An Ordered Nanoporous Monolith from an Elastomeric Crosslinked Block Copolymer Precursor

Summary: An ordered nanoporous monolith was prepared from a poly(isoprene‐b‐dimethylsiloxane) (PI‐PDMS) hexagonally packed cylinder precursor. The PDMS cylinders were macroscopically aligned, the PI was crosslinked with dicumyl peroxide, and the PDMS was removed using tetrabutylammonium fluoride. The stability of the pores depended on the modulus of the matrix. At high crosslink density the pores were stable, but they collapsed at a low crosslink density. The nanoporous materials could be swollen in toluene.

A scanning electron micrograph of the end‐on view of crosslinked degraded poly(isoprene‐b‐dimethylsiloxane).     

Effect of pH on interface composition and on quality of oil-in-water emulsions made with hen egg yolk

Constituents of egg yolk are key ingredients of many food emulsions. They contribute to create an interfacial film between oil and water, which determines largely the characteristics of the emulsions. Food emulsions prepared with yolk are made at various pHs. However, the effect of pH on the adsorption of yolk constituents and on the composition of the interfacial film is not known. The present study deals with the influence of pH (3, 6 and 9), on protein interface concentration and composition, change in interfacial tension, and oil droplet diameter, of emulsions made with yolk. Emulsions were prepared as follows: 0.5% w/v of yolk; oil volume fraction: 0.375, homogenisation rate: 20 000 rpm/2 min. pH 6 provided the best conditions to prepare emulsion with yolk. The average diameter of oil droplets was lower at pH 6 (8.5 μm) than at pH 3 (11.8 μm) and pH 9 (13.5 μm). The interfacial protein concentration was higher at pH 6 (1.7 mg m⁻²) than at pH 3 and pH 9 (0.5 mg m⁻²). At pH 6, all the proteins of yolk, except phosvitin, were adsorbed at the interface and the interfacial tension at steady-state was lower (10 mN m⁻¹) than at pH 3 (15 mN m⁻¹) and pH 9 (30 mN m⁻¹). At pH 3, proteins at the interface are mainly phosvitin, and, at pH 9, some apoproteins of LDL and HDL. The pH modulates the composition of yolk proteins at the interface, mainly by modifying the net charge of the proteins causing their repulsion or dimerisation.     

On coupled gradient-dependent plasticity and damage theories with a view to localization analysis

Combinations of gradient plasticity with scalar damage and of gradient damage with isotropic plasticity are proposed and implemented within a consistently linearized format. Both constitutive models incorporate a Laplacian of a strain measure and an internal length parameter associated with it, which makes them suitable for localization analysis.The theories are used for finite element simulations of localization in a one-dimensional model problem. The physical relevance of coupling hardening/softening plasticity with damage governed by different damage evolution functions is discussed. The sensitivity of the results with respect to the discretization and to some model parameters is analyzed. The model which combines gradient-damage with hardening plasticity is used to predict fracture mechanisms in a Compact Tension test.     

The Kelvin–Nevanlinna–Royden criterion for p-parabolicity

We generalize the so called Kelvin–Nevanlinna–Royden criterion for the parabolicity of manifolds to the case of p-parabolicity for all . Received July 29, 1998; in final form September 25, 1998     

A novel and efficient alkyl radical trap in aqueous medium

A simple water soluble diselenide derivative 1 shows radical scavenger properties towards alkyl and hydroxyl radicals (k₃ (0°C)=6.8×10⁸ M⁻¹ s⁻¹) in Fenton-type chemistry. The reaction rate between produceded alkyl radicals 2 and the diselenide overwhelms self-termination and halogen transfer reactions.     

Pore Network Analysis of Resistivity Index for Water-Wet Porous Media

Pore network analysis is used to investigate the effects of microscopic parameters of the pore structure such as pore geometry, pore-size distribution, pore space topology and fractal roughness porosity on resistivity index curves of strongly water-wet porous media. The pore structure is represented by a three-dimensional network of lamellar capillary tubes with fractal roughness features along their pore-walls. Oil-water drainage (conventional porous plate method) is simulated with a bond percolation-and-fractal roughness model without trapping of wetting fluid. The resistivity index, saturation exponent and capillary pressure are expressed as approximate functions of the pore network parameters by adopting some simplifying assumptions and using effective medium approximation, universal scaling laws of percolation theory and fractal geometry. Some new phenomenological models of resistivity index curves of porous media are derived. Finally, the eventual changes of resistivity index caused by the permanent entrapment of wetting fluid in the pore network are also studied.Resistivity index and saturation exponent are decreasing functions of the degree of correlation between pore volume and pore size as well as the width of the pore size distribution, whereas they are independent on the mean pore size. At low water saturations, the saturation exponent decreases or increases for pore systems of low or high fractal roughness porosity respectively, and obtains finite values only when the wetting fluid is not trapped in the pore network. The dependence of saturation exponent on water saturation weakens for strong correlation between pore volume and pore size, high network connectivity, medium pore-wall roughness porosity and medium width of the pore size distribution. The resistivity index can be described succesfully by generalized 3-parameter power functions of water saturation where the parameter values are related closely with the geometrical, topological and fractal properties of the pore structure.     

Fluorinated Amphiphilic Block Copolymers: Combining Anionic Polymerization and Selective Polymer Modification

We report the preparation of novel fluorinated block copolymers using a two-step modification sequence. We first prepared model polyisoprene-poly-tert-butylmethacrylate block copolymers by anionic polymerization. Exposing these materials to difluorocarbene (generated by the thermolysis of hexafluoropropylene oxide) resulted in modification of the polyisoprene block to the corresponding difluorocyclopropane repeating unit without compromising the integrity of the poly-tert-butylmethacrylate block. Hydrolysis of the difluorocarbene-modified materials gave the corresponding difluorocarbene-modified polyisoprene-polymethacrylic acid diblock copolymers. These amphiphilic materials are expected to exhibit interesting self-assembly behavior in aqueous solution.     

Automated Raman Spectroscopy as a Tool for the High‐Throughput Characterization of Molecular Structure and Mechanical Properties of Polyethylenes

Raman spectroscopy, which does not require a time‐consuming sample preparation, is described as an analytical tool for the high‐throughput characterization of polyethylenes. The content of comonomer and the amount of methyl groups per 1 000 carbon atoms of polyethylenes can be predicted from Raman spectra using multivariate data analysis. In addition, macroscopic properties, such as density and elastic modulus as well as yield stress, can be derived from Raman spectra.

Raman spectra of selected metallocene‐catalyzed polyethylenes of different comonomer content.     

Structure prediction of cyclic peptides by molecular dynamics + machine learning

Recent computational methods have made strides in discovering well-structured cyclic peptides that preferentially populate a single conformation. However, many successful cyclic-peptide therapeutics adopt multiple conformations in solution. In fact, the chameleonic properties of some cyclic peptides are likely responsible for their high cell membrane permeability. Thus, we require the ability to predict complete structural ensembles for cyclic peptides, including the majority of cyclic peptides that have broad structural ensembles, to significantly improve our ability to rationally design cyclic-peptide therapeutics. Here, we introduce the idea of using molecular dynamics simulation results to train machine learning models to enable efficient structure prediction for cyclic peptides. Using molecular dynamics simulation results for several hundred cyclic pentapeptides as the training datasets, we developed machine-learning models that can provide molecular dynamics simulation-quality predictions of structural ensembles for all the hundreds of thousands of sequences in the entire sequence space. The prediction for each individual cyclic peptide can be made using less than 1 second of computation time. Even for the most challenging classes of poorly structured cyclic peptides with broad conformational ensembles, our predictions were similar to those one would normally obtain only after running multiple days of explicit-solvent molecular dynamics simulations. The resulting method, termed StrEAMM (Structural Ensembles Achieved by Molecular Dynamics and Machine Learning), is the first technique capable of efficiently predicting complete structural ensembles of cyclic peptides without relying on additional molecular dynamics simulations, constituting a seven-order-of-magnitude improvement in speed while retaining the same accuracy as explicit-solvent simulations.

The StrEAMM method enables predicting the structural ensembles of cyclic peptides that adopt multiple conformations in solution.     

Reduced formation of peroxide and radical species stabilises iron-based hybrid catalysts in polymer electrolyte membrane fuel cells

The incorporation of Pt into an iron-nitrogen-carbon(Fe NC)catalyst for the oxygen reduction reaction(ORR)was recently shown to enhance catalyst stability without Pt directly contributing to the ORR activity.However,the mechanistic origin of this stabilisation remained obscure.It is established herein with rotating ring disc experiments that the side product,H₂O₂,which is known to damage FeNC catalysts,is suppressed by the presence of Pt.The formation of reactive oxygen species is additionally inhibited,independent of intrinsic H₂O₂ formation,as determined by electron paramagnetic resonance.Transmission electron microscopy identifies an oxidised Fe-rich layer covering the Pt particles,thus explaining the inactivity of the latter towards the ORR.These insights develop understanding of Fe NC degradation mechanisms during ORR catalysis,and crucially establish the required properties of a precious metal free protective catalyst to improve Fe NC stability in acidic media.