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The instability of the surface chemistry in transition metal oxide perovskites is the main factor hindering the long-term durability of oxygen electrodes in solid oxide electrochemical cells. The instability of surface chemistry is mainly due to the segregation of A-site dopants from the lattice to the surface. Here we report that cathodic potential can remarkably improve the stability in oxygen reduction reaction and electrochemical activity, by decomposing the near-surface region of the perovskite phase in a porous electrode made of La_1-xSr_xCo_1-xFe_xO₃mixed with Sm_0.2Ce_0.8O_1.9. Our approach combines X-ray photoelectron spectroscopy and secondary ion mass spectrometry for surface and sub-surface analysis. Formation of Ruddlesden-Popper phase is accompanied by suppression of the A-site dopant segregation, and exsolution of catalytically active Co particles onto the surface. These findings reveal the chemical and structural elements that maintain an active surface for oxygen reduction, and the cathodic potential is one way to generate these desirable chemistries.

 

Polymer nanoparticles are an emerging class of materials with potential impact in sensing, catalysis, imaging, cosmetics, and therapeutics. Here, a collection of graft polymers with conjugated polythiophene backbones were synthesized via a grafting-to approach. We functionalized polythiophene backbones with side chains of either poly(3-hexylthiophene) (P3HT), poly(ethylene oxide), or poly(methyl methacrylate) (PMMA) via copper-catalyzed azide–alkyne click chemistry. The backbones, graft polymers and a linear poly(3-hexylthiophene) were fabricated into nanoparticles through precipitation in aqueous media. We measured the absorption and emission spectra of the polymers dissolved in chloroform and as nanoparticles suspended in water. Compared to linear P3HT, all graft polymer nanoparticles exhibit higher quantum yields. Moreover, the addition of PMMA side chains increased the quantum yield by more than two orders of magnitude. This versatile approach to conjugated graft copolymer synthesis demonstrates a route for enhancing photoluminescence of conjugated polymer nanoparticles that could be beneficial for a variety of applications, such as biosensing and bioimaging. 

Alkyd resins are oil-based polymers that have been widely used for generations in the surface coating industry and beyond. Characterization of these resins is of high importance to understand the influence of its components on its behavior, compatibility with other resins, and final quality to ensure high durability. Here, NMR spectroscopy and GPC were used for characterizing differences in the chemical structure, molecular distribution, and dispersity between oil-based and fatty acid-based alkyd polymers made from sacha inchi and linseed oils. Sancha inchi (Plukentia volubilis L.) is a fruit-bearing plant native to South America and the Caribbean, and has a rich unsaturated fatty acid content. The effect of vegetable oil and polyol selection on the synthesis of alkyd resins for coating applications was analyzed. The influence of two different synthesis methods, monoglyceride and fatty acid processes, was also compared. Important structural differences were observed using NMR: one-dimensional spectra revealed the degree of unsaturated fatty acid chains along the polyester backbone, whereas, 2D NMR experiments facilitated chemical shift assignments of all signals. GPC analysis suggested that alkyd resins with homogeneous and high molecular weights can be obtained with the fatty acid process, and that resins containing pentaerythritol may have uniform chain lengths.

 

The excess free energy of mixing Δ G ex governs the phase behavior of mixtures and controls material properties. It is challenging, however, to measure Δ G ex in simulations. Previously, we developed a method that combines molecular dynamics (MD) simulations with thermodynamic integration along the path of transformation of chains to predict the Flory Huggins interaction parameter χ for polymer mixtures and block copolymers. However, this method is best applied when the constituent molecules of the blends are structurally related. To overcome this limitation, we have developed a new method to predict Δ G ex for mixtures. We perform simulations to induce phase separation within a mixture by gradually weakening the interaction between different species. To compute Δ G ex we measure the thermodynamic work required to modify the interactions and the interfacial energy between the separated phases. We validate our method by applying it first to equimolar mixtures of labeled and unlabeled Lennard-Jones (LJ) beads, and labeled and unlabeled benzene, which results in good agreement with ideal solution theory. Then we compute the excess free energy of mixing for equimolar mixtures of benzene and pyridine, using both united-atom (UA) and all-atom (AA) potentials. Our results using UA potentials predict a value for Δ G ex about four times the experimental value, whereas using AA potentials gives results consistent with experiment, highlighting the need for good potentials to faithfully represent mixture behavior.