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Rubber-based nanocomposites prepared by solid-phase mixing with precipitated silica nanoparticles are typically stronglyaggregated systems with different levels of spatial organization, as highlighted by our group in the past [1]. The strategythat we developed these past years was to investigate such systems based on the study of simplified industrial sampleswith ingredients limited to a strict minimum. The analysis of small-angle X-ray scattering data can then be performed onthe scale of a micrometric simulation box. Tens of thousands of “model” nanoparticles are embedded in the matrix, andtheir dispersion strongly affects both the mechanical properties of the material, and the scattered intensity. A statisticalmethod based on a reverse Monte Carlo solution of this many-parameter scattering problem will be presented, showingthat some key features like percolation can be described [2].Another key feature of rubber nanocomposites refers to the influence of the filler surfaces on the polymer structure anddynamics, and some recent progress will be discussed [3]. In particular, we have studied blends of short and long chains,where one chain type is deuterated, by small-angle neutron scattering. Different degrees of spatial segregation could beidentified recently, including a peculiar, “fish-shaped” interfacial gradient characterized also by reverse Monte Carlosimulations, this time of the interface.[1] Guilhem P. Baeza, Anne-Caroline Genix, C. Degrandcourt, Laurent Petitjean, Jérémie Gummel, Marc Couty, Julian Oberdisse, Macromolecules 2013, 46, 317−329(cover article)[2] Musino D, Genix A-C, Chauveau E, Bizien T, Oberdisse J, Nanoscale 2020, 12:3907.[3] A.C. Genix, V. Bocharova, B. Carroll, P. Dieudonné-George, M. Sztucki, R. Schweins, A. P. Sokolov, and Julian Oberdisse, ACS Applied Materials and Interfaces,2021, in press

Rubber-based nanocomposites prepared by solid-phase mixing with precipitated silica nanoparticles are typically strongly aggregated systems with different levels of spatial organization, as highlighted by our group in the past [1]. The strategy that we developed these past years was to investigate such systems based on the study of simplified industrial samples with ingredients limited to a strict minimum. The analysis of small-angle X-ray scattering data can then be performed on the scale of a micrometric simulation box. Tens of thousands of “model” nanoparticles are embedded in the matrix, and their dispersion strongly affects both the mechanical properties of the material, and the scattered intensity. A statistical method based on a reverse Monte Carlo solution of this many-parameter scattering problem will be presented, showing that some key features like percolation can be described [2].Another key feature of rubber nanocomposites refers to the influence of the filler surfaces on the polymer structure and dynamics, and some recent progress will be discussed [3]. In particular, we have studied blends of short and long chains, where one chain type is deuterated, by small-angle neutron scattering. Different degrees of spatial segregation could be identified recently, including a peculiar, “fish-shaped” interfacial gradient characterized also by reverse Monte Carlo simulations, this time of the interface.References[1] Guilhem P. Baeza, Anne-Caroline Genix, C. Degrandcourt, Laurent Petitjean, Jérémie Gummel, Marc Couty, Julian Oberdisse, Macromolecules 2013, 46, 317−329 (cover article)[2] Musino D, Genix A-C, Chauveau E, Bizien T, Oberdisse J, Nanoscale 2020, 12:3907.[3] A.C. Genix, V. Bocharova, B. Carroll, P. Dieudonné-George, M. Sztucki, R. Schweins, A. P. Sokolov, and Julian Oberdisse, ACS Applied Materials and Interfaces, 2021, in press

Understanding the kinetic selectivity of carbon nanotube growth at the scale of individual nanotubes is essential for the development of high chiral selectivity growth methods. Here we demonstrate that homodyne polarization microscopy can be used for high-throughput imaging of long individual carbon nanotubes under real growth conditions (at ambient pressure, on a substrate), and with sub-second time resolution. Our in situ observations on hundreds of individual nanotubes reveal that about half of them grow at a constant rate all along their lifetime while the other half exhibits stochastic changes in growth rates, and switches between growth, pause and shrinkage. Statistical analysis shows that the growth rate of a given nanotube essentially varies between two values, with similar average ratio (~1.7) regardless of whether the rate change is accompanied by a change in chirality. These switches indicate that the nanotube edge or the catalyst nanoparticle fluctuates between different configurations during growth.

The field of ion transport through carbon nanotubes (CNTs) is marked by a large variability of the ionic conductance values reported by different groups. There is also a large uncertainty concerning the relative contributions of channel and access resistances in the experimentally measured currents, both depending on experimental parameters (nanotube length and diameter). In this perspective article, we discuss the ionic conductance values reported so far in the case of 2 individual CNTs and compare them with standard nano-fluidic models considering both the access and channel resistances. With a view toward guiding experimentalists, we thus show in which conditions the access or the channel resistance can predominate in CNTs. We explain in particular that it is not justified to use phenomenological models neglecting the channel resistance in the case of micrometer-long CNTs. This comparison reveals that most experimental conductance values can be explained in the framework of current nanofluidic models by considering experimental variations of slip length and surface charge density and that just a few extraordinarily high values cannot be accounted for even using extreme parameter values. Finally, we discuss how to complete existing models and how to improve the statistical reliability of experimental data in the field.