A β-NMR study of the depth, temperature, and molecular-weight dependence of secondary dynamics in polystyrene: Entropy–enthalpy compensation and dynamic gradients near the free surface

Response of Elementary Structural Transitions in Glassy Atactic Polystyrene to Temperature and Deformation

The effects of temperature, pressure, and imposed strain on the structural transition pathways of glassy atactic polystyrene (aPS) are studied for a wide range of conditions. By employing an atomistic description of the system, we systematically explore its free energy landscape, emphasizing connections between local free energy minima. A triplet of two minima connected to each other via a first-order saddle point provides the full description of each elementary structural relaxation event. The basis of the analysis is the potential energy landscape (PEL), where efficient methods for finding saddle points and exploring transition pathways have been developed. We then translate the stationary points of the PEL to stationary points of the proper free energy landscape that obeys the macroscopically imposed constraints (either stress- or strain-controlled). By changing the temperature under isobaric conditions (i.e., Gibbs energy landscape), we probe the temperature dependence of the transition rates of the subglass relaxations of aPS, thus obtaining their activation energies by fitting to the Arrhenius equation. The imposition of different strain levels under isothermic conditions allows us to estimate the apparent activation volume of every elementary transition. Our findings are in good agreement with experimental observations for the same system, indicating that both length- and time-scales of the structural transitions of glassy aPS can be obtained by proper free energy minimization of atomistically detailed configurations.

Magnesium(II)‐ATP Complexes in 1‐Ethyl‐3‐Methylimidazolium Acetate Solutions Characterized by 31 Mg β‐Radiation‐Detected NMR Spectroscopy

The complexation of Mg^II with adenosine 5′‐triphosphate (ATP) is omnipresent in biochemical energy conversion, but is difficult to interrogate directly. Here we use the spin‐1/2 β‐emitter ³¹Mg to study Mg^II‐ATP complexation in 1‐ethyl‐3‐methylimidazolium acetate (EMIM‐Ac) solutions using β‐radiation‐detected nuclear magnetic resonance (β‐NMR). We demonstrate that (nuclear) spin‐polarized ³¹Mg, following ion‐implantation from an accelerator beamline into EMIM‐Ac, binds to ATP within its radioactive lifetime before depolarizing. The evolution of the spectra with solute concentration indicates that the implanted ³¹Mg initially bind to the solvent acetate anions, whereafter they undergo dynamic exchange and form either a mono‐ (³¹Mg‐ATP) or di‐nuclear (³¹MgMg‐ATP) complex. The chemical shift of ³¹Mg‐ATP is observed up‐field of ³¹MgMg‐ATP, in accord with quantum chemical calculations. These observations constitute a crucial advance towards using β‐NMR to probe chemistry and biochemistry in solution.

The Analysis of WJ Distribution as an Extended Gaussian Function: Case Study

The double exponential WJ distribution has been shown to competently describe extreme events and critical phenomena, while the Gaussian function has celebrated rich applications in many other fields. Here we present the analysis that the WJ distribution may be properly treated as an extended Gaussian function. Based on the Taylor expansion, we propose three methods to formulate the WJ distribution in the form of Gaussian functions, with Method I and Method III being accurate and self-consistent, and elaborate the relationship among the parameters of the functions. Moreover, we derive the parameter scaling formula of the WJ distribution to express a general Gaussian function, with the work illustrated by a classical case of extreme events and critical phenomena and application to topical medical image processing to prove the effectiveness of the WJ distribution rather than the Gaussian function. Our results sturdily advocate that the WJ distribution can elegantly represent a Gaussian function of arbitrary parameters, whereas the latter usually is not able to satisfactorily describe the former except for specific parameter sets. Thus, it is conclusive that the WJ distribution offers applicability in extreme events and critical phenomena as well as processes describable by the Gaussian function, namely, implying plausibly a unifying approach to the pertinent data processing of those quite distinct areas and establishing a link between relevant extreme value theories and Gaussian processes.