Understanding the pH-Directed Self-Assembly of a Four-Arm Block Copolymer

Influence of Nanoaggregation Routes on the Structure and Thermal Behavior of Multiple-Stimuli-Responsive Micelles from Block Copolymers of Oligo(ethylene glycol) Methacrylate and the Weak Acid [2-(Hydroxyimino)aldehyde]butyl Methacrylate

In this work, we compare nanoaggregation driven by pH-induced micellization (PIM) and by the standard solvent displacement (SD) method on a series of pH-, light-, and thermosensitive amphiphilic block copolymers. Specifically, we investigate poly(HIABMA)-b-poly(OEGMA) and poly(HIABMA)-b-poly(DEGMA-r-OEGMA), where HIABMA = [(hydroxyimino)aldehyde]butyl methacrylate, OEGMA = oligo(ethylene glycol)methyl ether methacrylate, and DEGMA = di(ethylene glycol)methyl ether methacrylate. The weakly acidic HIA group (pK_a ≈ 8) imparts stability to micelles at neutral pH, unlike most of the pH-responsive copolymers investigated in the literature. With SD, only some of our copolymers yield polymeric micelles (34-59 nm), and their thermoresponsivity is either poor or altogether absent. In contrast, PIM affords thermoresponsive, smaller micelles (down to 24 nm), regardless of the polymer composition. In some cases, cloud points are remarkably well defined and exhibit limited hysteresis. By combining turbidimetric, dyamic light scattering, and small-angle X-ray scattering measurements, we show that SD yields loose micelles with POEGMA segments partly involved in the formation of the hydrophobic core, whereas PIM yields more compact core-shell micelles with a well-defined PHIABMA core. We conclude that pH-based nanoaggregation provides advantages over block-selective solvation to obtain compact micelles exhibiting well-defined responses to external stimuli.

Conformational Heterogeneity and Interchain Percolation Revealed in an Amorphous Conjugated Polymer

Conjugated polymers are employed in a variety of application areas due to their bright fluorescence and strong biocompatibility. However, understanding the structure of amorphous conjugated polymers on the nanoscale is extremely challenging compared to their related crystalline phases. Using a bespoke classical force field, we study amorphous poly(9,9-di-n-octylfluorene-alt-benzothiadiazole) (F8BT) with molecular dynamics simulations to investigate the role that its nanoscale structure plays in controlling its emergent (and all-important) optical properties. Notably, we show that a giant percolating cluster exists within amorphous F8BT, which has ramifications in understanding the nature of interchain species that drive the quantum yield reduction and bathochromic shift observed in conjugated polymer-based devices and nanostructures. We also show that distinct conformations can be unravelled from within the disordered structure of amorphous F8BT using a two-stage machine learning protocol, highlighting a link between molecular conformation and ring stacking propensity. This work provides predictive understanding by which to enhance the optical properties of next-generation conjugated polymer-based devices and materials by rational, simulation-led design principles.

Fate of Photoinduced Electron Transfer Reactions with Temperature- and pH-Induced Assembly/Disassembly of Star Block Copolymer Micelles

The assembly/disassembly of star block copolymers induced by changes in temperature or pH of the medium is anticipated to have interesting implications for hosting/releasing drugs and tuning chemical reactions. This study investigates the possibility of employing the dually sensitive self-assembly of an ethylene oxide-propylene oxide star block copolymer, Tetronic T904, to influence photoinduced electron transfer (ET) reactions, on switching from the assembled state (micelle) when temperature is above the critical micelle temperature (CMT) and pH of the medium is above the pK_a of T904 to the dissociated (unimer) state when either the temperature is below the CMT or the polymer is protonated. Steady-state and time-resolved fluorescence techniques have been used to characterize the microenvironments of the reactants in T904 solutions under different temperature and pH conditions and to determine ET rate constants. Interestingly, the bimolecular ET rate constants in both assembled and disassembled states of T904 depict a bell-shaped correlation with the driving force of the reaction, in accordance with Marcus inversion behavior instead of the usual Rehm-Weller behavior seen in conventional solvents. The assembly/disassembly of T904 stimulated by temperature or pH affects the micropolarity in the reactant environment, the magnitude of ET rate constants, and the position of inversion on the exergonicity scale.

Interplay of lipid and surfactant: Impact on nanoparticle structure

Liquid lipid nanoparticles (LLN) are oil-in-water nanoemulsions of great interest in the delivery of hydrophobic drug molecules. They consist of a surfactant shell and a liquid lipid core. The small size of LLNs makes them difficult to study, yet a detailed understanding of their internal structure is vital in developing stable drug delivery vehicles (DDVs). Here, we implement machine learning techniques alongside small angle neutron scattering experiments and molecular dynamics simulations to provide critical insight into the conformations and distributions of the lipid and surfactant throughout the LLN. We simulate the assembly of a single LLN composed of the lipid, triolein (GTO), and the surfactant, Brij O10. Our work shows that the addition of surfactant is pivotal in the formation of a disordered lipid core; the even coverage of Brij O10 across the LLN shields the GTO from water and so the lipids adopt conformations that reduce crystallisation. We demonstrate the superior ability of unsupervised artificial neural networks in characterising the internal structure of DDVs, when compared to more conventional geometric methods. We have identified, clustered, classified and averaged the dominant conformations of lipid and surfactant molecules within the LLN, providing a multi-scale picture of the internal structure of LLNs.