Gas diffusion in nanoporous carbon includes distinct diffusion modes: surface diffusion on the pore walls and non-surface diffusion away from pore walls. We have performed molecular dynamics (MD) simulations of Ar diffusion in disordered nanoporous carbon. The main objective of this work is to separate the surface diffusion and non-surface diffusion contributions so as to comprehend their respective dependency on the porous structure and testing conditions. The nanoporous carbon sample is obtained using the quenched molecular dynamics (QMD) method. Gas flows are generated by applying a constant external force on each Ar atom, mimicking a constant chemical potential gradient. The contributions from surface diffusion and non-surface diffusion are separated according to the distance of the gas atoms away from the pore wall. We show that the surface diffusivity is affected by the interactions between gas atoms and the pore walls, the temperature, and the loading.

Diffusion of tetrafluoromethane in aluminosilicate nanotubes was studied by means of 13C pulsed field gradient (PFG) NMR at 297 K. The measured data allow the estimation of the diffusivity of tetrafluoromethane inside the nanotubes as well as the diffusivity for these molecules undergoing fast exchange between many nanotubes. The results support the assumption about the one-dimensional nature of the tetrafluoromethane diffusion inside nanotubes.

In the modelling of translational motion, the concepts of frequency-dependent (of the angular fluctuations of the velocity field) self-diffusion and the dispersion tensor are commonly used in its characterisation. Both of these parameters are related to velocity autocorrelation. An alternative means of modelling translational motion is via the equilibrium and nonequilibrium fluctuation-dissipation theorem in classical statistical mechanics. This alternative approach provides further insight into the molecular level processes occurring in the system. Here both of these theoretical fluctuation-dissipation approaches are employed to determine expressions for energy dissipation in simple equilibrium systems exhibiting asymptotic and preasymptotic diffusion and dispersion phenomena and also in a nonequilibrium preasymptotic system involving dispersion within and beyond the upper limit of heterogeneity of an isotropic porous medium. As an example the permeability of porous media due to diffusion and dispersion are studied and it is shown how a frequency-dependent permeability can be treated as a phasor.

Ni based superalloys can be welded by diffusion bonding. Temperature, diffusion coefficient, activation energy and Boltzmann constant influence the quality of diffusion bonding, so obtaining the best condition for welding is considered. Showing the suitable condition for diffusion welding of nickel-based superalloys is the aim of this paper.

The LDD model was first applied to Arsenic concentration profiles determined in surface diffusion experiments by Yoshida and Arai [1]. The new method presented is based on a mathematical convolution with a delta-function-like concentration profile. By comparing the LDD approximation of post-surface diffusion with post-implant diffusion experiments, the same LDD model parameter r is found to hold for both experimental arrangements. This work found that post-implant diffusivity is concentration dependant and this might indicate an anomalous diffusion mechanism for Arsenic.

The solvent resistance properties of the unsaturated polyster and their montmorillonite filled nanocomposites are studied in acetic through equilibrium swelling method at different temperatures. The kinetics of sorption is studied by using the equation of transport phenomena. The values of ‘n’ in solvent transport equation are found to be below ‘0.5’, showing the non-Fickian or pseudo-Fickian transport in the polymer. The dependence of diffusion coefficient on composition and temperature has been studied for all polymeric samples. The diffusion coefficient of unsaturated polyester samples decreases with an increase in unsaturated acid content. The nanocomposite samples show low diffusion coefficient than corresponding pristine polymers. The diffusion coefficient, sorption coefficient and permeation coefficient increase with an increase in temperature for all samples. The crosslink density for neat polymer with varied unsaturated acid content ranges from 2.98 to 3.52 ×105mol/cm3. For the nanocomposite samples it ranges from 3.70 to 5.72 × 105 mol/cm3.

A number of random processes in various fields of science is described by phenomenological equations of motion containing stochastic forces, the best known example being the Langevin equation (LE) for the Brownian motion (BM) of particles. Long ago Vladimirsky (1942) in a little known paper proposed a simple method for solving such equations. The method, based on the classical Gibbs statistics, consists in converting the stochastic LE into a deterministic equation for the mean square displacement of the particle, and is applicable to linear equations with any kind of memory in the dynamics of the system. This approach can be effectively used in solving many of the problems currently considered in the literature. We apply it to the description of the BM when the noise driving the particle is exponentially correlated in time. The problem of the hydrodynamic BM of a charged particle in an external magnetic field is also solved.

A method for rapid acquisition of multiple scans of NMR sequences is presented. The method initially applies two RF-pulses in combination with two magnetic field gradient pulses of opposite polarity, different strength and different duration. The basic idea is to spoil any magnetization in any direction before by letting the system recover to some degree of restoration of the thermal equilibrium magnetization. Thereafter any pulse sequence can be applied, and the next scan may be run immediately after the end of the pulse sequence. Thus one avoids the 5 times T1 delay between each scan. A set of PFG sequences are presented that apply the spoiler recovery method for significant reduction in acquisition time, and the method has been verified at 0.5 Tesla as well as at 11.7 Tesla.

The 10th Bologna Conference on “Magnetic Resonance in Porous Media” was among the impressive events which, dedicated to the 600th anniversary of Leipzig University in December 2009, attracted colleagues from all over the world. The conference excursion took the participants to Ferropolis, a place north of Leipzig, equipped with impressive remainings of an old mining site, including huge conveyer bridges. Ferropolis also visualizes, in some way, Leipzig as a center of industry and science, with coal mining in its vicinity as one of the sources of industrial development and, hence, as a promoter of scientific progress. With pleasure I followed the invitation to talk on this occasion, by merging a plenary lecture with an after-dinner speech, about Leipzig’s special affection towards the topic of the conference. This contribution is a reproduction of my talk, accompanied by most of the presented slides.

NMR T2 distribution measurement is our chosen everyday method for NMR logging while drilling oil and gas wells. This method yields straightforward preparation and execution of the job as well as a normally easy interpretation of the measured data. For instance, gas and light oil discrimination against water is feasible by direct observation of the T2 distribution. A condition for this measurement method is a NMR logging tool that hardly moves while drilling and in addition uses a small static magnetic field gradient and short inter-echo time TE to be motion tolerant. Using data compression techniques, we can transmit by mud pulse telemetry the T2 distribution in real time from the borehole to the surface. This enables the drilling operator to use the NMR data for real-time decisions such as geosteering.