Nanostructured polymetallaynes of controlled length: Synthesis and characterization of oligomers and polymers from 1,1′‐bis‐(ethynyl)4,4′‐biphenyl bridging Pt(II) or Pd(II) centers

The reactivity of square planar palladium(II) and platinum(II) complexes in trans or cis configuration, namely trans or cis‐[dichlorobis(tributylphosphine)platinum(II)] and trans‐[dichlorobis(tributylphosphine)palladium(II)] with 1,1′‐bis(ethynyl) 4,4′‐biphenyl, DEBP, leading to π‐conjugated organometallic oligomeric and polymeric metallaynes, was investigated by a systematic variation of the reaction conditions. The formation of polymers and oligomers with defined chain length [? M(PBu₃)₂ (C?C? C₆H₄? C₆H₄? C?C? )]_n (n = 3–10 for the oligomers, n = 20–50 for the polymers) depends on the configuration of the precursor Pt(II) and Pd(II) complexes, the presence/absence of the catalyst CuI, and the reaction time. A series of model reactions monitored by XPS, GPC, and NMR ³¹P spectroscopy showed the route to modulate the chain growth. As expected, the nature of the transition metal (Pt or Pd) and the molecular weight of the polymers markedly influence the photophysical characteristics of the polymetallaynes, such as optical absorption and emission behavior. Polymetallaynes with nanostructured morphology could be obtained by a simple casting procedure of polymer solutions. © 2007 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 45: 3311–3329, 2007     

A statistical study of the analysis of congested spectra by total spectrum fitting

Heavily overlapped, or congested spectra often display much structure but few individual “lines.” Methods have been devised for analyzing such spectra through nonlinear least-squares fitting of the intensity as a function of wavelength or wavenumber. Such total spectrum fitting (TSF) methods are examined statistically for a simple diatomic model and compared with the standard “measure-assign-fit” (MAF) approach in use since the dawn of spectroscopy. Monte Carlo computations on typically 1000 synthetic spectra at a time verify that the predictions of the variance-covariance matrix are reliable under many circumstances. However in regions where the P and R branches double up, the predicted standard errors in the key spectroscopic constants rise sharply and greatly exceed estimates from the Monte Carlo ensemble statistics. In the same regions, the MAF method actually gives better precision. However, for imperfectly overlapped R and P branches, the MAF standard errors are typically three times larger than the TSF values; moreover, the MAF statistical errors are dwarfed by bias. The TSF approach, while clearly superior in these tests, has a practical drawback: it, too, can give significant bias if the spectra are analyzed with an incorrect model, as illustrated here through calculations employing the wrong function to describe the spectral lineshape.     

Volume Chemistry of Nitrogen in Binary Metal Nitrides and Subnitrides

A comparison of the concept of volume increments created by W. Biltz with that based on quantum mechanical calculations by R.F.W. Bader was performed for crystal structures of binary metal nitrides and ‐subnitrides. The mutual comparison of both concepts permits insights into the bonding relationships of these compounds and reveals the considerable range of volume demand of a strongly polarisable bonding partner, such as the nitride ion. Finally it becomes clear that the Biltz volume increments show a quantum‐chemical relevance in the chemistry of solids.     

Metallo‐supramolecular micelles: Studies by analytical ultracentrifugation and electron microscopy

In aqueous solutions, amphiphilic block copolymers in which a polystyrene (PS) segment is connected to a poly(ethylene oxide) (PEO) block via a bis(2,2′:6′,2″‐ terpyridine ruthenium) complex can form micelles. Such micelles of the protomer type PS₂₀‐[Ru]‐PEO₇₀, according to the preparation procedure representing frozen micelles, were studied by sedimentation velocity and sedimentation equilibrium analysis in an analytical ultracentrifuge and by transmission electron microscopy, with different techniques applied for the sample preparation. The particles obtained were surprisingly multifarious in size. In ultracentrifugation experiments performed at relatively low salt concentrations, the distributions of the sedimentation coefficient s_20,w showed a pronounced peak at 9.6 S and a broad, only partly separated second peak around 14 S. The molar mass of the particles at the peak was around 430,000 g/mol, corresponding to an aggregation number of approximately 85. The average hydrodynamic diameter of the particles in the peak fraction was approximately 13 nm. In electron micrographs of negatively stained samples, spheres of diameters between 10 and 25 nm were the most abundant particles, but larger ones with a wide size range were also visible. The latter particles apparently were composed of smaller ones. The data from both sedimentation analysis and electron microscopy showed that (1) the studied compound formed primary micelles of diameters around 20 nm and (2) the primary micelles had a tendency toward aggregation. © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 3159–3168, 2003     

Sugar conjugates of fulvestrant (ICI 182,780): efficient general procedures for glycosylation of the fulvestrant core

We have prepared glucose and cellobiose conjugates at the phenolic 3- and hydroxylic 17-positions of the pure anti-estrogenic compound fulvestrant (ICI 182,780), which has recently been approved in the USA for the treatment of advanced postmenopausal breast cancer. Glycosylation at the 17-position was achieved most effectively using pivaloyl protection of the sugar imidates employed, which we found suppressed the competing transacylation reaction and led to improved yields of the product glycosides.     

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.