Thermal response of self-organization in an amphiphilic triblock polyelectrolyte and the influence of the globular protein lysozyme

Stimuli-Responsive Self-Assembly of Poly(2-(Dimethylamino)ethyl Methacrylate-co-(oligo ethylene glycol)methacrylate) Random Copolymers and Their Modified Derivatives

In this work, the synthesis and the stimuli-responsive self-assembly behavior of novel double-hydrophilic poly(2-(dimethylamino)ethyl methacrylate-co-(oligo ethylene glycol)methacrylate) random copolymers and their chemically modified derivatives are presented. The synthesis of P(DMAEMA-co-OEGMA) copolymers of different DMAEMA mass compositions was successfully conducted through RAFT polymerization, further followed by the hydrophilic/hydrophobic quaternization with methyl iodide (CH3I), 1-iodohexane (C6H13I), and 1-iodododecane (C12H25I). The tertiary and quaternary amines are randomly arranged within the DMAEMA segment, responding thus to pH, temperature, and salt alterations in aqueous solutions. Light scattering techniques elucidated the intramolecular self-folding and intermolecular self-assembly of polymer chains of P(DMAEMA-co-OEGMA) copolymers upon exposure to different pHs and temperatures. Q(P(DMAEMA-co-OEGMA)) cationic polyelectrolytes demonstrated moderate response to pH, temperature, and ionic strength as a result of the permanent hydrophilic/hydrophobic profile, closely connected with the attached alkyl chains and the quaternization degree. Moreover, fluorescence spectroscopy measurements confirmed the internal micropolarity and the picture of the aggregate inner structure.

Small-Angle Scattering from Fractals: Differentiating between Various Types of Structures

Small-angle scattering (SAS; X-rays, neutrons, light) is being increasingly used to better understand the structure of fractal-based materials and to describe their interaction at nano- and micro-scales. To this aim, several minimalist yet specific theoretical models which exploit the fractal symmetry have been developed to extract additional information from SAS data. Although this problem can be solved exactly for many particular fractal structures, due to the intrinsic limitations of the SAS method, the inverse scattering problem, i.e., determination of the fractal structure from the intensity curve, is ill-posed. However, fractals can be divided into various classes, not necessarily disjointed, with the most common being random, deterministic, mass, surface, pore, fat and multifractals. Each class has its own imprint on the scattering intensity, and although one cannot uniquely identify the structure of a fractal based solely on SAS data, one can differentiate between various classes to which they belong. This has important practical applications in correlating their structural properties with physical ones. The article reviews SAS from several fractal models with an emphasis on describing which information can be extracted from each class, and how this can be performed experimentally. To illustrate this procedure and to validate the theoretical models, numerical simulations based on Monte Carlo methods are performed.