphene-metal interfaces depending on the extent of thermal annealing which results in oxide formation along the interfaces.