David Alperstein

Determination of plasticizers efficiency for nylon by molecular modeling

Polyamides are semicrystalline polymers useful in a wide range of applications in the plastics industry. Some applications require higher flexibility and workability of the polyamides, therefore, plasticizers are added to ease compounding and processing procedures and produce the desired product properties. The goal of this study was to estimate plasticizers efficiency in plasticizing Nylon 66/6 copolymer (molar ratio 80/20, respectively) using computational tools and to compare the calculated estimations to experimental results. Four plasticizers were studied: glycerin mono stearate, benzene sulfonamide, methyl 4-hydroxybenzoate (M4HB), and diethylhexyl phthalate. Plasticizers efficiency was determined by calculating cohesive energy density, solubility parameters, free volume and interaction intensities of pristine nylon, and the nylon–plasticizer blends. It was found that the efficiency of the plasticizers increases with the degree of interaction intensity between the plasticizer and polymer chains and that M4HB molecules cause the largest changes in free volume. This finding correlates with the experimental results, based on reduction of polymer glass transition temperature (Tg). The highest calculated plasticization efficiency was obtained for M4HB, for which the decrease in Tg was the most significant.

Computer-aided selection of a polymer matrix for polyaniline conductive blends

The selection of a polymer matrix for a conductive blend with polyaniline and para-toluene sulfonic acid (PANI-pTSA) was performed using molecular simulation techniques, both a fast quantitative structure–properties relationship method as a first screening phase followed by atomistic simulation. Using the atomistic simulation method, the solubility parameters and the heat of mixing of each blend were calculated to enable the determination of compatible matrices in blends with PANI-pTSA, which was validated by experimental scanning electron microscopy fractographs. Based on such calculations, polycaprolactone (PCL)/PANI-pTSA phase diagrams were estimated, showing slight miscibility of polydispersed PANI in PCL, particularly the short chains fraction, at the elevated melt processing temperature. It was suggested that this partial miscibility at the elevated temperature might lead to a conductive network morphology of PANI in PCL at room temperature, because of phase separation and precipitation of soluble PANI molecules, upon cooling and solidification of the melt.

Molecular modeling study of CO2 plasticization and sorption onto absorbable polyesters

Drug delivery systems are often made of porous polymer matrices. One method used to prepare a foamed polymer matrix is the controlled expansion of saturated polymers process in which amorphous polymer is exposed to CO2 at high pressure with a significant lowering of glass transition temperature. This plasticizing effect allows us to process temperature-sensitive polymers at relatively low temperatures. In the present study, computational tools were applied to estimate plasticizing effect of CO2 and calculate CO2- and H2O-loading capacities for three absorbable polyesters: polycaprolactone and two copolymers of (poly-d,l-lactid-co-glycolid)-co-polyethylenglycol. Plasticization caused by CO2 was estimated by solubility parameter and radial distribution function at several CO2 concentrations and by enlargement of free volume detected by mean square displacement of helium atoms, calculated after dynamic simulation. It was found that the maximal values of the solubility parameter and density can serve as a tool to predict saturation concentration. The loading capacities of the biopolymers that were preloaded with CO2 molecules were significantly higher than those of the nontreated polymers. Similar results were obtained for H2O molecules loading.

Study of interactions between single-wall carbon nanotubes and surfactant using molecular simulations

Carbon nanotubes (CNT) exhibit interesting electrical and mechanical properties. However, the insolubility of CNT in either water or organic solvents, poses serious obstacles to their future applications. The main problems are strong van der Waals attractive interactions and CNT tendency to form bundles which are very difficult to disrupt. In this study, molecular dynamics and quantum mechanics simulations were conducted to investigate the interactions between a carbonaceous nanoparticle and surfactants. It was found that a benzoic ring in the surfactant molecule improves its binding to the graphitic surface. It was shown that a structure of two stacked graphene layers causes a significant straightening of the aliphatic tail of the surfactant molecule adsorbed on the outer graphene layer. Binding energy calculations showed the effect of surfactant structure and CNT diameter on their interaction intensity.

Mechanisms of antiproliferative drug release from bioresorbable porous structures

Restenosis (renarrowing of the blood vessel wall) and cancer are two different pathologies that have drawn extensive research attention over the years. Antiproliferative drugs such as paclitaxel inhibit cell proliferation and are therefore effective in the treatment of cancer as well as neointimal hyperplasia, which is known to be the main cause of restenosis. Antiproliferative drugs are highly hydrophobic and their release from porous biodegradable structures is therefore advantageous. The release profiles of four antiproliferative drugs from highly porous polymeric structures were studied in this study in light of the physical properties of both the host polymers and the drug molecules, and a qualitative model was developed. The chemical structure of the polymer chain directly affects the drug release profile through water uptake in the early stages or degradation and erosion in later stages. It also affects the release profile indirectly, through the polymers 3D porous structure. However, this effect is minor. The drug volume and molecular area dominantly affect its diffusion rate from the 3D porous structure and the drugs solubility parameter compared with that of the host polymer has some effect on the drug release profile. This model can also be used to describe release mechanisms of other hydrophobic drugs from porous structures.

Simulation of DBS, DBS-COOH, and DBS-CONHNH2 as Hydrogelators

The organic gelator 1,3(R):2,4(S)-dibenzylidene-d-sorbitol (DBS) self-organizes to form a 3D network at relatively low concentrations in a variety of nonpolar organic solvents and polymer melt. DBS could be transformed into a hydrogelator by introduction of hydrophilic groups, which facilitate its self-assembly in an aqueous medium. In this work, we have investigated the hydrogelators DBS-COOH and DBS-CONHNH2 and the organogelator DBS by molecular modeling. We have used quantum mechanics (QM) to elucidate the preferred geometry of one molecule and a dimer of each of the gelators and molecular dynamics (MD) to simulate the pure gelators and their mixtures with water. The results of the simulation indicate that the interaction between DBS-COOH molecules is the strongest of the three and its water compatibility is the highest. Therefore, DBS-COOH seems to be a better hydrogelator than DBS-CONHNH2 and DBS. Intermolecular H-bonding interactions are formed between DBS, DBS-COOH, and DBS-CONHNH2 molecules as pure substances, and they dramatically decrease in the presence of water. In contrast, the intramolecular interactions increase in water. This result indicates that in aqueous environment the molecular structure tends to be more rigid and fixed in the preferred conformation. The most significant intramolecular interaction is formed between O3 acetal and H-O6 groups. Due to the H-bonds, DBS, DBS-COOH, and DBS-CONHNH2 molecules form a rigid structure similar to that of liquid crystal forming molecules, which might explain their tendency to create nanofibrils. It was found that the aromatic rings do not contribute significantly to the inter- and intramolecular interactions. Their main role is probably to stiffen the molecular structure.

Computer simulation of curing and toughening of epoxy systems

The crosslinking and toughening process of diglycidyl ether of bisphenol A (DGEBA) resin was simulated by various computational techniques, using a commercial polymer modeling software package. First, curing of DGEBA resin with three different curing agents was simulated using a Monte Carlo simulation technique. Results calculated for crosslinking conversion of the formed network showed that deviation from an ideal network due to loops and dangling chains increased with excess amounts of the curing agent and that the formed network is close to the ideal when stoichiometric concentrations are used. The maximal calculated modulus was an indication of the optimal curing agent concentration. The glassy modulus and T g for the simulated systems were calculated using the group contribution method and semiempirical correlations. Second, the simulation results of multicomponent epoxy systems, comprising two curing agents, a reactive diluent and DGEBA resin, indicate that there is no difference in network quality compared with bicomponent epoxy systems, comprising DGEBA and a single curing agent. The simulation results exemplified the ability to choose optimal components concentration in a complicated multicomponent epoxy system. Third, the toughening process of amino-terminated butadiene acrylonitrile (ATBN) and carboxyl-terminated butadiene acrylonitrile (CTBN) in DGEBA resin was analyzed using the solubility parameter approach. This approach could explain the role of the rubber acrylonitrile group in epoxy/rubber blends. The interaction parameters of both systems (ATBN and CTBN) and their phase diagrams were estimated using modified Flory-Huggins theory. It was shown that this technique leads to good estimations of the optimal rubber concentration, leading to optimal mechanical properties.