Oxidative regulation of the mechanical strength of a C–S bond

The mechanical strength of individual polymer chains is believed to underlie a number of performance metrics in bulk materials, including adhesion and fracture toughness. Methods by which the intrinsic molecular strength of the constituents of a given polymeric material might be switched are therefore potentially useful both for applications in which triggered property changes are desirable, and as tests of molecular theories for bulk behaviors. Here we report that the sequential oxidation of sulfide containing polyesters (PE-S) to the corresponding sulfoxide (PE-SO) and then sulfone (PE-SO2) first weakens (sulfoxide), and then enhances (sulfone), the effective mechanical integrity of the polymer backbone; PE-S ∼ PE-SO2 > PE-SO. The relative mechanical strength as a function of oxidation state is revealed through the use of gem-dichlorocyclopropane nonscissile mechanophores as an internal standard, and the observed order agrees well with the reported bond dissociation energies of C–S bonds in each species and with the results of CoGEF modeling.

The mechanical strength of individual polymer chains is believed to underlie a number of performance metrics in bulk materials, including adhesion and fracture toughness.     

Rapid,Traceless, AgI‐Promoted Macrocyclization of Peptides Possessing an N‐Terminal Thioamide

Peptide macrocyclization is often a slow process, plagued by epimerization and cyclodimerization. Herein, we describe a new method for peptide macrocyclization employing the Ag^I‐promoted transformation of peptide thioamides. The Ag^I has a dual function: chemoselectively activating the thioamide and tethering the N‐terminal thioamide to the C‐terminal carboxylate. Extrusion of Ag₂S generates an isoimide intermediate, which undergoes acyl transfer to generate the native cyclic peptide, resulting in a rapid, traceless macrocylization process. Cyclic peptides are furnished in high yields within 1 hour, free of epimerization and cyclodimerization.     

The Pearcey Process

The extended Airy kernel describes the space-time correlation functions for the Airy process, which is the limiting process for a polynuclear growth model. The Airy functions themselves are given by integrals in which the exponents have a cubic singularity, arising from the coalescence of two saddle points in an asymptotic analysis. Pearcey functions are given by integrals in which the exponents have a quartic singularity, arising from the coalescence of three saddle points. A corresponding Pearcey kernel appears in a random matrix model and a Brownian motion model for a fixed time. This paper derives an extended Pearcey kernel by scaling the Brownian motion model at several times, and a system of partial differential equations whose solution determines associated distribution functions. We expect there to be a limiting nonstationary process consisting of infinitely many paths, which we call the Pearcey process, whose space-time correlation functions are expressible in terms of this extended kernel.     

AN ALTERNATIVE SPECIFICATION FOR MODELING GROUNDWATER DYNAMICS

This research extends previous work with dynamic models to manage groundwater quality by using the consumptive nitrate use rate instead of the nitrate application rate. The analysis indicates that misspecification results in overestimation of economic benefits, and supra-optimum nitrogen fertilizer application rates and groundwater nitrate stocks at a steady state.     

Nano-electrochemical detection of hydrogen or protons using palladium nanoparticles: distinguishing surface and bulk hydrogen.

The benefits of using nanoparticle-modified electrodes are exemplified through the electrochemical detection of protons and/or hydrogen. It is shown that a palladium-nanoparticle-modified boron-doped diamond allows voltammetric information relating to the relative roles played by the surface and the bulk metal to be obtained for the proton-hydrogen system at palladium surfaces which is not accessible using palladium macroelectrodes or microelectrodes.     

Degradative chain transfer in vinyl acetate polymerizations using toluene as solvent

In this work, we propose that retardation in vinyl acetate polymerization rate in the presence of toluene is due to degradative chain transfer. The transfer constant to toluene (C_trs) determined using the Mayo method is equal to 3.8 × 10^?3, which is remarkably similar to the value calculated from the rate data, assuming degradative chain transfer (2.7 × 10^?3). Simulations, including chain‐length‐dependent termination, were carried out to compare our degradative chain transfer model with experimental results. The conversion–time profiles showed excellent agreement between experiment and simulation. Good agreement was found for the M_n data as a function of conversion. The experimental and simulation data strongly support the postulate that degradative chain transfer is the dominant kinetic mechanism. © 2007 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 45: 3620–3625, 2007     

Cognitive Demands and Second-Language Learners: A Framework for Analyzing Mathematics Instructional Contexts

The issues involved in teaching English language learners mathematics while they are learning English pose many challenges for mathematics teachers and highlight the need to focus on language-processing issues related to teaching mathematical content. Two realistic-type problems from high-stakes tests are used to illustrate the complex interactions between culture, language, and mathematical learning. The analyses focus on aspects of the problems that potentially increase cognitive demands for second-language learners. An analytical framework is presented that is designed to enable mathematics teachers to identify critical elements in problems and the learning environment that contribute to increased cognitive demands for students of English as a second language. The framework is proposed as a cycle of teacher reflection that would extend a constructivist model of teaching to include broader linguistic, cultural, and cognitive processing issues of mathematics teaching, as well as enable teachers to develop more accurate mental models of student learning.