Gels

Background: Spreadability is a critical performance attribute for semisolid formulations, influencing patient compliance, dose uniformity, and product acceptability. Despite its importance, there is no standardized method for its assessment across pharmaceutical and cosmetic applications. Objective: This review uniquely integrates systematic literature mapping with an experimental comparison of five spreadability assessment techniques, providing evidence-based recommendations for harmonizing protocols and improving reproducibility in semisolid formulation testing. Methods: A systematic search of PubMed, Scopus, and Web of Science identified 211 records, of which 14 studies met the inclusion criteria. Techniques reviewed included parallel-plate, slip-and-drag, rheometry (flow curve and amplitude sweep), texture analysis, and frictiometry. An experimental comparison was conducted on ten commercial formulations using all five techniques to assess inter-method variability and formulation-dependent behavior. Results: Texture analyzer and amplitude sweep rheometry emerged as the most reproducible and predictive methods, showing strong correlation (r = 0.74) in both literature and experimental data. Flow curve yield stress negatively correlated with parallel-plate spreadability (r = –0.796). Frictiometry results varied significantly with formulation type, particularly for ointments. Creams consistently ranked highest in spreadability across methods. Conclusion: No single method universally captures spreadability. Amplitude sweep rheometry correlated well with texture analysis, while flow curve values were more variable. Parallel-plate testing showed strong agreement with rheological and tribological methods, though texture analysis diverged, capturing distinct mechanical attributes. A tiered approach integrating parallel-plate, amplitude sweep, and frictiometry is recommended, with flow curve retained for regulatory compliance. Texture analysis provides valuable orthogonal information. Standardization of parallel-plate protocols is needed to establish unified spreadability indices.

This study investigates the impact of ultrasonic treatment on the deagglomeration of aggregates of single-walled carbon nanotubes (SWCNTs) and reduced graphene oxide (rGO). The aim of the research is to enhance the electrical conductivity of a biopolymer hydrogel designed for coating metallic neurostimulation electrodes. Biocompatible coating materials are essential for the safe long-term function of implants within the body, enabling the transmission of nerve impulses to external devices for signal conversion and neurostimulation. Dynamic light scattering (DLS) was employed to monitor the dispersion state, in conjunction with measurements of specific electrical conductivity. The mass loss and swelling capacity were evaluated over an 80-day period to account for the effects of degradation during in vitro studies. Samples of flexible–elastic hydrogels for electrodes with complex geometry were formed by the photopolymerization of a photopolymerizable medium, similar to a photoresist. Analysis of the dependence of temperature and normalized optical transmittance on the duration of laser photopolymerization made it possible to determine the optimal polymerization temperature for the photopolymerizable medium as −28 °C. This temperature regime ensures maximum reproducibility of hydrogel formation and eliminates the presence of unpolymerized areas. The article presents a biopolymer hydrogel with SWCNTs and rGO nanoparticles in a 1:1 ratio. It was found that sufficient specific electrical conductivity is achieved using SWCNTs with a characteristic hydrodynamic radius of R = 490 nm and rGO with R = 210 nm (sample Col/BSA/CS/Eosin Y/SWCNTs (490 nm)/rGO 4). The photopolymerized hydrogel 4 demonstrated sufficient biocompatibility, exceeding the control sample by 16%. According to the results of in vitro studies over 80 days, this sample exhibited moderate degradation of 45% while retaining its swelling ability. The swelling degree decreased by 50% compared to the initial value of 170%. The presented hydrogel 4 is a promising coating material for implantable metallic neurostimulation electrodes, enhancing their stability in the physiological environment.

This study investigated the influence of coconut oil concentration (0–2%) on the nonlinear rheological and thermal behavior of soy protein concentrate (SPC) mixtures and integrated these data into computational fluid dynamics (CFD) models to predict flow behavior during high-moisture extrusion. Temperature sweep tests revealed that increasing oil content elevated the onset and peak gelation temperatures from 64.13 to 70.21 °C and 70.29 to 76.08 °C, respectively, while decreasing gelation enthalpy from 4.05 J/g to 2.81 J/g. Large-amplitude oscillatory shear (LAOS) analysis showed a shift from strain-stiffening (e₃/e₁ > 0.15) behavior to strain-thinning (e₃/e₁ < 0.05) behavior with increasing oil, accompanied by enhanced shear-thinning behavior (v₃/v₁ < 0). Integrating these nonlinear parameters into the CFD simulations enhanced model accuracy relative to the SAOS-based approach, resulting in lower RMSE values (≤4.41 kPa for pressure and ≤0.11 mm/s for velocity) and enabling more realistic prediction of deformation and flow under extrusion-relevant conditions, a capability that conventional SAOS-based models could not achieve. Predicted outlet melt temperatures averaged 70.27 ± 1.55 °C, consistent with experimental results. The findings demonstrate that oil addition modulates protein network formation and flow resistance, and that nonlinear rheology-coupled CFD models enable reliable prediction of extrusion behavior. Overall, this study provides a novel rheology-driven modeling strategy for enhancing the design and optimization of oil-enriched plant-protein extrusion processes.