Perspectives in process analytics using low field NMR.

Low field NMR is a powerful analytical tool which creates an enormous added value in process analytics. Based on specific applications in process analytics and perspectives for low field NMR in form of spectroscopy, relaxation, diffusion, and imaging in quality control, diverse applications and technical realizations like spectrometers, time domain NMR, mobile NMR sensors and MRI will be discussed.

Entrance effects at nanopores of nanocapsules functionalized with poly(ethylene glycol) and their flow through nanochannels.

We studied the effect of poly(ethylene glycol) (PEG) on the extrusion of large, multilamellar nanocapsules (also called liposomes or vesicles) through nanochannels with a length of 6 microm. For the generation of the nanocapsules, we used a lipid mixture with lecithin consisting of saturated and unsaturated fatty acids (dipalmitoylphosphatidylcholine (DPPC) and dioleoylphosphatidylcholine (DOPC)), cholesterol, and 2-8 mol % PEG linked to a lipid anchor (distearoylphosphatidylethanolamine (DSPE)) or the plain lipid anchor without PEG. An increase in PEG leads to a decrease of the critical tension for nanocapsule rupture (lysis tension) between 20-30%, whereas the pure lipid anchor does not produce any differences. We interpret these findings to be produced by a partial intrusion of the polymeric chain into the phospholipid bilayer of the nanocapsule which weakens its tensile strength. We evaluate statistically the discrepancies of lysis tensions found for different channels widths (50-100 nm) and two or four channels in series. Comparing our results on the flow resistance of either nanocapsules or pure water with lubrication theory, we find that the calculated viscous forces are not sufficient to account for the measured friction of nanocapsules. This shows that the nanocapsules are decelerated in the nanochannels by van der Waals interactions between channel and capsule walls and the intermediate water layer. The strength of these forces is 24 times higher for PEG and 94 times higher for the pure lipid anchor than the respective calculated viscous forces alone, showing that nanocapsule flow in nanochannels cannot be considered under the classical continuum assumption of the intermediate water layer.

Characterizing dispersion and fragmentation of fractal, pyrogenic silica nanoagglomerates by small-angle X-ray scattering.

Typical characterization of nanoparticle dispersion and compounding processes by dynamic light scattering (DLS) and TEM lack quantitative information on fractal structure, aggregation number, and specific surface area. In this work a synchrotron ultra-small-angle X-ray scattering (USAXS) investigation on diffusion flame and 'Aerosil' silica powders, as well as on their desagglomeration by high-pressure liquid dispersion (200-1400 bar) is presented. Primary particle size, polydispersity, and specific surface area are measured for powders, stirred-in dispersions, and after high-pressure processing with identical results, showing the in-situ applicability of USAXS. These parameters, as well as the hard aggregate mass fractal dimension, with typically Df = 2.15 representing reaction-limited cluster aggregation, are determined by synthesis process conditions. They are unchanged even at the highest hydrodynamic stresses; thus, neither comminution nor agglomerate restructuring nor re-agglomeration occurs. Fragmentation reflects in decreasing radii of gyration, which are compared to mobility equivalent radii from DLS in agreement with theory.

Turbulent hydrodynamic stress induced dispersion and fragmentation of nanoscale agglomerates.

High pressure dispersion nozzles of 2.5-10 mm length and 125 microm diameter have been characterized in terms of fluid dynamics and dispersion experiments at 100-1400 bar. Elongational stresses at the nozzle entry (5 x 10(5) Pa) and turbulent stresses up to 10(5) Pa at a Reynolds number of 25,000 in turbulent channel flow are identified crucial for desagglomeration and aggregate fragmentation. Maximum stresses are calculated on representative particle tracks and related to agglomerate breakage. Agglomerates in the experimental study are in the range of the Kolmogorov micro scale (100-400 nm) and therefore break due to turbulent energy dissipation in viscous flow. Bond strength distributions could be determined experimentally from particle size distributions and fluid dynamics simulations, with primary particle erosion determined as dispersion mechanism for diffusion flame silica particles. Nanoscale agglomerates show a power law scaling for breakage with scaling exponents diverging from theory of floc dispersion. This is attributed to their strong bonding by sinter necks.

First use of cognitive algorithms in investigations under compensated gravity.

In the present paper the use of cognitive algorithms for solving a wide spectrum of problems which often arise in investigations under compensated gravity is suggested. Applying such algorithms in the preparation and performance of experiments provides a substantial assistance to the experimentator as the behaviour of complex processes can be described and predicted correctly even when unexpected perturbations occur. Furthermore, an essential advantage of cognitive computing consists in the fact that the description and optimisation of the processes considered are possible also in such cases in which the corresponding basic equations are not known or not treatable practically. For convenience, the basic ideas of cognitive algorithms are discussed here. Due to their special relevance for investigations under compensated gravity algorithms based on fuzzy logic (FL) and artificial neuronal networks (ANN) are elucidated more in detail. In order to illustrate some advantages of cognitive computing exemplary results for the flow field induced by coaxial rotating disks are given. This represents the first attempt to use the benefits provided by cognitive algorithms in investigations under compensated gravity. The flow field between rotating disks plays an important role not only in experiments under compensated gravity but also in a wide range of terrestrial applications. A comparison of the results found by solving the Navier-Stokes equations and those from the prediction performed by ANN adequately trained shows an excellent agreement. However, the calculation times needed by the ANN are significantly smaller than that of the direct numerical simulation. Therefore, the real time prediction of the results from a running experiment seems to be possible.