Synthesis and properties of a new AB-cross-linked copolymer membrane system

The alcohol permeability and permselectivity properties as well as the morphology of membranes made of a newly developed AB-cross-linked copolymer system composed of elastomeric and glassy components were investigated. The copolymer was synthesized by a hydrosilylation reaction between poly(styrene-stat-isoprenes) (Mn from 40,000 to 100,000 g/mol) with high content in unsaturated side groups (≈ 60% of entire isoprene content) and polyhydrogen polysiloxanes with varying SiH content (0.75 10.7 mol %) and molecular mass, Mn, from 2,500 to 36,000 g/mol. A two-track approach was taken to determine the morphology of the copolymer system. The first employed the usual polymer characterization methods such as electron microscopy, DSC, IR spectroscopy, the density gradient method, and mechanical measurements. For the second approach, different copolymer permeability models were tested so as to give an insight into the copolymer morphology. As a final step, the permeability and permselectivity properties were correlated with the morphological structure of the copolymer system. It was observed that the respective continuous microphase dominated the copolymer's physical properties, as, e.g., permeability, permselectivity, and mechanical properties. The microphase inversion in the copolymer system was proved by the permeability/permselectivity as well as by the mechanical measurements

Two-chamber lattice model for thermodiffusion in polymer solutions

When a temperature gradient is applied to a polymer solution, the polymer typically migrates to the colder regions of the fluid as a result of thermal diffusion (Soret effect). However, in recent thermodiffusion experiments on poly(ethylene-oxide) (PEO) in a mixed ethanol/water solvent it is observed that for some solvent compositions the polymer migrates to the cold side, while for other compositions it migrates to the warm side. In order to understand this behavior, we have developed a two-chamber lattice model approach to investigate thermodiffusion in dilute polymer solutions. For a short polymer chain in an incompressible, one-component solvent we obtain exact results for the partitioning of the polymer between a warm and a cold chamber. In order to describe mixtures of PEO, ethanol, and water, we have extended this simple model to account for compressibility and hydrogen bonding between PEO and water molecules. For this complex system, we obtain approximate results for the composition in the warmer and cooler chambers that allow us to calculate Soret coefficients for given temperature, pressure, and solvent composition. The sign of the Soret coefficient is found to change from negative (polymer enriched in warmer region) to positive (polymer enriched in cooler region) as the water content of the solution is increased, in agreement with experimental data. We also investigate the temperature dependence of the Soret effect and find that a change in temperature can induce a change in the sign of the Soret coefficient. We note a close relationship between the solvent quality and the partitioning of the polymer between the two chambers, which may explain why negative Soret coefficients for polymers are so rarely observed.Comment: 12 pages, 8 figure

SOM-VAE: Interpretable Discrete Representation Learning on Time Series

High-dimensional time series are common in many domains. Since human cognition is not optimized to work well in high-dimensional spaces, these areas could benefit from interpretable low-dimensional representations. However, most representation learning algorithms for time series data are difficult to interpret. This is due to non-intuitive mappings from data features to salient properties of the representation and non-smoothness over time. To address this problem, we propose a new representation learning framework building on ideas from interpretable discrete dimensionality reduction and deep generative modeling. This framework allows us to learn discrete representations of time series, which give rise to smooth and interpretable embeddings with superior clustering performance. We introduce a new way to overcome the non-differentiability in discrete representation learning and present a gradient-based version of the traditional self-organizing map algorithm that is more performant than the original. Furthermore, to allow for a probabilistic interpretation of our method, we integrate a Markov model in the representation space. This model uncovers the temporal transition structure, improves clustering performance even further and provides additional explanatory insights as well as a natural representation of uncertainty. We evaluate our model in terms of clustering performance and interpretability on static (Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST images, a chaotic Lorenz attractor system with two macro states, as well as on a challenging real world medical time series application on the eICU data set. Our learned representations compare favorably with competitor methods and facilitate downstream tasks on the real world data.Comment: Accepted for publication at the Seventh International Conference on Learning Representations (ICLR 2019

Recent advances in the formation of phase inversion membranes made from amorphous or semi-crystalline polymers

Structural characteristics in membranes formed by diffusion induced phase separation processes are discussed. Established theories on membrane formation from ternary systems can be extended to describe the effects of high or low molecular weight additives. A mechanism for the formation of nodular structures in the top layer of ultrafiltration membranes is presented. In the last part structures arising from polymer crystallization during immersion precipitation are discussed

Facultative secondary lecithotrophy in the megalopa of the shrimp Lysmata seticaudata (Risso, 1816) (Decapoda : Hippolytidae) under laboratory conditions

Certain decapod crustaceans can catabolize internal reserves to undergo partial or full larval development. This feature is termed secondary lecithotrophy, if energy used results from plankton derived organic matter accumulated Ig earlier larval stages. The present work reports the ability of Lysmata seticaudata megalopa to moll to the first juvenile stage in the absence of food. Unlike previous records of secondary lecithotrophy displayed by nonfeeding last larval stages of hermit crabs and spiny lobsters, the megalopa of L. seticaudata retains its feeding capacity. This is the first time such a feature has been reported in decapods, and the term facultative secondary lecithotrophy is proposed. The build up of energy reserves continues during the last zoeal stage of L. seticaudata, with starved zoea IX failing to molt to megalopa. Energy reserves that enable starved megalopa to molt to juvenile seem to be partially depleted, with starved juveniles produced either from, starved or fed megalopae being unable to molt to the next juvenile stage. The longer resistance of starved juveniles produced from fed megalopae (nine days), compared to that of starved juveniles produced from starved megalopae (five days), indicates that some energy reserves may pass to juvenile, not being totally depleted at metamorphosis.info:eu-repo/semantics/publishedVersio

Non-aqueous retention measurements: ultrafiltration behaviour of polystyrene solutions and colloidal silver particles

The retention behaviour of polyimide ultrafiltration membranes was investigated using dilute solutions of polystyrene in ethyl acetate as test solutions. It is shown that flow-induced deformation of the polystyrene chains highly affects the membrane retention. This coil-stretch transition is not instantaneous, but gradual. The concept of a deformation resistance has been ontroduced to explain this behaviour. This concept can be applied to describe the flux behaviour of the membranes during the tests as well. Solute deformation allows comparison of the pore size distributions of the membranes qualitatively. Retention measurements were also performed with silver sol particles that were prepared in mixtures of ethanol and water; these sols remain stable as long as the ethanol concentration does not exceed 57 vol%. The sols were completely retained by the membranes, which is probably caused by the fact that the effective diameter of the particles is much larger than that observed by transmission electron microscopy

Characterization of hemodialysis membranes by inverse size exclusion chromatography

Inverse size exclusion chromatography (i-SEC) was used to characterize three different cellulosic hollow fiber hemodialysis membranes, i.e. low-flux cuprophan and hemophan and high-flux RC-HP400A. With the i-SEC technique the pore size distribution and porosity of a membrane can be determined and adsorption phenomena can be studied. The membranes showed clear differences in pore size and porosity, the high-flux RC-HP400A membrane has a larger pore size as well as a higher porosity. For all the membranes it was found that the elution curves were best described by a homoporous pore volume distribution. It appeared that the bound or non-freezing water in the membranes was at least partly accessible to solutes. The test molecules creatinine and vitamin B 12 both adsorbed to the cellulosic membranes. The adsorption behavior of creatinine was strongly dependent on the NaCl concentration present. The observations could be explained by assuming that cuprophan and RC-HP400A are negatively charged whereas hemophan is positively charged due to the modification with N,N-diethylaminoethyl ether. The net charge of the hemophan is smaller