Compression of Molecular Interaction Fields Using Wavelet Thumbnails: Application to Molecular Alignment

Self-assembly Processes in Hydrated Montmorillonite by FTIR Investigations

Experimental findings obtained by FTIR and Raman spectroscopies on montmorillonite-water mixtures at three concentration values are presented. To get some insight into the hydrogen bond network of water within the montmorillonite network, FTIR and Raman spectra have been collected as a function of time and then analyzed following two complementary approaches: An analysis of the intramolecular OH stretching mode in the spectral range of 2700–3900 cm⁻¹ in terms of two Gaussian components, and an analysis of the same OH stretching mode by wavelet cross-correlation. The FTIR and Raman investigations have been carried as a function of time for a montmorillonite-water weight composition (wt%) of 20–80%, 25–75%, and 35–65%, until the dehydrated state where the samples appear as a homogeneous rigid layer of clay. In particular, for both the FTIR and Raman spectra, the decomposition of the OH stretching band into a “closed” and an “open” contribution and the spectral wavelet analysis allow us to extract quantitative information on the time behavior of the system water content. It emerges that, the total water contribution inside the montmorillonite structure decreases as a function of time. However, the relative weight of the ordered water contribution diminishes more rapidly while the relative weight of the disordered water contribution increases, indicating that a residual water content, characterized by a highly structural disorder, rests entrapped in the montmorillonite layer structure for a longer time. From the present study, it can be inferred that the montmorillonite dehydration process promotes the layer self-assembly.

Chemoinformatics at the University of Sheffield 2002-2014

This paper summarises work in chemoinformatics carried out in the Information School of the University of Sheffield during the period 2002-2014. Research studies are described on fingerprint-based similarity searching, data fusion, applications of reduced graphs and pharmacophore mapping, and on the School's teaching in chemoinformatics.

Using Wavelet Analysis To Assist in Identification of Significant Events in Molecular Dynamics Simulations

Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.

Similarity-driven discovery of zeolite materials for adsorption-based separations

Crystalline porous materials can be exploited in many applications. Discovery of materials with optimum adsorption properties typically involves expensive brute-force characterization of large sets of materials. An alternative approach based on similarity searching that enables discovery of materials with optimum adsorption for CO(2) and other molecules at a fraction of the cost of brute-force characterization is demonstrated.