Stimuli-responsive and self-healing supramolecular Zn(II)-guanosine metal-organic gel for Schottky barrier diode application.

Spontaneous formation of a supramolecular metal-organic hydrogel using unsubstituted guanosine as a ligand and Zn2+ ions is reported. Guanosine, in the presence of NaOH, self-assembled into a stable G-quadruplex structure, which underwent crosslinking through Zn2+ ions to afford a stable hydrogel. The gel has been characterized using several spectroscopic as well as microscopic studies. The hydrogel demonstrated excellent stimuli responsiveness towards various chemicals and pH. Furthermore, the gel exhibited intrinsic thixotropic behavior and showed self-healing and injectable properties. The optical properties of the Zn-guanosine metallo-hydrogel suggested a semiconducting nature of the gel, which has been exploited for fabricating a thin film device based on a Schottky diode interface between metal and a semiconductor. The fabricated device shows excellent charge transport characteristics and linear rectifying behavior. The findings are likely to pave the way for newer research in the area of soft electronic devices fabricated using materials synthesized by employing simple biomolecules.

Molecular Dynamics Simulations of Water-Mediated Cholesterol Capture within an Open-Ended Single-Walled Carbon Nanotube.

The excess concentration of cholesterol in the bloodstream can be brought down to a safer level by utilizing a potential cholesterol-binding agent such as a carbon nanotube (CNT). Here, we have probed solvent-mediated interactions between cholesterol and CNT by performing molecular dynamics simulations and potential-of-mean force (PMF) calculations. Simulations predict favorable interactions between water-mediated cholesterol and CNT owing to strong mutual interactions between them, whereas water plays an opposing role in the association. The breakdown of PMF into its enthalpic and entropic contributions indicates that contrary to traditional entropy-driven hydrophobic association, the cholesterol encapsulation within a CNT is primarily driven by enthalpy.

Water-mediated curvature change in graphene by single-walled carbon nanotubes.

Novel nanostructured materials possessing new architectural segments can be synthesized using various combinations of graphene and carbon nanotubes (CNT) that can result in the generation of enhanced physico-chemical properties within the hybrids. Comprehending the various physical processes involved in the creation of these new segments is crucial for designing an optimized nanomaterial for a specific purpose. In this paper we report induced folding in a graphene sheet resulting from the physical interactions between water-mediated graphene and a CNT. Owing to robust binding interactions between the CNT and a compatible graphene sheet, the latter forms a second domed layer around the former culminating in a structure equivalent to a double-walled CNT. The induced curvature change in graphene by CNT was found to have a strong dependence upon their relative physical dimensions. For example, CNT possessing extremely small diameters are unable to induce any significant curvature changes in longer graphene sheets. The potential-of-mean force (PMF) between our reference graphene and CNT in water suggests a favorable binding interaction of -14.5 kcal mol-1. The breakdown of the PMF into direct graphene-nanotube interactions and water-mediated interactions reveals a huge reduction in the strongly attractive binding interactions between graphene and CNT by the water molecules.

A Theoretical Study of Oxygen Anion Diffusion through the A-Site Deficient SrTiO3 Lattice Structure: A Machine Learning Approach.

The performance of strontium titanate-based perovskite materials, widely employed as electrode materials for reversible solid oxide cells, is directly characterized by their efficiency and their ability to facilitate the diffusion of generated oxygen ions. A technique frequently employed for enhancing oxygen ion diffusivity involves artificially generating A-site vacancies in these structures. In this study, the molecular-level mechanism of oxygen ion diffusion for a range of A-site deficient structures is extensively investigated using combined molecular dynamics simulations and machine learning-based technique. The analysis of molecular simulation trajectories yields diffusion parameters for the bulk system. Additionally, clustering analysis of time-overlapped locations of oxygen ions provides a spatial distribution of oxygen ion dislocations. Concurrently, tracking the motion of individual oxygen ions elucidates the contribution of each ion to the overall ionic conductance. Overall, the systematic generation of A-site deficiency is found to significantly influence oxygen ion dislocations, thereby impacting the performance of these materials in terms of oxide ion conduction.