We combine 1 H, 7 Li, and 19 F NMR methods to selectively investigate polymer, cation, and anion dynamics in polymer electrolytes on various length and time scales and over broad temperature ranges. By mixing unentangled poly(propylene glycol) (PPG) with lithium perchlorate (LiClO 4 ) or lithium bis-(trifluoromethylsulfonyl)imide (LiTFSI), fully disordered samples are obtained at all studied concentrations. In static field gradient diffusometry, we observe that the longrange motion of all components slows down when the salt concentration is increased, but the effect is more prominent for PPG−LiClO 4 than PPG−LiTFSI electrolytes and, in general, differs for the respective components. The self-diffusion coefficients D of polymer and ions have essentially temperature-independent ratios, where cations are less mobile than anions and do not show Arrhenius temperature dependence. To ascertain short-range motions in broad dynamic ranges, spin−lattice relaxation studies, including field-cycling relaxometry, are combined with stimulated-echo experiments. We show that rate and heterogeneity of local lithium and polymer dynamics depend on the salt content. For intermediate salt concentrations, the segmental motion even exhibits bimodal distributions of correlation times τ, implying structures with salt-rich and salt-depleted regions. Relating diffusion coefficients D and correlation times τ, we find that the lithium ion transport is strongly coupled to polymer segmental motion even in polymer electrolytes with micro-heterogeneous salt distributions. Finally, field-cycling susceptibilities reveal that Rouse dynamics is important not only for the reorganization of polymer chains but also for the transport of lithium ions.

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Molecular dynamics (MD) simulations are a powerful tool for detailed studies of altered properties of liquids in confinement, in particular, of changed structures and dynamics. They allow, on one hand, for perfect control and systematic variation of the geometries and interactions inherent in confinement situations and, on the other hand, for type-selective and position-resolved analyses of a huge variety of structural and dynamical parameters. Here, we review MD simulation studies on various types of liquids and confinements. The main focus is confined aqueous systems, but also ionic liquids and polymer and silica melts are discussed. Results for confinements featuring different interactions, sizes, shapes, and rigidity will be presented. Special attention will be given to situations in which the confined liquid and the confining matrix consist of the same type of particles and, hence, disparate liquid–matrix interactions are absent. Findings for the magnitude and the range of wall effects on molecular positions and orientations and on molecular dynamics, including vibrational motion and structural relaxation, are reviewed. Moreover, their dependence on the parameters of the confinement and their relevance to theoretical approaches to the glass transition are addressed.

Experimental studies of the glassy slowdown in molecular liquids indicate that the high-temperature activation energy E∞ of glass-forming liquids is directly related to their glass transition temperature Tg. To further investigate such a possible relation between high- and low-temperature dynamics in glass-forming liquids, we analyze the glassy dynamics of binary mixtures using molecular dynamics simulations. We consider a binary mixture of charged Lennard-Jones particles and vary the partial charges of the particles and, thus, the high-temperature activation energy and the glass transition temperature of the system. Based on previous results, we introduce a phenomenological model describing relaxation times over the whole temperature regime from high temperatures to temperatures well inside the supercooled regime. By investigating the dynamics of both particle species on molecular and diffusive length scales along isochoric and isobaric pathways, we find a quadratic charge dependence of both E∞ and Tg, resulting in an approximately constant ratio of both quantities independent of the underlying observable, the thermodynamic ensemble, and the particle species, and this result is robust against the actual definition of Tg. This generic relation between the activation energy and the glass transition temperature indicates that high-temperature dynamics and the glassy slowdown are related phenomena, and the knowledge of E∞ may allow us to approximately predict Tg.

Lowering the limit of detection in chemical or biochemical analysis is key to extending the application scope of sensing schemes. Usually, this is related to an increased instrumentation effort, which in turn precludes many commercial applications. We demonstrate that the signal-to-noise ratio of isotachophoresis-based microfluidic sensing schemes can be substantially increased merely by postprocessing of recorded signals. This becomes possible by exploiting knowledge about the physics of the underlying measurement process. The implementation of our method is based on microfluidic isotachophoresis and fluorescence detection, for which we take advantage of the physics of electrophoretic sample transport and the structure of noise in the imaging process. We demonstrate that by processing only 200 images, the detectable concentration, compared to the detection from a single image, is already lowered by 2 orders of magnitude without any additional instrumentation effort. Furthermore, we show that the signal-to-noise ratio is proportional to the square root of the number of fluorescence images, which leaves room for further lowering of the detection limit. In the future, our results could be relevant for various applications where the detection of minute sample amounts plays a role.

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