Drug loading and release studies for milled silk particles of different sizes

Milled silk particles with volume median particle size (d(0.5)) of 7 μm and 281 nm as well as silk snippets were used for loading of model drugs Orange G, Azophloxine, Rhodamine B, and Crystal Violet. Loading and release of these chemicals depended on the size of silk particles, pH, and the structure and properties of model drugs. Both types of silk particles reached equilibrium loading in less than 10 min due to high surface area whereas silk fibres needed more than 2-3 days to reach equilibrium, depending on the drug type. The uptake rate in fibres could be improved by increasing temperature. Both fibres and particles could slowly release the drugs over many days at 37 °C without a significant initial burst. As particle size decreased, the amount of model drug release also decreased. The release of drugs by the silk fibres was quicker than the silk particles.

Evaluation of polyvinyl alcohol composite membranes containing collagen and bone particles

Composite biomaterials provide alternative materials that improve on the properties of the individual components and can be used to replace or restore damaged or diseased tissues. Typically, a composite biomaterial consists of a matrix, often a polymer, with one or more fillers that can be made up of particles, sheets or fibres. The polymer matrix can be chosen from a wide range of compositions and can be fabricated easily and rapidly into complex shapes and structures. In the present study we have examined three size fractions of collagen-containing particles embedded at up to 60% w/w in a poly(vinyl alcohol) (PVA) matrix. The particles used were bone particles, which are a mineral-collagen composite and demineralised bone, which gives naturally cross-linked collagen particles. SEM showed well dispersed particles in the PVA matrix for all concentrations and sizes of particles, with FTIR suggesting collagen to PVA hydrogen bonding. Tg of membranes shifted to a slightly lower temperature with increasing collagen content, along with a minor amount of melting point depression. The modulus and tensile strength of membranes were improved with the addition of both particles up to 10 wt%, and were clearly strengthened by the addition, although this effect decreased with higher collagen loadings. Elongation at break decreased with collagen content. Cell adhesion to the membranes was observed associated with the collagen particles, indicating a lack of cytotoxicity.

Control of partial coalescence of self-assembled metal nano-particles across lyotropic liquid crystals templates towards long range meso-porous metal frameworks design

The formation of purely metallic meso-porous metal thin films by partial interface coalescence of self-assembled metal nano-particles across aqueous solutions of Pluronics triblock lyotropic liquid crystals is demonstrated for the first time. Small angle X-ray scattering was used to study the influence of the thin film composition and processing conditions on the ordered structures. The structural characteristics of the meso-structures formed demonstrated to primarily rely on the lyotropic liquid crystal properties while the nature of the metal nano-particles used as well as the their diameters were found to affect the ordered structure formation. The impact of the annealing temperature on the nano-particle coalescence and efficiency at removing the templating lyotropic liquid crystals was also analysed. It is demonstrated that the lyotropic liquid crystal is rendered slightly less thermally stable, upon mixing with metal nano-particles and that low annealing temperatures are sufficient to form purely metallic frameworks with average pore size distributions smaller than 500 nm and porosity around 45% with potential application in sensing, catalysis, nanoscale heat exchange, and molecular separation.

Parametric investigation of batch adsorption of proteins onto polymeric particles

Background: Effective bimolecular adsorption of proteins onto solid matrices is characterized by in-depth understanding of the biophysical features essential to optimize the adsorption performance. Results: The adsorption of bovine serum albumin (BSA) onto anion-exchange Q-sepharose solid particulate support was investigated in batch adsorption experiments. Adsorption kinetics and isotherms were developed as a function of key industrially relevant parameters such as polymer loading, stirring speed, buffer pH, protein concentration and the state of protein dispersion (solid/aqueous) in order to optimize binding performance and adsorption capacity. Experimental results showed that the first order rate constant is higher at higher stirring speed, higher polymer loading, and under alkaline conditions, with a corresponding increase in equilibrium adsorption capacity. Increasing the stirring speed and using aqueous dispersion protein system increased the adsorption rate, but the maximum protein adsorption was unaffected. Regardless of the stirring speed, the adsorption capacity of the polymer was 2.8 mg/ml. However, doubling the polymer loading increased the adsorption capacity to 9.4 mg/ml. Conclusions: The result demonstrates that there exists a minimum amount of polymer loading required to achieve maximum protein adsorption capacity under specific process conditions.

Effect of B4C, TiB2 and ZrSiO4 ceramic particles on mechanical properties of aluminium matrix composites: Experimental investigation and predictive modelling

This paper focuses on the influence of processing temperature and inclusion of micron-sized B4C, TiB2 and ZrSiO4 on the mechanical performance of aluminium matrix composites fabricated through stir casting. The ceramic/aluminium composite could withstand greater external loads, due to interfacial ceramic/aluminium bonding effect on the movement of grain and twin boundaries. Based on experimental results, the tensile strength and hardness of ceramic reinforced composite are significantly increased. The maximum improvement is achieved through adding ZrSiO4 and TiB2, which has led to 52% and 125% increase in tensile strength and hardness, respectively. To predict the effect of incorporating ceramic reinforcements on the mechanical properties of composites, experimental data of mechanical tests are used to create 3 models named Levenberg-Marquardt Algorithm (LMA) neural networks. The results show that the LMA- neural networks models have a high level of accuracy in the prediction of mechanical properties for ceramic reinforced-aluminium matrix composites.