CuO/CuO Nanoparticle-Cotton Fiber Biocomposite Catalyst: Self-Improvement through Morphological Changes during Methyl Orange Degradation.

In this study, the application of a novel polymer-supported CuO/CuO nanoparticle catalyst for the efficient degradation of an organic dye, in which the nanoparticle catalyst is incorporated within a natural plant fiber matrix, is presented. The use of plant fibers provides a renewable and environmentally friendly support material, and enhances the catalytic efficiency over consecutive degradation cycles. This innovative design promotes the efficient adsorption and degradation of dye.

Repurposing Cotton Gin Trash for Cellulose Nanofibril-Silver Hybrid and Ultralight Silver-Infused Aerogel.

Cellulose nanofibril-silver (CNF-Ag) hybrid and ultralight silver-infused aerogel were produced using cotton gin trash (CGT), an abundant agro-waste material. This repurposing of CGT was achieved by exploiting its potential for CNF extraction and the in situ synthesis of silver nanoparticles (Ag NPs). CNFs were extracted from CGT through a mechanical shearing process.

On the Nature of Guest Complexation in Water: Triggered Wetting-Water-Mediated Binding.

The complexity of macromolecular surfaces means that there are still many open questions regarding how specific areas are solvated and how this might affect the complexation of guests. Contributing to the identification and classification of the different possible mechanisms of complexation events in aqueous solution, and as part of the recent SAMPL8 exercise, we report here on the synthesis and conformational properties of TEEtOA , a cavitand with conformationally flexible ethyl groups at its portal. Using a combination of ITC and NMR spectroscopy, we report the binding affinities of a series of carboxylates to and compare it to a related cavitand TEMOA .

Proximal charge effects on guest binding to a non-polar pocket.

Science still does not have the ability to accurately predict the affinity that ligands have for proteins. In an attempt to address this, the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) series of blind predictive challenges is a community-wide exercise aimed at advancing computational techniques as standard predictive tools in rational drug design. In each cycle, a range of biologically relevant systems of different levels of complexity are selected to test the latest modeling methods.