We present in this communication the preparation and the solid state NMR characterization of phenyl phosphonic acid encapsulated both in pure and aminopropyl-modified SBA-15 mesoporous silica materials. The 31P and 1H MAS studies revealed two radically different behaviors of the confined molecules. The included phosphonic acid in SBA-15 is submitted to a confinement effect that implies a weak interaction with the SiO2 surface and a relative mobility at room temperature. On the contrary, phenyl phosphonic acid molecules in the aminopropyl modified sample possess a strong interaction with the hybrid surface of the material. This finding is supported by a two dimensional double-quantum 1H experiment that revealed the close proximity between phenyl phosphonic acid and aminopropyl surface groups.

This paper reports on a molecular simulation study of the thermodynamics, structure and dynamics of water confined at ambient temperature in charged silica nanopores of a width H = 10 and 20 Å. The adsorption isotherms for water resemble those observed for experimental samples; the adsorbed amount increases continuously in the multilayer adsorption regime until a jump occurs due to capillary condensation of the fluid within the pore. Strong layering of water in the vicinity of the silica surfaces is observed as marked density oscillations are seen up to 8 Å from the surface in the density profiles for confined water. Our results also indicate that the Ca2+ counterions remain in a space close to the silica surface whatever the pore width and the adsorbed amount of water. For all pore sizes and adsorbed amounts, the self-diffusivity of confined water is lower than the bulk due to the strong hydrophilic nature of the pore surface. Our results also suggest that the self-diffusivity of confined water is sensitive to the adsorbed amount of water molecules.

The combination of active and passive microrheology using magnetic probes engulfed inside living cells demonstrates the violation of the fluctuation dissipation theorem in cells. It is proposed to quantify the deviation from the in equilibrium situation with an effective temperature. Each magnetic probe then serves as a local thermometer within the cells. The response of pairs of magnetic beads of two diameters (1 and 2.8 μm) to an oscillating magnetic field is analyzed to measure the viscoelastic complex modulus in the beads environment (active measurement). The spontaneous motion of the beads is tracked to compute their mean square displacements (passive measurement). The effective temperature is derived using an extension of the fluctuation dissipation theorem.

Coarse-grained network models of proteins successfully predict equilibrium properties related to collective modes of motion. In this study, the network construction strategies and their systematic application to proteins are used to explain the role of network models in defining the collective properties of the system. The analysis is based on the radial distribution function, a newly defined angular distribution function and the spectral dimensions of a large set of globular proteins. Our analysis shows that after reaching a certain threshold for cut-off distance, network construction has negligible effect on the collective motions and the fluctuation patterns of the residues.

With characteristic time constants for polymer dynamics, namely τs (the segment fluctuation time), τe (the entanglement time), and τR (the longest Rouse relaxation time), the time scales of particular interest (i) t<τs, (ii) τs<t<τe, and (iii) τe<t<τR will be discussed and compared with experimental data. These ranges correspond to the chain-mode length scales (i) l<b, (ii) b<l<d2/b, and (iii) d2/b<l<L, where b is the statistical segment length, d is the dimension of constraints by entanglements and/or confinement, and L is the chain contour length. Based on Langevin-type equations-of-motion coarse-grained predictions for the mean-squared segment displacement and the spin-lattice relaxation dispersion will be outlined for the scenarios “freely-draining”, “entangled”, and “confined”. In the discussion we will juxtapose “local” versus “global” dynamics on the one hand, and “bulk” versus “confined” systems on the other.