Molecular recognition of avidin on biotin-functionalized gold surfaces detected by FT-IRRAS and use of metal carbonyl probes

Fourier transform infrared reflection-absorption spectroscopy (FT-IRRAS) was successively used to monitor the covalent immobilization of biotin molecules onto a planar gold substrate covered with a self-assembled monolayer of cystamine and to transduce the molecular recognition of avidin and biotin. This detection was greatly facilitated and made selective by the labeling of avidin and of biotin with various transition metal carbonyl probes. The binding of avidin to the surface was optimized by blocking the nonspecific binding sites by adsorption of an unrelated protein, bovine serum albumin. This work exemplifies the feasibility of detecting biomolecular associations involving molecules of any size at a liquid/solid interface by using a simple and accessible surface analysis technique.     

Poisson discretizations of Wiener functionals and Malliavin operators with Wasserstein estimates

This article proposes a global, chaos-based procedure for the discretization of functionals of Brownian motion into functionals of a Poisson process with intensity $\lambda >0$. Under this discretization we study the weak convergence, as the intensity of the underlying Poisson process goes to infinity, of Poisson functionals and their corresponding Malliavin-type derivatives to their Wiener counterparts. In addition, we derive a convergence rate of $O\left({\lambda }^{?1∕4}\right)$ for the Poisson discretization of Wiener functionals by combining the multivariate Chen–Stein method with the Malliavin calculus. Our proposed sufficient condition for establishing the mentioned convergence rate involves the kernel functions in the Wiener chaos, yet we provide examples, especially the discretization of some common path dependent Wiener functionals, to which our results apply without committing the explicit computations of such kernels. To the best our knowledge, these are the first results in the literature on the universal convergence rate of a global discretization of general Wiener functionals.     

Synthesis of two-dimensional gallium nitride via spin coating method: influences of nitridation temperatures

This paper reports the synthesis and characterization of gallium nitride (GaN) thin films deposited on p-type silicon (100) substrates by using low cost spin coating method under various nitridation temperatures. This work demonstrated that spin coating with the new prepared precursor solution can be used as a versatile method for the successfully growth of GaN thin films. Furthermore, the influence of varying nitridation temperatures on the structural, morphological, and optical properties of synthesized GaN thin films were studied in this work. The GaN thin films were characterized by X-ray diffraction, field-emission scanning electron microscopy, atomic force microscopy, photoluminescence and Raman spectroscopy. All the characteristics of the GaN thin films were effectively improved with the increasing of the nitridation temperatures from 750 to 950 °C and degraded at temperature of 1,050 °C. The measured results show that nitridation temperature plays an important role in improving the crystalline quality of the GaN thin films and the most efficient nitridation temperature was at 950 °C.     

Dual pH‐ and Temperature‐Responsive Metallosupramolecular Block Copolymers with Tunable Critical Micelle Temperature by Modulation of the Self‐Assembly of NIR‐Emissive Alkynylplatinum(II) Complexes Induced by Changes in Hydrophilicity and Electrostatic Effects

Terpyridylplatinum(II)‐based metallosupramolecular triblock copolymers with hydrophilic alkynyl ligands have been synthesised and characterised. As a result of the intrinsic properties of Pluronics, reversible temperature‐induced micellisation occurred at high temperature leading to aggregation of the platinum(II) complex moieties through Pt???Pt and π–π interactions, resulting in significant UV/Vis absorption and near‐infrared (NIR) emission spectral changes. The critical micelle temperatures of the complexes were found to vary from 21 to 30 °C due to differences in the hydrophilicity of the alkynyl ligands and the electrostatic repulsions between the positively charged platinum(II) complex moieties. One of the complexes with pH‐responsive CH₂NMe₂ groups on the alkynyl ligand was found to show NIR emission that is sensitive to both pH and temperature. Such dual‐responsive behaviour has been ascribed to the modulation of the self‐assembly of the complex moieties by temperature‐induced micellisation and the changes in the hydrophilicity as well as electrostatic interactions upon protonation/deprotonation of the CH₂NMe₂ groups on the alkynyl ligand.     

Precise Size‐Selective Sieving of Nanoparticles Using a Highly Oriented Two‐Dimensional Supramolecular Polymer

The development of size‐selective membranes with well‐defined nanopores towards the precise separation of nanometer‐sized substances is a challenging task to achieve. Here a supramolecular membrane is presented that comprises a highly oriented, honeycomb‐like, 2D supramolecular polymer on a polycarbonate filter support. It enables precise size‐selective sieving of colloidal nanoparticles (NPs). Owing to the uniform parallel‐aligned nanocavities within the 2D supramolecular polymers, the composite membrane shows a high size‐selectivity with a sub‐nanometer accuracy in the cutoff size of about 4.0 nm. In principle, the species of size‐separable particles are unlimited, as demonstrated by quantum dots, noble metal, and metal oxide NPs. This supramolecular membrane combined with filtration advances the potential of NPs in terms of their monochromatic emission and size monodispersity, and also enables rapid removal of small magnetic NP adsorbents that are otherwise difficult to capture.     

Monte Carlo approximation through Gibbs output in generalized linear mixed models

Geyer (J. Roy. Statist. Soc. 56 (1994) 291) proposed Monte Carlo method to approximate the whole likelihood function. His method is limited to choosing a proper reference point. We attempt to improve the method by assigning some prior information to the parameters and using the Gibbs output to evaluate the marginal likelihood and its derivatives through a Monte Carlo approximation. Vague priors are assigned to the parameters as well as the random effects within the Bayesian framework to represent a non-informative setting. Then the maximum likelihood estimates are obtained through the Newton Raphson method. Thus, out method serves as a bridge between Bayesian and classical approaches. The method is illustrated by analyzing the famous salamander mating data by generalized linear mixed models.