Molecular simulations are computer experiments that allow us to investigate thermodynamic and transport properties of complex chemical systems. Here, we have investigated self-assembly of organogelators and analysed the diffusion characteristics of small molecules in the nanopores of zeolites. Molecular gels are attractive soft-materials with viscoelastic properties with applications in drug delivery, tissue engineering, sensing, etc. Small organic amphiphilic gelators act as a building block of complex 3-dimensional network in molecular gels. Due to time and length scale differences, the understanding and characterization of early stage aggregation of gelators is difficult using experimental techniques. Classical and quantum mechanical approaches have been used to understand the self-assembly of gelator molecules and to rationalize the gelation. We have used density functional theory (DFT) to derive new quantity namely, pseudo-cohesive energy density to rationalize the gelation of di-Fmoc-L-lysine. Molecular dynamics is used to probe the self-assembly and conformation of gelators in DMSO-water. We have also studied the self-assembly of 12-hydroxyoctadecanamide in octane. We used DFT to calculate the dimer energy in the vacuum and meta-dynamics simulation to calculate potential of mean force in the condensed phase. Interestingly, we found that, dimer energetics was not sufficient to elucidate bulk aggregation behavior, such as, probability distribution of different dimers in aggregation. We also observed different types of branched and mesh-like networks in the aggregation, which are analogous to the network found through experimental imaging techniques. Zeolites are crystalline materials with well defined nanoporous channels and act as molecular sieves. They are attractive for catalytic applications due to their tunable Bronsted and Lewis acidity. A wide array of zeolite polymorph offers versatile micro and meso-porous channels to accommodate small molecules like glucose to big and complex lignocellulose molecules for undergoing chemical transformations. In this current study, we present the transport properties of -glucose into Faujisite zeolite framework. We have investigated the trajectory of the glucose molecule into porous material and found that, the diffusivity of glucose inside zeolite pore is two order of magnitude smaller than that of bulk solutions. We have also observed the variable loading rate of glucose molecule inside pore at different temperatures.

A key use of high throughput sequencing technology is the sequencing and assembly of full genome sequences. These genome assemblies are commonly assessed using statistics relating to contiguity of the assembly. Measures of contiguity are not strongly correlated with information about the biological completion or correctness of the assembly, and a commonly reported metric, N50, can be misleading. Over the past ten years, multiple research groups have rejected the overuse of N50 and sought to develop more informative metrics. This research seeks to create a ranking method that includes biologically relevant information about the genome, such as completeness and correctness of the genome. Approximately eight hundred genomes were initially selected, and information about their completeness, contiguity, and correctness was gathered using publicly available tools. Using this information, these genomes were scored by subject matter experts. This rating system was explored using supervised machine learning techniques. A number of classifiers and regressors were tested using cross validation. Two metrics were explored in this research. First, a metric that describes the distance to the ideal genome was created as a way to explore the incorporation of human subject matter expert knowledge into the genome assembly assessment process. Second, random forest regression was found to be the method of supervised learning with the highest scores. A model created by an optimized random forest regressor was saved, and a tool was created to load the saved model and rank genomes provided by the end user. These metrics both serve as ways to incorporate human subject matter expert knowledge into genome assembly assessment.

The first step in the assembly of an overset grid system is to cut holes or to mark points that are inside a solid body and outside the domain of interest. Most existing approaches have been developed for use only with structured grids. A fast and robust approach that can be applied to structured, unstructured, or generalized grid topologies, with a minimum of user inputs, is desired. A new hole cutting process is presented that utilizes a Cartesian Binary tree representation of the geometry to provide a fast and efficient algorithm applicable to generalized grids. An algorithm has also been developed to mark the fringe points and find its donors. The effectiveness of the algorithm is demonstrated by testing it on generalized and structured grids.

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