Diffusion-based deprotection in mesoporous materials: a strategy for differential functionalization of porous silica particles

A monodisperse, spherical mesoporous silica (Acid-Prepared Mesoporous Spheres, APMS) was prepared and then functionalized with two types of Fmoc (9-fluorenylmethyloxycarbonyl) terminated silanes with variable chain lengths. N2 physisorption experiments indicated that, under some conditions, the pores of the solid were completely filled by the Fmoc-protected organosilanes. These blocked pores were then "reopened" by the cleavage of Fmoc groups with a piperidine solution. In contrast to the solution reaction, this deprotection reaction was much slower within the pores. The rate of deprotection was followed by UV/visible spectroscopy, and a plot of Fmoc released versus time showed a sigmoidal shape. An empirical model was applied to the data, which indicated that the reaction was influenced by the concentration and temperature of the piperidine solution as well as the number of Fmoc moieties within the pores. Using this information, we show that the location of the deprotection reaction in the pores of the silica can be empirically controlled. Our work provides a method by which the surface of the porous silica can be functionalized in a well-defined manner. This method can be used to produce materials for catalysis or drug delivery.     

Generating Encoded Compound Libraries for Fabricating Microarrays as a High-Throughput Protein Ligand Discovery Platform

We demonstrate an effective method for generating libraries of encoded compounds for fabricating large compound microarrays on solid supports. This method is based on one-bead, one-compound synthesis and employs a novel trilayer bead-partition scheme that ensures sufficient quantity of synthesized compounds releasable from each bead for compound microarray fabrication in high-throughput protein–ligand discovery assays.

[Supplementary materials are available for this article. Go to the publisher's online edition of Synthetic Communications® for the following free supplemental resource(s): Full experimental and spectral details.]     

Molecularly ordered inorganic frameworks in layered silicate surfactant mesophases.

Self-assembled lamellar silica-surfactant mesophase composites have been prepared with crystal-like ordering in the silica frameworks using a variety of cationic surfactant species under hydrothermal conditions. These materials represent the first mesoscopically ordered composites that have been directly synthesized with structure-directing surfactants yielding highly ordered inorganic frameworks. One-dimensional solid-state 29Si NMR spectra, X-ray diffraction patterns, and infrared spectra show the progression of molecular organization in the self-assembled mesophases from structures with initially amorphous silica networks into sheets with very high degrees of molecular order. The silicate sheets appear to be two-dimensional crystals, whose structures and rates of formation depend strongly on the charge density of the cationic surfactant headgroups. Two-dimensional solid-state heteronuclear and homonuclear NMR measurements show the molecular proximities of the silica framework sites to the structure-directing surfactant molecules and establish local Si-O-Si bonding connectivities in these materials.     

Model validation in operations research

Numerous articles have appeared in the literature expressing different degrees of concern with the methodology of OR in general and with the validation of OR models in particular. Suggestions have been formulated to remove some of the shortcomings of the methodology as currently practised and to introduce modifications in the approach because of the changing nature of the problems tackled. Advances in modeling capabilities and solution techniques have also had considerable impact on the way validation is perceived. Large scale computer-based mathematical models and especially simulation models have brought new dimensions to the notion of validation. Terms like ‘confidence’, ‘credibility and reliability’, ‘model assessment and evaluation’, ‘usefulness and usability of the model’ have become rather common. This paper is an attempt, through an interpretation of the literature, to put model validation and related issues in a framework that may be of use both to model-builders and to decision-makers.     

Silica microparticles as a solid support for gadolinium phosphonate magnetic resonance imaging contrast agents

Particle-based magnetic resonance imaging (MRI) contrast agents have been the focus of recent studies, primarily due to the possibility of preparing multimodal particles capable of simultaneously targeting, imaging, and treating specific biological tissues in vivo. In addition, particle-based MRI contrast agents often have greater sensitivity than commercially available, soluble agents due to decreased molecular tumbling rates following surface immobilization, leading to increased relaxivities. Mesoporous silica particles are particularly attractive substrates due to their large internal surface areas. In this study, we immobilized a unique phosphonate-containing ligand onto mesoporous silica particles with a range of pore diameters, pore volumes, and surface areas, and Gd(III) ions were then chelated to the particles. Per-Gd(III) ionic relaxivities ranged from ～2 to 10 mM(-1) s(-1) (37 °C, 60 MHz), compared to 3.0-3.5 mM(-1) s(-1) for commercial agents. The large surface areas allowed many Gd(III) ions to be chelated, leading to per-particle relaxivities of 3.3 × 10(7) mM(-1) s(-1), which is the largest value measured for a biologically suitable particle.     

On an efficient implementation and mass boundedness conditions for a discrete Dirichlet problem associated with a nonlinear system of singular partial differential equations

In this work, we propose an efficient implementation of a finite-difference method employed to approximate the solutions of a system of partial differential equations that appears in the investigation of the growth of biological films. The associated homogeneous Dirichlet problem is discretized using a linear approach. This discretization yields a positivity- and boundedness-preserving implicit technique which is represented in vector form through the multiplication by a sparse matrix. A straightforward implementation of this methodology would require a substantial amount of computer memory and time, but the problem is conveniently coded using a continual reduction of the zero sub-matrices of the representing matrix. In addition to the conditions that guarantee the positivity and the boundedness of the numerical approximations, we establish some parametric constraints that assure that the same properties for the discrete total mass at each point of the mesh-grid and each discrete time are actually satisfied. Some simulations are provided in order to illustrate both the performance of the implementation, and the preservation of the positivity and the boundedness of the numerical approximations.     

Convenient Pd‐Catalyzed Synthesis of Large Unimolecular Star Polyethylene Nanoparticles

A simplistic convenient “arm‐first” catalytic synthesis method is demonstrated to render soft unimolecular star polyethylene nanoparticles. Low‐dispersity polyethylene arms of controllable length and topology are first synthesized via Pd‐catalyzed “living” ethylene poly­merization. The subsequent addition of norbornadiene as a unique cross‐linker renders the block polymer containing a short polynorbornadiene (PNBD) sequence. Efficient and rapid catalytic cross‐linking of the PNBD sequences occurs in the polymer precipitation and drying steps to give rise to star polyethylene nanoparticles. The star polymers are featured with tunable arm length and topology, high molecular weight (as high as 1770 kg mol⁻¹), high arm numbers (as high as 88), and desirable average nano­particle size (29−72 nm).