Lignin nanoparticles as Pickering stabilizers: emulsion engineering through physicochemical design and meta-analysis

Abstract

This review systematically examines the principal physicochemical parameters that govern the formation, stability, and properties of Pickering emulsions stabilized by lignin nanoparticles (LNPs). We consider the role of particle size, charge and concentration, oil volume fraction, as well as emulsification variables (pH and shearing method). We demonstrate the broad applicability of fundamental physical chemistry principles in explaining the long-term stability of LNP-stabilized Pickering emulsions. LNPs with diameters of 25–50 nm, at concentrations between 0.2 and 2 wt%, generally yield emulsions stable for over six months. This suggests that rapid interfacial coverage by smaller particles, facilitated by high-energy emulsification, is critical for preventing initial coalescence. Such emulsions are generally more stable at acidic to neutral pH (pH 3–7). In addition, more negative LNP zeta potentials (up to −64 mV) correlate with enhanced colloidal stability due to the electrostatic repulsion between oil droplets. Furthermore, LNP modification such as acetylation and polymer grafting can significantly enhance emulsion stability by balancing surface wettability (hydrophilicity/hydrophobicity) and interfacial activity. A meta-analysis and support vector regressor with Bayesian optimization and eXplainable artificial intelligence (AI) analysis confirmed high-energy emulsification (ultrasonication, high-shear mixing), pH, and packing parameter (LNP<inf>size</inf>/LNP<inf>conc</inf> ratio) as the main features that can influence the formulation of emulsions and lead to smaller droplets and larger lifetimes. Finally, we propose heuristics to tailor LNP-stabilized Pickering emulsions that require stability and functionality, including those used in agriculture and crop protection, food, nutraceuticals, stimuli-responsive and energy systems, as well as coatings.

Authors wish to acknowledge the financial support of the Spanish Ministry of Science, Innovation and Universities to the project NextPack (PID2021- 124766OA-I00). Marc Delgado-Aguilar and Quim Tarrés are Serra Húnter Fellows. B.L.T. acknowledges funding from Khalifa University of Science and Technology (KUST) FSU-2022-021 project code: 8474000438. O.J.R. acknowledges the Canada Excellence Research Chair Program (Grant No. CERC-2018-00006) and the BC Ministry of Forests. M.A.H. acknowledges the Buckman Foundation

Open Access funding provided thanks to the CRUE-CSIC agreement with Elsevier

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