Anionic iron(II) alkoxides as initiators for the controlled ring‐opening polymerization of lactide

Hetero‐bimetallic Fe(II) alkoxide/aryloxides were evaluated as initiators for the ring‐opening polymerization of rac‐lactide. [(THF)NaFe(O^tBu)₃]₂ ( 1 ) and [(THF)₄Na₂Fe(2,6‐diisopropylphenolate)₄] ( 2 ) (THF = tetrahydrofuran) both polymerized lactide efficiently at room temperature, with complex 1 affording better control over the molecular weight parameters of the resultant polymer. At conversions below 70%, a linear increase in molecular weight with conversion was observed, indicative of a well‐controlled polymerization process. Complex 2 is the first example of a dianionic Fe(II) alkoxide and has been structurally characterized to reveal a distorted square planar FeO₄ array in which both Na counterions bridge two aryloxide ligands and are further complexed by two THF ligands. © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 3798–3803, 2003     

Variational aspects of Faddeev calculations

We examine differences between³H binding energies obtained by solving the Faddeev equations using standard partial-wave expansion procedures and results from solving the Schrödinger equation by means of the coupled-rearrangement-channel variational method. Variational bounds generated from Faddeev solutions for several contemporary, realistic potential models are presented as a function of the number of partial waves retained in the potential expansion. We demonstrate that the Faddeev wave function yields an optimal variational bound for the partial-wave truncated potential from which it is generated, but it does not yield optimal bounds for the full Hamiltonian or when the potential is partial-wave truncated at a different level. Finally, qualitative differences between³H solutions for static models such as the AV14 and RSC potentials and for momentum-dependent models such as the Nijmegen soft-core and Paris potentials are explored, and comparison is made with solutions for the RSC/TM two-body-force plus three-body-force model.     

Fluorescence anisotropy decay study of self-association of bacterial luciferase intermediates

The fluorescence dynamics parameters of the fluorescent transient flavin-luciferase species from the typesVibrio fischeri andPhotobacterium leiognathi are presented. The fluorescence anisotropy decay is a single exponential function for both types. The correlation time is 70 ns for theP. leiognathi fluorescent transient intermediate (2°C, aqueous buffer, pH 7.0), consistent with the rotational correlation time of the luciferase macromolecule (77 kD) to which the flavin fluorophore is rigidly attached. In contrast, for theV. fischeri species the observed correlation time for the anisotropy decay function is 133 ns. This suggests that protein self-association occurs in theV. fischeri case and this is confirmed by filtration, where the fluorescent transient fromV. fischeri does not pass through a 100,000 molecular weight cutoff membrane, whereas theP. leiognathi species does. The filtration method also demonstrates self-association in the luciferase peroxyflavin and photoflavin fromV. fischeri. A monomer-dimer equilibrium also explains the previously reported high correlation times for theV. harveyi luciferase-flavin species. It is proposed that the self-association competes with the lumazine protein interaction in the bioluminescence reaction.     

An algorithm for packing regular multistrand polypeptide structures by energy minimization

An algorithm has been developed for packing polypeptide chains by energy minimization subject to regularity conditions, in which regularity is maintained without the addition of pseudoenergy terms by defining the energy as a function of appropriately chosen independent variables. The gradient of the energy with respect to the independent variables is calculated analytically. The speed and efficiency of convergence of the algorithm to a local energy minimum are comparable to those of existing algorithms for minimizing the energy of a single polypeptide chain. The algorithm has been used to reinvestigate the minimum-energy regular structures of three-stranded (L -Ala)₈, three-stranded (L -Val)₆, five-stranded (L -Ile)₆, and the regular and truncated three-stranded (Gly-L -Pro-L -Pro)₄ triple helices. Local minima with improved packing energies, but with essentially unchanged geometrical properties, were obtained in all cases. The algorithm was also used to reinvestigate the structures proposed previously for the I and II forms of crystalline silk fibroin. The silk II structure was reproduced with slightly improved packing and little other change. The orthorhombic silk I structure showed more change and considerably improved packing energy, but the new regular monoclinic silk I structure had considerably higher energy. The results support the structure proposed previously for silk II and the orthorhombic structure, but not the monoclinic structure proposed for silk I. © 1994 by John Wiley & Sons, Inc.     

Learning and transfer in dynamic decision environments

An important aspect of learning is the ability to transfer knowledge to new contexts. However, in dynamic decision tasks, such as bargaining, firefighting, and process control, where decision makers must make repeated decisions under time pressure and outcome feedback may relate to any of a number of decisions, such transfer has proven elusive. This paper proposes a two-stage connectionist model which hypothesizes that decision makers learn to identify categories of evidence requiring similar decisions as they perform in dynamic environments. The model suggests conditions under which decision makers will be able to use this ability to help them in novel situations. These predictions are compared against those of a one-stage decision model that does not learn evidence categories, as is common in many current theories of repeated decision making. Both models' predictions are then tested against the performance of decision makers in an Internet bargaining task. Both models correctly predict aspects of decision makers' learning under different interventions. The two-stage model provides closer fits to decision maker performance in a new, related bargaining task and accounts for important features of higher-performing decision makers' learning. Although frequently omitted in recent accounts of repeated decision making, the processes of evidence category formation described by the two-stage model appear critical in understanding the extent to which decision makers learn from feedback in dynamic tasks. Faison (Bud) Gibson is an Assistant Professor at College of Business, Eastern Michigan University. He has extensive experience developing and empirically testing models of decision behavior in dynamic decision environments.     

Stability of muon-oxygen bond sites in RBa2Cu3O7

Relative energies of muon probe sites in the chain region of RBa₂Cu₃O₇ (RBCO) are investigated using a molecular quantum chemistry calculation for (Oμ)⁻ embedded in a cluster of point charges to simulate local charge distributions in RBCO. Partial Cu−O chain covalency results in a O-μ...O muon site between the chain and bridging oxygens. However, Cu-μ “hydride”-like sites are suggested by results for nominally ionic clusters.