Supramolecular Copolymerization as a Strategy to Control the Stability of Self‐Assembled Nanofibers

A major challenge in supramolecular polymerization is controlling the stability of the polymers formed, that is, controlling the rate of monomer exchange in the equilibrium between monomer and polymer. The exchange dynamics of supramolecular polymers based on benzene‐1,3,5‐tricarboxamide (BTA) can be regulated by copolymerizing molecules with dendronized (dBTA) and linear (nBTA) ethylene glycol‐based water‐soluble side chains. Whereas nBTAs form long nanofibers in water, dBTAs do not polymerize, forming instead small spherical aggregates. The copolymerization of the two BTAs results in long nanofibers. The exchange dynamics of both the BTA monomers in the copolymer are significantly slowed down in the mixed systems, leading to a more stable copolymer, while the morphology and spectroscopic signature of the copolymers are identical to that of nBTA homopolymer. This copolymerization is the supramolecular counterpart of styrene/ maleic anhydride copolymerization.     

On Silylated Oxonium and Sulfonium Ions and Their Interaction with Weakly Coordinating Borate Anions

Attempts have been made to prepare salts with the labile tris(trimethylsilyl)chalconium ions, [(Me₃Si)₃E]⁺ (E=O, S), by reacting [Me₃Si-H-SiMe₃][B(C₆F₅)₄] and Me₃Si[CB] (CB⁻=carborate=[CHB₁₁H₅Cl₆]⁻, [CHB₁₁Cl₁₁]⁻) with Me₃Si-E-SiMe₃. In the reaction of Me₃Si-O-SiMe₃ with [Me₃Si-H-SiMe₃][B(C₆F₅)₄], a ligand exchange was observed in the [Me₃Si-H-SiMe₃]⁺ cation leading to the surprising formation of the persilylated [(Me₃Si)₂(Me₂(H)Si)O]⁺ oxonium ion in a formal [Me₂(H)Si]⁺ instead of the desired [Me₃Si]⁺ transfer reaction. In contrast, the expected homoleptic persilylated [(Me₃Si)₃S]⁺ ion was formed and isolated as [B(C₆F₅)₄]⁻ and [CB]⁻ salt, when Me₃Si-S-SiMe₃ was treated with either [Me₃Si-H-SiMe₃][B(C₆F₅)₄] or Me₃Si[CB]. However, the addition of Me₃Si[CB] to Me₃Si-O-SiMe₃ unexpectedly led to the release of Me₄Si with simultaneous formation of a cyclic dioxonium dication of the type [Me₃Si-μO-SiMe₂]₂[CB]₂ in an anion-mediated reaction. DFT studies on structure, bonding and thermodynamics of the [(Me₃Si)₃E]⁺ and [(Me₃Si)₂(Me₂(H)Si)E]⁺ ion formation are presented as well as mechanistic investigations on the template-driven transformation of the [(Me₃Si)₃E]⁺ ion into a cyclic dichalconium dication [Me₃Si-μE-SiMe₂]₂²⁺.     

Diindenopyrazines: Electron-Deficient Arenes

The syntheses, properties and application of the air-stable electron acceptors, diindenopyrazines 4 a – g are reported demonstrating the introduction of functional aryl groups in the 6- and 12-positions. The targets are accessible on the hundred milligram to gram scale. The structure of the aryl groups in 4 a – g modulates their solubility, redox potentials and optical properties. The introduction of electron-poor aryl groups to the electron-poor diindenopyrazine backbone reduces the electron affinity to −4 eV, making the compounds attractive as n-semiconductors. A simple organic field-effect transistor of 4 e –without optimization– shows electron transport with a mobility of up to 0.037 cm² V⁻¹ s⁻¹.     

Tracking control for underactuated non-minimum phase multibody systems

Nonlinear Dynamics - We consider tracking control for multibody systems which are modeled using holonomic and non-holonomic constraints. Furthermore, the systems may be underactuated and contain...     

Magnetic resonance in an atomic vapor excited by a mechanical resonator

We demonstrate a direct resonant interaction between the mechanical motion of a mesoscopic resonator and the spin degrees of freedom of a sample of neutral atoms in the gas phase. This coupling, mediated by a magnetic particle attached to the tip of the miniature mechanical resonator, excites a coherent precession of the atomic spins about a static magnetic field. The novel coupled atom-resonator system may enable development of low-power, high-performance sensors, and enhance research efforts connected with the manipulation of cold atoms, quantum control, and high-resolution microscopy.     

Promoter Activation in Δhfq Mutants as an Efficient Tool for Specialized Metabolite Production Enabling Direct Bioactivity Testing

Natural products (NPs) from microorganisms have been important sources for discovering new therapeutic and chemical entities. While their corresponding biosynthetic gene clusters (BGCs) can be easily identified by gene‐sequence‐similarity‐based bioinformatics strategies, the actual access to these NPs for structure elucidation and bioactivity testing remains difficult. Deletion of the gene encoding the RNA chaperone, Hfq, results in strains losing the production of most NPs. By exchanging the native promoter of a desired BGC against an inducible promoter in Δhfq mutants, almost exclusive production of the corresponding NP from the targeted BGC in Photorhabdus, Xenorhabdus and Pseudomonas was observed including the production of several new NPs derived from previously uncharacterized non‐ribosomal peptide synthetases (NRPS). This easyPACId approach (easy Promoter Activated Compound Identification) facilitates NP identification due to low interference from other NPs. Moreover, it allows direct bioactivity testing of supernatants containing secreted NPs, without laborious purification.     

Using linear programming to analyze and optimize stochastic flow lines

This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time, to determine a production rate estimate. As our methodology is purely numerical, it offers the full modeling flexibility of stochastic simulation with respect to the probability distribution of processing times. However, unlike discrete-event simulation models, it also offers the optimization power of linear programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines.