Deposition on a vicinal surface with alternating rough and smooth steps is described by a solid-on-solid model with anisotropic interactions. Kinetic Monte Carlo (KMC) simulations of the model reveal step-pairing in the absence of any additional step attachment barriers. We explore the description of this behavior within an analytic BCFtype step dynamics treatment. Without attachment barriers, conventional kinetic coefficients for the rough and smooth steps are identical, as are the predicted step velocities for a vicinal surface with equal terrace widths. However, we determine refined kinetic coefficients from a two-dimensional discrete deposition-diffusion equation formalism which accounts for step structure. These coefficients are generally higher for rough steps than for smooth steps, reflecting a higher propensity for capture of diffusing terrace adatoms due to a higher kink density. Such refined coefficients also depend on the local environment of the step and can even become negative (corresponding to net detachment despite an excess adatom density) for a smooth step in close proximity to a rough step. Our key observation is that incorporation of these refined kinetic coefficients into a BCF-type step dynamics treatment recovers quantitatively the mesoscale steppairing behavior observed in the KMC simulations.

Torsion-induced mechanical couplings of single-walled carbon nanotubes (SWCNTs) are studied by using molecular dynamics simulations. We show that these mechanical couplings are strongly dependent on the chirality of SWCNTs. In particular, the structural difference between armchair and zigzag nanotubes can remarkably influence the Poynting effect [J. H. Poynting, Proc. R. Soc. Lond. A 82, 546 (1909)], i.e., torsion-induced axial strain response. For SWCNTs with large aspect ratios and small chiral angles, an intriguing torsion-induced bending effect is observed. This effect results from the release of torsion-induced axial stress and may probably affect the torsional oscillation behavior of nanoelectromechanical systems based on SWCNTs.

We study NaCl ion-pair dissociation in a dilute aqueous solution using computer simulations both for the full system with long-range Coulomb interactions and for a well-chosen reference system with short-range intermolecular interactions. Analyzing results using concepts from Local Molecular Field (LMF) theory and the recently proposed AI-based analysis tool “State predictive information bottleneck” (SPIB), we show that the system with short-range interactions can accurately reproduce the transition rate for the dissociation process, the dynamics for moving between the underlying metastable states, and the transition state ensemble. Contributions from long-range interactions can be largely neglected for these processes because long-range forces from the direct interionic Coulomb interactions are almost completely canceled (>90%) by those from solvent interactions over the length scale where the transition takes place. Thus, for this important monovalent ion-pair system, short-range forces alone are able to capture detailed consequences of the collective solvent motion, allowing the use of physically suggestive and computationally efficient short-range models for the dissociation event. We believe that the framework here should be applicable to disentangling mechanisms for more complex processes such as multivalent ion disassociation, where previous work has suggested that long-range contributions may be more important.

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