Fractionation of Rice Husk into Lignin Nanoparticles, Silica Nanoparticles, Cellulose Nanocrystals, and Cellulose Nanofibers for Pickering Emulsion Applications

Pickering emulsions require solid particles to stabilize the oil−water interface, and the demand for such particle-based emulsifiers continues to grow across industrial sectors. Conventional inorganic or synthetic particles, however, often raise environmental and sustainability concerns. As a result, biomass-derived nanoparticles have emerged as promising renewable alternatives. Most existing approaches extract only isolated single components of biomass, rather than fully valorizing all major fractions, which limiting both sustainability and material efficiency. Rice husk, despite its abundance and rich chemical composition, remains underutilized for producing a complete suite of nanomaterials suited for Pickering emulsion stabilization, leaving a significant gap in integrated biorefinery strategies. In this study, we develop a comprehensive fractionation process that converts rice husk into four distinct nanomaterials lignin nanoparticles (LNPs), silica nanoparticles (SNPs), cellulose nanocrystals (CNCs), and cellulose nanofibers (CNFs) to evaluate their ability to stabilize Pickering emulsions. Using alcohol pretreatment, alkaline hydrogen peroxide treatment, acid hydrolysis, and microfluidization, each biomass fraction was transformed into particles with tailored interfacial and morphological features. The results demonstrated that CNFs from rice husk produced Pickering emulsions with the highest stability, followed by LNPs, CNCs, and SNPs. These results provide the first direct comparison of all major rice-husk-derived nanomaterials within a unified biorefinery framework, demonstrating how their intrinsic physicochemical properties dictate Pickering emulsion stability. Overall, this work establishes rice husk as a single-feedstock platform for renewable stabilizers and advances the development of sustainable, surfactant-free Pickering emulsion technologies.