Author Correction: A nano-mechanical instability as primary contribution to rolling resistance.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A nano-mechanical instability as primary contribution to rolling resistance.

Rolling resistance ranks among the top ten automobile megatrends, because it is directly linked to fuel efficiency and emissions reduction. The mechanisms controlling this phenomenon are hidden deeply inside the complexity of tire tread materials and do elude direct experimental observation. Here we use atomistic molecular modelling to identify a novel nano-mechanical mechanism for dissipative loss in silica filled elastomers when the latter are subjected to dynamic strain. The force-vs-particle separation curve of a single silica particle-to-silica particle contact, embedded inside a polyisoprene rubber matrix, is obtained, while the contact is opened and closed by a cyclic force. We confirm the occurrence of spontaneous relative displacements ('jolts') of the filler particles. These jolts give rise to energy dissipation in addition to the usual viscous loss in the polymer matrix. As the temperature is increased the new loss mechanism becomes dominant. This has important technical implications for the control and reduction of tire rolling resistance as well as for many other elastomer composite applications involving dynamic loading.

Multiscale approach to equilibrating model polymer melts.

We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed to be computationally effective at each scale. Density fluctuations in the melt structure above the tube scale are minimized through a Monte Carlo simulated annealing of a lattice polymer model. Subsequently the melt structure below the tube scale is equilibrated via the Rouse dynamics of a force-capped Kremer-Grest model that allows chains to partially interpenetrate. Finally the Kremer-Grest force field is introduced to freeze the topological state and enforce correct monomer packing. We generate 15 melts of 500 chains of 10.000 beads for varying chain stiffness as well as a number of melts with 1.000 chains of 15.000 monomers. To validate the equilibration process we study the time evolution of bulk, collective, and single-chain observables at the monomeric, mesoscopic, and macroscopic length scales. Extension of the present method to longer, branched, or polydisperse chains, and/or larger system sizes is straightforward.

Geometries of Second-Row Transition-Metal Complexes from Density-Functional Theory.

A data set of 19 second-row transition-metal complexes has been collated from sufficiently precise gas-phase electron-diffraction experiments and used for evaluating errors in DFT optimized geometries. Equilibrium geometries have been computed using 15 different combinations of exchange-correlation functionals in conjunction with up to three different effective core potentials. Most DFT levels beyond the local density approximation can reproduce the 29 metal-ligand bond distances selected in this set with reasonable accuracy and precision, as assessed by the mean and standard deviations of optimized vs experimentally observed bond lengths. The pure GGAs tested in this study all have larger standard deviations than their corresponding hybrid variants. In contrast to previous findings for first-row transition-metal complexes, the TPSSh hybrid meta-GGA is slightly inferior to the best hybrid GGAs. The ranking of some popular density functionals, for second-row transition-metal complexes, ordered according to decreasing standard deviation, is VSXC ≈ LSDA > BLYP > BP86 > B3LYP ≈ TPSSh > PBE hybrid ≈ B3PW91 ≈ B3P86. When zero-point vibrational corrections, computed at the BP86/SDD level, are added to equilibrium bond distances obtained from a number of density-functional/basis-set combinations, the overall performance in terms of mean and standard deviations from experiment is not improved. For a combined data set comprised of the first- and second-row transition-metal complexes the hybrid functionals B3P86, B3PW91, and the meta-GGA hybrid TPSSh afford the lowest standard deviations.