Detailed Molecular Structure Modeling – A Path Forward to Designing Application Properties of ldPE

Summary: This paper describes a step on the ambitious aim to “design” application properties of ldPE by first simulating the detailed molecular structure of a high‐pressure tubular reactor product. The reactor of a certain configuration produces under well‐defined operating conditions. The next step is to correlate the structure with the application properties. Finally, the sequence will be reversed in order to deduce the operating conditions, which lead to the desired product quality. Two‐dimensional distributions, in molecular weight and branching frequency, as well a two compartment models with a core and a shell stream were simulated and compared with experimental results. Therefore, CFD simulations were carried out to discretize the reaction medium. Samples were taken from both pilot and commercial plants. The TREF‐SEC analytical method was successfully applied in order to measure the microscopic structure of the material. The tremendous numerical problems were solved with the help of the software PREDICI .

Detailed MWD for a pilot scale reactor product.     

Application of the percolation model to gelation of an epoxy resin

The percolation model has been applied to the study of gelation of the TGDDM-DDS system (tetraglycidyldiaminodiphenylmethane–diaminodiphenylsulfone) at a mass concentration of 100–30. For each temperature the experimental viscosity curves are satisfactorily described by a percolation law. Using the degree of chemical reactions, X, as a variable, a very clear change in the reaction mechanism with temperature can be shown. Then a rate of advancement of effective reactions, Y, is defined. This value only takes intermolecular-type reactions into account, and is probably the only variable on which viscosity depends in a percolation law: η = B(1 ? Y/Y_c)^?p. We obtain Y_c= 0.45 and p= 2.0. Comparing X_c and Y_c at the gel point, we obtain information on the proportion of intramolecular reactions with temperature. It is also demonstrated that the critical percolation threshold agrees closely with the gel point determined experimentally on log G″= f(t) curves.     

Well-defined polymer precursors synthesized by RAFT polymerization of N,N-dimethylacrylamide/N-acryloxysuccinimide: random and block copolymers

N,N-dimethylacrylamide (DMA) and N-acryloxysuccinimide (NAS) were copolymerized by the reversible addition–fragmentation chain transfer (RAFT) polymerization technique, to obtain random and block copolymer precursors onto which different side-groups may be statistically grafted via the reactive NAS units. These reactive copolymers have interesting applications in various fields such as coatings and paints, water purification and biology. Random poly(DMA-co-NAS) copolymer chains were synthesized with a 75/25 molar ratio, high conversion, an excellent molecular weight (MW) control from 5000 to 130 000 g mol⁻¹, and low polydispersity index (M_w/M_n<1.1). Poly(DMA-b-NAS) block copolymers were synthesized by a two step method, in which a poly(DMA) homopolymer was prepared first and then used as macro-chain transfer agent to polymerize NAS. For example, a poly(DMA-b-NAS) sample was obtained with an average molecular weight of 44 300/7400 g mol⁻¹ corresponding to 447 DMA and 44 NAS units. Such block copolymers had not yet been synthesized by any controlled polymerization technique. They can be used to prepare polymers with exactly the same backbone and an increasing number of different side groups (e.g. hydrophobic, ionic or fluorescent).     

Effect of Step Size in Incremental Loading Tests

Using the crack-growth model, the deviation of real fracture stress from the stressing level measured by stepwise incremental loading with three starting modes is calculated. For both static and dynamic fatigue, the relative error depends only on the relative increment size and the crack-growth parameter, n. The usefulness of stepwise incremental loading for strength testing can be confirmed.     

Automated bank cheque verification using image processing and deep learning methods

Multimedia Tools and Applications - Automated bank cheque verification using image processing is an attempt to complement the present cheque truncation system, as well as to provide an alternate...     

Surface Modification of Ready-to-Use Hollow Fiber Ultrafiltration Modules for Oil/Water Separation

Reusing wastewater from oil-related industries is becoming increasingly important, especially in water-stressed oil-producing countries. Before oily wastewater can be discharged or reused, it must be properly treated, e.g., by membrane-based processes like ultrafiltration. A major issue of the applied membranes is their high fouling propensity. This paper reports on mitigating fouling inside ready-to-use ultrafiltration hollow-fiber modules used in a polishing step in oil/water separation. For this purpose, in-situ polyzwitterionic hydrogel coating was applied. The membrane performance was tested with oil nano-emulsions using a mini-plant system. The main factors influencing fouling were systematically investigated using statistical design of experiments.     

Properties of Induction Plasma Sprayed Iron Based Nanostructured Alloy Coatings for Metal Based Thermal Barrier Coatings

Metal-based thermal barrier coatings (MBTBCs) have been produced using high frequency induction plasma spraying (IPS) of iron-based nanostructured alloy powders. The study of MBTBCs has been initiated to challenge issues associated with current TBC materials such as difficult prediction of their “in-service” lifetime. Reliability of TBCs is an important aspect besides the economical consideration. Therefore, the study of MBTBCs, which should posses higher toughness than the current TBC materials, has been initiated to challenge the mechanical problems of ceramic-based TBCs (CBTBCs) to create a new generation of TBCs. The thermal diffusivity (TD) (α) properties of the MBTBCs were measured using a laser flash method, and density (ρ) and specific heat (C _p) of the MBTBCs were also measured for their thermal conductivity (k) calculation (k = αρ C _p).     

Task-dependent evolution of modularity in neural networks

There exist many ideas and assumptions about the development and meaning of modularity in biological and technical neural systems. We empirically study the evolution of connectionist models in the context of modular problems. For this purpose, we define quantitative measures for the degree of modularity and monitor them during evolutionary processes under different constraints. It turns out that the modularity of the problem is reflected by the architecture of adapted systems, although learning can counterbalance some imperfection of the architecture. The demand for fast learning systems increases the selective pressure towards modularity.