A strategy for probing the evolution of crystallization processes by low-temperature solid-state NMR and dynamic nuclear polarization

Crystallization plays an important role in many areas, and to derive a fundamental understanding of crystallization processes, it is essential to understand the sequence of solid phases produced as a function of time. Here, we introduce a new NMR strategy for studying the time evolution of crystallization processes, in which the crystallizing system is quenched rapidly to low temperature at specific time points during crystallization. The crystallized phase present within the resultant “frozen solution” may be investigated in detail using a range of sophisticated NMR techniques. The low temperatures involved allow dynamic nuclear polarization (DNP) to be exploited to enhance the signal intensity in the solid-state NMR measurements, which is advantageous for detection and structural characterization of transient forms that are present only in small quantities. This work opens up the prospect of studying the very early stages of crystallization, at which the amount of solid phase present is intrinsically low

Insights into the crystallization and structural evolution of glycine dihydrate by in situ solid-state NMR spectroscopy

In situ solid‐state NMR spectroscopy is exploited to monitor the structural evolution of a glycine/water glass phase formed on flash cooling an aqueous solution of glycine, with a range of modern solid‐state NMR methods applied to elucidate structural properties of the solid phases present. The glycine/water glass is shown to crystallize into an intermediate phase, which then transforms to the β polymorph of glycine. Our in situ NMR results fully corroborate the identity of the intermediate crystalline phase as glycine dihydrate, which was first proposed only very recently

Divergent platforms

Models of electoral competition between two opportunistic, office-motivated parties typically predict that both parties become indistinguishable in equilibrium. I show that this strong connection between the office motivation of parties and their equilibrium choice of identical platforms depends on two—possibly false—assumptions: (1) Issue spaces are uni-dimensional and (2) Parties are unitary actors whose preferences can be represented by expected utilities. I provide an example of a two-party model in which parties offer substantially different equilibrium platforms even though no exogenous differences between parties are assumed. In this example, some voters’ preferences over the 2-dimensional issue space exhibit non-convexities and parties evaluate their actions with respect to a set of beliefs on the electorate

Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications

The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions that do not refer to ambiguity: expected utility for risk and backward induction. These assumptions, even if normatively appropriate, fail descriptively. This paper relaxes these ancillary assumptions to avoid the descriptive violations, while maintaining AA\xe2\x80\x99s convenient mixture operation. Thus, it becomes possible to test and apply all AA-based ambiguity theories descriptively while avoiding confounds due to violated ancillary assumptions. The resulting tests use only simple stimuli, avoiding noise due to complexity. We demonstrate the latter in a simple experiment where we find that three assumptions about ambiguity, commonly made in AA theories, are violated: reference independence, universal ambiguity aversion, and weak certainty independence. The second, theoretical, part of the paper accommodates the violations found for the first ambiguity theory in the AA model\xe2\x80\x94Schmeidler\xe2\x80\x99s CEU theory\xe2\x80\x94by introducing and axiomatizing a reference dependent generalization. That is, we extend the AA ambiguity model to prospect theory