Examination of the flow rheological and textural properties of polymer gels composed of poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone): rheological and mathematical interpretation of textural parameters.

The purpose of this study was to mathematically characterize the effects of defined experimental parameters (probe speed and the ratio of the probe diameter to the diameter of sample container) on the textural/mechanical properties of model gel systems. In addition, this study examined the applicability of dimensional analysis for the rheological interpretation of textural data in terms of shear stress and rate of shear. Aqueous gels (pH 7) were prepared containing 15% w/w poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone) (PVP) (0, 3, 6, or 9% w/w). Texture profile analysis (TPA) was performed using a Stable Micro Systems texture analyzer (model TA-XT 2; Surrey, UK) in which an analytical probe was twice compressed into each formulation to a defined depth (15 mm) and at defined rates (1, 3, 5, 8, and 10 mm s-1), allowing a delay period (15 s) between the end of the first and beginning of the second compressions. Flow rheograms were performed using a Carri-Med CSL2-100 rheometer (TA Instruments, Surrey, UK) with parallel plate geometry under controlled shearing stresses at 20.0°?±?0.1°C. All formulations exhibited pseudoplastic flow with no thixotropy. Increasing concentrations of PVP significantly increased formulation hardness, compressibility, adhesiveness, and consistency. Increased hardness, compressibility, and consistency were ascribed to enhanced polymeric entanglements, thereby increasing the resistance to deformation. Increasing probe speed increased formulation hardness in a linear manner, because of the effects of probe speed on probe displacement and surface area. The relationship between formulation hardness and probe displacement was linear and was dependent on probe speed. Furthermore, the proportionality constant (gel strength) increased as a function of PVP concentration. The relationship between formulation hardness and diameter ratio was biphasic and was statistically defined by two linear relationships relating to diameter ratios from 0 to 0.4 and from 0.4 to 0.563. The dramatically increased hardness, associated with diameter ratios in excess of 0.4, was accredited to boundary effects, that is, the effect of the container wall on product flow. Using dimensional analysis, the hardness and probe displacement in TPA were mathematically transformed into corresponding rheological parameters, namely shearing stress and rate of shear, thereby allowing the application of the power law (??=?k?n) to textural data. Importantly, the consistencies (k) of the formulations, calculated using transformed textural data, were statistically similar to those obtained using flow rheometry. In conclusion, this study has, firstly, characterized the relationships between textural data and two key instrumental parameters in TPA and, secondly, described a method by which rheological information may be derived using this technique. This will enable a greater application of TPA for the rheological characterization of pharmaceutical gels and, in addition, will enable efficient interpretation of textural data under different experimental parameters.

Effect of Mix Proportions on Rheological and Hardened Properties of Composite Cement Pastes

There is an increasing need to identify the effect of mix composition on the rheological properties of composite cement pastes using simple tests to determine the fluidity, the cohesion and other mechanical properties of grouting applications such as compressive strength. This paper reviews statistical models developed using a fractional factorial design which was carried out to model the influence of key parameters on properties affecting the performance of composite cement paste. Such responses of fluidity included mini-slump, flow time using Marsh cone and cohesion measured by Lombardi plate meter and unit weight, and compressive strength at 3 d, 7 d and 28 d. The models are valid for mixes with 0.35 to 0.42 water-to-binder ratio (W/B), 10% to 40% of pulverised fuel ash (PFA) as replacement of cement by mass, 0.02 to 0.06% of viscosity enhancer admixture (VEA), by mass of binder, and 0.3 to 1.2% of superplasticizer (SP), by mass of binder. The derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of composite cement paste are presented. Such parameters can be useful to reduce the test protocol needed for proportioning of composite cement paste. This paper attempts also to demonstrate the usefulness of the models to better understand trade-offs between parameters and compare the responses obtained from the various test methods which are highlighted. The multi parametric optimization is used in order to establish isoresponses for a desirability function of cement composite paste. Results indicate that the replacement of cement by PFA is compromising the early compressive strength and up 26%, the desirability function decreased.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

Rheological Evaluation of the Isothermal Cure Characteristics of Medical Grade Silicone Elastomers

Silicone elastomer systems have been shown to offer potential for the fabrication of medical devices and sustained release drug delivery devices comprising low molecular weight drugs and protein therapeutics. For drug delivery systems in particular, there is often no clear rationale for selection of the silicone elastomer grade, particularly in respect of optimizing the manufacturing conditions to ensure thermal stability of the active agent and short cycle times. In this study, the cure characteristics of a range of addition-cure and condensation-cure, low-consistency, implant-grade silicone elastomers, either as supplied or loaded with the model protein bovine serum albumin (BSA) and the model hydrophilic excipient glycine, were investigated using oscillatory rheology with a view to better understanding the isothermal cure characteristics. The results demonstrate the influence of elastomer type, cure temperature, protein loading, and glycine loading on isothermal cure properties. By measuring the cure time required to achieve tan delta values representative of early and late-stage cure conditions, a ratio t(1)/t(2) was defined that allowed the cure characteristics of the various systems to be compared. Sustained in vitro release of BSA from glycine-loaded silicone elastomer covered rod devices was also demonstrated over 14 days. (C) 2010 Wiley Periodicals, Inc. J Appl Polym Sci 116: 2320-2327, 2010

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

Rheological, mechanical and membrane penetration properties of novel dual drug systems for percutaneous delivery

In this study it has been demonstrated that mixtures of two solid drugs, ibuprofen and methyl nicotinate, with different but complementary pharmacological activities and which exist as a single liquid phase over a wide composition range at skin temperature, can be formulated as o/w emulsions without the use of an additional hydrophobic carrier. These novel dual drug systems provided significantly enhanced in vitro penetration rates through a model lipophilic barrier membrane compared to conventional individual formulations of each active. Thus, for ibuprofen, drug penetration flux enhancements of three- and 10-fold were observed when compared to an aqueous ibuprofen suspension and a commercial alcohol-based ibuprofen formulation, respectively. Methyl nicotinate penetration rates were shown to be similar for aqueous gels and emulsified systems. Mechanisms explaining these observations are proposed. Novel dual drug formulations of ibuprofen and methyl nicotinate, formulated within the liquid range at skin temperature, were investigated by oscillatory rheology and texture profile analysis. demonstrating the effects of drug and viscosity enhancer concentrations, and disperse phase type upon the rheological, mechanical and drug penetration properties of these systems. (C) 2000 Elsevier Science B.V. All rights reserved.

Rheological destructuring of aqueous gels composed of cellulose ethers following storage in the presence of redox agents

Despite their widespread use, there is a paucity of information concerning the effect of storage on the rheological properties of pharmaceutical gels that contain organic and inorganic additives. Therefore, this study examined the effect of storage (1 month at either 4 or 37 degrees C) on the rheological and mechanical properties of gels composed of either hydroxypropylmethylcellulose (3-5% w/w, HPMC) or hydroxyethylcellulose (3-5% w/w, HEC) and containing or devoid of dispersed organic (tetracycline hydrochloride 2% w/w) or inorganic (iron oxide 0.1% w/w) agents. The mechanical properties were measured using texture profile analysis whereas the rheological properties were analyzed using continuous shear rheometry and modeled using the Power Law model. All formulations exhibited pseudoplastic flow with minimal thixotropy. Increasing polymer concentration (3-5% w/w) significantly increased the consistency, hardness, compressibility, and adhesiveness of the formulations due to increased polymer chain entanglement. Following storage (I month at 4 and 37 degrees C) the consistency and mechanical properties of additive free HPMC gets (but not HEC gels) increased, due to the time-dependent development of polymer chain entanglements. Incorporation of tetracycline hydrochloride significantly decreased and increased the rheological and mechanical properties of HPMC and HEC gels, respectively. Conversely, the incorporation of iron oxide did not affect these properties. Following storage, the rheological and mechanical properties of HPMC and HEC formulations were markedly compromised. This effect was greater following storage at 37 than at 4 degrees C and, additionally, greater in the presence of tetracycline hydrochloride than iron oxide. It is suggested that the loss of rheological/mechanical structure was due to chain depolymerization, facilitated by the redox properties of tetracycline hydrochloride and iron oxide. These observations have direct implications for the design and formulation of gels containing an active pharmaceutical ingredient. (c) 2005 Wiley Periodicals, Inc.

Electrical conduction and rheological behaviour of composites of poly(epsilon-caprolactone) and MWCNTs

Two mechanisms of conduction were identified from temperature dependent (120 K-340 K) DC electrical resistivity measurements of composites of poly(c-caprolactone) (PCL) and multi-walled carbon nanotubes (MWCNTs). Activation of variable range hopping (VRH) occurred at lower temperatures than that for temperature fluctuation induced tunneling (TFIT). Experimental data was in good agreement with the VRH model in contrast to the TFIT model, where broadening of tunnel junctions and increasing electrical resistivity at T > T-g is a consequence of a large difference in the coefficients of thermal expansion of PCL and MWCNTs. A numerical model was developed to explain this behavior accounting for a thermal expansion effect by supposing the large increase in electrical resistivity corresponds to the larger relative deformation due to thermal expansion associated with disintegration of the conductive MWCNT network. MWCNTs had a significant nucleating effect on PCL resulting in increased PCL crystallinity and an electrically insulating layer between MWCNTs. The onset of rheological percolation at similar to 0.18 vol% MWCNTs was clearly evident as storage modulus, G' and complex viscosity, vertical bar eta*vertical bar increased by several orders of magnitude. From Cole-Cole and Van Gurp-Palmen plots, and extraction of crossover points (G(c)) from overlaying plots of G' and G '' as a function of frequency, the onset of rheological percolation at 0.18 vol% MWCNTs was confirmed, a similar MWCNT loading to that determined for electrical percolation.