Wettability studies on drugs and drug delivery vesicles

Engineering mesoporous silica nanoparticles towards oral delivery of vancomycin

Vancomycin (Van) is a key antibiotic of choice for the treatment of systemic methicillin resistant Staphylococcus aureus (MRSA) infections. However, due to its poor membrane permeability, it is administered parenterally, adding to the cost and effort of treatment. The poor oral bioavailability of Van is mainly due to its physico-chemical properties that limit its paracellular and transcellular transport across gastrointestinal (GI) epithelium. Herein we report the development of silica nanoparticles (SNPs)-based formulations that are able to enhance the epithelial permeability of Van. We synthesized SNPs of different pore sizes (2 nm and 9 nm) and modified their surface charge and polarity by attaching different functional groups (-NH₂, -PO₃, and -CH₃). Van was loaded within these SNPs at a loading capacity in the range of ca. 18-29 wt%. The Van-loaded SNPs exhibited a controlled release behaviour when compared to un-encapsulated Van which showed rapid release due to its hydrophilic nature. Among Van-loaded SNPs, SNPs with large pores showed a prolonged release compared to SNPs with small pores while SNPs functionalised with -CH₃ groups exhibited a slowest release among the functionalised SNPs. Importantly, Van-loaded SNPs, especially the large pore SNPs with negative charge, enhanced the permeability of Van across an epithelial cell monolayer (Caco-2 cell model) by up to 6-fold, with P_app values up to 1.716 × 10^-5 cm s^-1 (vs. 0.304 × 10^-5 cm s^-1 for un-encapsulated Van) after 3 h. The enhancement was dependent on both the type of SNPs and their surface functionalisation. The permeation enhancing effect of SNPs was due to its ability to transiently open the tight junctions measured by decrease in transepithelial resistance (TEER) which was reversible after 3 h. All in all, our data highlights the potential of SNPs (especially SNPs with large pores) for oral delivery of Van or other antimicrobial peptides.

Tuneable fluidics within graphene nanogaps for water purification and energy storage

Precise control of liquid-solid interactions within sub-micrometer spaces is critical to maximize the active surface areas in porous materials, yet is challenging because of the limited liquid penetration. Here we discover an effective, dry-climate natural plant-inspired approach to guide water into sub-micrometer graphene microwells (Sub-μGWs) and to tune the transition from the hydrophobic to superhydrophilic states. Dry plasma texturing of Sub-μGWs by graphene 'nano-flaps' which adjust the tilt and density upon controlled liquid evaporation leads to controlled and stable sub-micrometer-scale surface modification and variable wettability in a wide range. This effect helps capture Au nanoparticles on the Sub-μGW surfaces as a proof-of-principle water purification platform and tune the charge-storage capacity and frequency response of Sub-μGW-based supercapacitors without altering the Sub-μGW backbones. The outcomes may be extended into diverse materials and solutions thus opening new opportunities for next-generation devices, systems and applications.

A robust algorithm for the simultaneous parameter estimation of interfacial tension and contact angle from sessile drop profiles

The pendant and sessile drop profile analysis using the finite element method (PSDA-FEM) is an algorithm which allows simultaneous determination of the interfacial tension (gamma) and contact angle (theta(c)) from sessile drop profiles. The PSDA-FEM algorithm solves the nonlinear second-order spherical coordinate form of the Young-Laplace equation. Thus, the boundary conditions at the drop apex and contact position of the drop with the substrate are required to solve for the drop profile coordinates. The boundary condition at the position where the drop contacts the substrate may be specified as a fixed contact line or fixed contact angle. This paper will focus on the fixed contact angle boundary condition for sessile drops on a substrate and how this boundary condition is used in the PSDA-FEM curve-fitting algorithm. The PSDA-FEM algorithm has been tested using simulated drop shapes with and without the addition of random error to the drop profile coordinates. The random error is varied to simulate the effect of camera resolution on the estimates of gamma and theta(c) values obtained from the curve-fitting algorithm. The error in the experimental values for gamma from sessile drops of water on acrylic and Mazola corn oil on acrylic falls within the predicted range of errors obtained for gamma values from simulated sessile drop profiles with randomized errors that are comparable in magnitude to the resolution of the experimental setup.