Modelling the Diffusion Kinetics of Bioactive Compounds Released from Protein-polysaccharides Composites
Creators: name: Sidhu, Manwinder
Publisher: name: RMIT University
Year: 2025
Subjects: classificationCode: 300602
subject: Food chemistry and food sensory science

description: The rheology of phase-separated biopolymers is characterised by distinct viscoelastic properties, with one biopolymer typically forming a continuous phase and the other a dispersed phase. This structural arrangement significantly impacts diffusion, as the rigidity and network density of the continuous phase influence the rate and extent of bioactive compound migration. By modifying these rheological properties, the release profiles of encapsulated or entrapped molecules can be finely tuned, making rheology a crucial factor in designing controlled diffusion systems within biopolymer matrices. In this study, phase separation in biopolymer gels was investigated using blending law modelling, with a focus on the diffusion behaviour of vitamin B6 as a bioactive compound within the matrix. While previous studies primarily utilised blending law modelling to predict solvent partitioning and phase behaviour in mixed biopolymer systems, our research extends this approach as an alternative to traditional diffusion models. By examining how matrix structural properties, such as elasticity and topology, influence diffusion, we provide insights into how biopolymer interactions affect the release kinetics of bioactive compounds. This approach emphasises the critical role of matrix architecture in functional food applications, allowing for controlled release and improved bioavailability of encapsulated compounds. In the first experimental chapter of this thesis, gelatin–agarose phase-separated composites were utilised to investigate pyridoxine diffusion using blending law modelling. The phase behaviour of these biopolymer composites was thoroughly analysed, employing a rheometer to characterise the rheological properties and confirm the lack of interactions between the polymers, affirming phase separation. Structural properties were further examined using Fourier-transform infrared (FTIR) spectroscopy, wide-angle X-ray diffraction (WXRD), confocal laser scanning microscopy (CLSM), and polymer blending laws. These combined microscopic, spectroscopic, and thermomechanical observations confirmed that gelatin formed a continuous phase, while agarose existed as a dispersed phase within the composite. Additionally, increasing agarose concentration resulted in heightened rigidity of the dispersed phase. Effective phase concentrations of each polymer were calculated using blending law modelling, allowing for the determination of the diffusion coefficient for each phase and, subsequently, an overall diffusion coefficient for the composite based on the phase behaviour. Furthermore, modern diffusion modelling techniques for cylindrical gel geometries were applied to obtain experimental diffusion coefficients from the composites. The close agreement between the diffusion coefficients derived from blending law modelling and modern diffusion modelling highlights the suitability of the blending law model as a reliable alternative for estimating diffusion behaviour in biopolymer composites.In the second chapter of this thesis, the study conducted a comprehensive exploration of the versatility of the blending law model to assess its applicability in estimating diffusion coefficients in various biopolymer systems. Concentrations of agarose and gelatin were systematically adjusted to establish a phase-inverted bicontinuous structure within the composites. This adjustment resulted in a significant alteration in phase behaviour, wherein both gelatin and agarose exhibited characteristics typical of a continuous phase. Consequently, agarose emerged as the continuous phase, while gelatin was relegated to the dispersed phase. This phase inversion phenomenon was characterised as operating under isostress conditions. To accurately determine the diffusion coefficients for the phase-inverted bicontinuous composites, relevant theoretical blending law models were employed and compared against coefficients derived from conventional diffusion modelling techniques. This dual methodology facilitated rigorous cross?validation of the calculated diffusion values, offering valuable insights into the accuracy of blending law modelling in systems with complex phase topologies. The structural properties of the phase-inverted bicontinuous composites were analysed extensively through a combination of Fourier-transform infrared (FTIR) spectroscopy, wide-angle X-ray diffraction (WXRD), confocal laser scanning microscopy (CLSM), and dynamic oscillatory testing. These integrated microscopic, spectroscopic, and thermomechanical analyses confirmed that gelatin and agarose formed a bicontinuous network, with agarose primarily constituting the continuous phase and gelatin occupying the dispersed phase. The phase inversion was distinctly observed in the exhibited isostress behaviour. The data obtained not only demonstrated the effectiveness of blending law modelling in calculating diffusion coefficients for complex biopolymer systems but also underscored its potential as a robust alternative to traditional diffusion modelling. This is particularly relevant for applications that necessitate precise diffusion control in the fields of food science and biopolymer-based functional materials. modelling in calculating diffusion coefficients for complex biopolymer systems but also underscored its potential as a robust alternative to traditional diffusion modelling. To further validate the developed blending law modelling, a composite system of whey protein and agarose was prepared, with whey protein forming the continuous phase and agarose as the dispersed phase. Gelation of the whey protein was achieved through controlled heat treatment at a neutral pH, allowing for the formation of a stable network that aligns with the phase-separated structure required for blending law application. This composite system demonstrated that blending law modelling could accurately predict the diffusion coefficient within a new biopolymer matrix, further supporting its novelty as an approach for calculating diffusion coefficients across diverse biopolymer systems. The results reinforce the blending law model's potential as a versatile, alternative method to traditional diffusion modelling for complex food and functional material applications.To extend the validation of blending law modelling, composites of bovine serum albumin (BSA) and agarose were prepared, where BSA served as the continuous phase and agarose formed the dispersed phase. This configuration confirmed that blending law modelling could effectively predict diffusion coefficients within a diverse range of biopolymer matrices. Throughout this research, blending law models were systematically employed as an alternative to diffusion modelling, offering new insight into diffusion coefficient estimation for phase-separated composites. To challenge the model's limitations, a second BSA–agarose composite was created, deliberately structured to fall outside the traditional scope of blending law applicability. In this configuration, gelation was restricted to the agarose phase, while BSA remained in a non-gelled state, entrapped as discrete particles within the continuous agarose matrix. Structural analysis using Fourier-transform infrared spectroscopy (FTIR), wide-angle X-ray diffraction (WAXD), confocal laser scanning microscopy (CLSM), and dynamic oscillatory shear testing confirmed the distinct phase structure, with a continuous agarose phase and dispersed BSA particles. The Lewis–Nielsen equation was applied to assess the thermomechanical properties and diffusion coefficients within this composite, offering an alternative calculation method. Comparison of diffusion coefficients derived from the Lewis–Nielsen approach with traditional diffusion modelling showed a close correlation, highlighting its potential as an innovative method for evaluating diffusion in systems with non-traditional phase structures. These findings indicate that the Lewis–Nielsen model can serve as a novel alternative, expanding the scope of diffusion coefficient estimation in complex biopolymer matrices.