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Hydrothermal synthesis techniques have been used to prepare a range of cerium based solid solutions. These materials have been studied by a range of techniques, principally diffraction and temperature programmed reduction.
The full crystal structure refinement of scheelite CeGeO4 has been carried out for the first time, using neutron powder diffraction data to propose a monoclinic space group for this material, instead of the tetragonal structure that has been proposed in the literature. In-situ powder neutron studies have been conducted in order to monitor the reduction and reoxidation of the Ce(IV) germanate and a Ce(III) germanate that has now been classified as α-Ce2Ge2O7. Rietveld analysis has been carried out using the diffraction patterns to monitor the phase transitions that occur during the redox reaction.
Another phase of Ce2Ge2O7 has been observed for the first time and has been classified as β-Ce2Ge2O7. This higher symmetry supercell is produced via the heating of the α phase under an N2 atmosphere to avoid re-oxidising the material back to CeGeO4. Both materials have been found to oxidise back to the Ce(IV) material, however, heating cerium germanates above 600 °C under reducing conditions leads to the reduction of Ge (IV) down to elemental Ge. This is an irreversible process that limits the use of these materials as oxygen storage materials, although uses could still be found for them at lower temperatures due to all the Ce (IV) in the sample being accessible for reduction at mild temperature and reduction conditions.
Ce-based solid solutions, including substituted CeGeO4 and Ce0.5Zr0.5O2 materials have been synthesised and characterised using diffraction and refinement techniques and tested for their ability to be reduced via the use of temperature programmed reduction.
Based on a three-year inductive field study of first-time founders, we reveal the dynamic identity relationships that tie founders to their ventures: what such relationships comprise, how they evolve over time, and with what strategic implications for the development of new businesses. Specifically, we found that such relationships comprise both identification and construals, which capture the degree to which founders saw their ventures as self-defining and founder-venture psychological distance. Construals, and shifts in construals over time, were critical in explaining how entrepreneurs handled venture-related challenges, as well as how they strategically (re)focused their ventures in terms of scope, whether by diversifying or specializing. By explaining these dynamics, we contribute to research on entrepreneurial identity as well as to construal level theory. In addition, as we distinguish construals from identification, we highlight the importance of construals for understanding identity relationships beyond entrepreneurship. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.15271 .
The article reports methods for the expression and assay of 9-cis-epoxycarotenoid cleavage dioxygenase (NCED), an enzyme involved in the biosynthesis of phytohormone abscisic acid in plants. A method for the preparation of the unstable substrate 9′-cis-neoxanthin from fresh spinach is described. The inhibition of Solanum lycopersicum NCED by a series of aryl hydroxamic acid inhibitors is illustrated, and inhibitors D2 and D4 are assayed against NCED isozymes from Zea mays.
Maximum likelihood estimation (MLE) of latent variable models is often recast as the minimization of a free energy functional over an extended space of parameters and probability distributions. This perspective was recently combined with insights from optimal transport to obtain novel particle-based algorithms for fitting latent variable models to data. Drawing inspiration from prior works which interpret `momentum-enriched' optimization algorithms as discretizations of ordinary differential equations, we propose an analogous dynamical-systems-inspired approach to minimizing the free energy functional. The result is a dynamical system that blends elements of Nesterov's Accelerated Gradient method, the underdamped Langevin diffusion, and particle methods. Under suitable assumptions, we prove that the continuous-time system minimizes the functional. By discretizing the system, we obtain a practical algorithm for MLE in latent variable models. The algorithm outperforms existing particle methods in numerical experiments and compares favourably with other MLE algorithms.
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