An automated stochastic docking program with a graphical user interface, RANDOMDOCK (RD), has been developed to aid the development of molecularly imprinted polymers and xerogels. RD supports computations with ab initio and semiempirical quantum chemistry programs. The RD algorithms have been tested by searching for the most stable geometries of a varying number of methacrylic acid molecules interacting with nicotinamide. The optimal structures found are either as stable or more stable than those previously proposed for this molecularly imprinted polymer, illustrating that RD is capable of identifying the lowest-energy structures out of a potentially vast number of possible configurations. RD was subsequently applied to determine the most favorable binding sites between silane molecules and tetracycline (TC) as well as TC analogues. Hydrogen bonding between the templates and a silane is an important determinant of stability. Dispersion interactions are also sizable, sometimes dominant, especially between the largest silane and TC analogues not possessing a site readily available for hydrogen bonding. We highlight the importance of exploring the full intermolecular potential energy landscape when studying systems which may not afford highly specific interactions.

A computational experiment that investigates single-walled carbon nanotubes (SWNTs) has been developed and employed in an upper-level undergraduate physical chemistry laboratory course. Computations were carried out to determine the electronic structure, radial breathing modes, and the influence of the nanotube's diameter on the curvature-induced strain. The students used a new graphical user interface to the TubeGen nanotube builder, which we have implemented as an extension to the open-source molecular editor Avogadro, to build and visualize SWNTs. Geometry optimizations, molecular orbital calculations, and frequencies were computed by an external quantum chemical program.

Advances in high performance computing are transforming the field of theoretical chemistry. Supercomputing hardware is becoming faster and cheaper, and we are at a point where accurate simulations of non-trivial chemical systems are not only possible, they are commonplace. Modern research facilities have incredible amounts of computational power -- at the time of this writing, the Titan supercomputer at Oak Ridge National Laboratory is the most performant cluster in the world, harnessing over 500,000 processors to churn out nearly 18e15 calculations per second. But while that is a impressive amount of power, no one will be surprised when Titan is replaced by a even faster system in a mere matter of months. With such rapid innovation in supercomputing hardware, it takes time to develop applications that harness this power in a way that is accessible to non-technical researchers. Using a modern supercomputing system requires knowledge of resource scheduling, shell scripting, parallel computing environments, and networking. The main focus of my research is the design and implementation of tools that can bring the incredible power of large scale simulations into the hands of researchers who are just interested in performing their domain-specific work, instead of configuring heavily-distributed simulations. To this end, I've developed a framework for integrating fully automatic structure searches with supercomputing resources. The LIBGLOBALSEARCH library is a platform for performing highly parallel searches for stable and metastable structures in a chemical system. It abstracts away the details of generating and staging input files for a simulation, scheduling calculations on supercomputing resources, as well as retrieval and analysis of calculation results. I've written the XTALOPT, GAPC, and RANDOMDOCK programs using this framework to identify energetically favorable species in such diverse categories as periodic solids, nanoclusters, and molecular clusters. The chapters in Part I cover these codes and deal with structure prediction in general. An application of the XTALOPT algorithm to locate stable crystalline magnesium polyhydrides under extreme pressures is included in Chapter 7. I've developed additional tools of general use to computational chemists along the way. Chapter 10 describes a visual crystallographic toolkit that provides a graphical user interface to a number of algorithms I wrote during the development of XTALOPT. Chapter 11 covers a virtual nanotube builder written for an undergraduate computational chemistry lab. Chapter 12 summarizes a number of chemical rendering techniques implemented in the Visualization ToolKit package. A novel algorithm that identifies duplicate crystal structures is presented in Chapter 13. Chapter 14 describes recent and future work in my career as an R&D engineer at Kitware. The appendix contains a tutorial for the XTALOPT crystal structure prediction software. All of the code produced over the course of my graduate work is freely available for use, modification, and redistribution under open source licenses.

Evolutionary structure searches are used to predict stable phases with unique stoichiometries in the hydrogen-rich region of the magnesium/hydrogen phase diagram under pressure. MgH$_4$, MgH$_{12}$ and MgH$_{16}$ are found to be thermodynamically stable with respect to decomposition into MgH$_2$ and H$_2$ near 100 GPa, and all lie on the convex hull by 200 GPa. MgH$_4$ contains two H$^-$ anions and one H$_2$ molecule per Mg$^{2+}$ cation, whereas the hydrogenic sublattices of MgH$_{12}$ and MgH$_{16}$ are composed solely of H$_2^{\delta -}$ molecules. The high-hydrogen content stoichiometries have a large density of states at the Fermi level, and the $T_c$ of MgH$_{12}$ at 140 GPa is calculated to be nearly three times greater than that of the classic hydride, MgH$_2$, at 180 GPa.

Background: The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types.Results: The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here.Conclusions: Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful plugin mechanism to support new features in organic chemistry, inorganic complexes, drug design, materials, biomolecules, and simulations. Avogadro is freely available under an open-source license from http://avogadro.openmolecules.net.

BACKGROUND:The Blue Obelisk movement was established in 2005 as a response to the lack of Open Data, Open Standards and Open Source (ODOSOS) in chemistry. It aims to make it easier to carry out chemistry research by promoting interoperability between chemistry software, encouraging cooperation between Open Source developers, and developing community resources and Open Standards.RESULTS:This contribution looks back on the work carried out by the Blue Obelisk in the past 5 years and surveys progress and remaining challenges in the areas of Open Data, Open Standards, and Open Source in chemistry.CONCLUSIONS:We show that the Blue Obelisk has been very successful in bringing together researchers and developers with common interests in ODOSOS, leading to development of many useful resources freely available to the chemistry community.

A new version of XtalOpt, a user-friendly GPL-licensed evolutionary algorithm for crystal structure prediction, is available for download from the CPC library or the XtalOpt website, http://xtalopt.openmolecules.net. The new version now supports four external geometry optimization codes (VASP, GULP, PWSCF, and CASTEP), as well as three queuing systems: PBS, SGE, SLURM, and “Local”. The local queuing system allows the geometry optimizations to be performed on the user’s workstation if an external computational cluster is unavailable. Support for the Windows operating system has been added, and a Windows installer is provided. Numerous bugfixes and feature enhancements have been made in the new release as well.

We describe the implementation of XTALCOMP, an efficient, reliable, and open-source library that tests if two crystal descriptions describe the same underlying structure. The algorithm has been tested and found to correctly identify duplicate structures in spite of the "real-world" difficulties that arise from working with numeric crystal representations: degenerate unit cell lattices, numerical noise, periodic boundaries, and the lack of a canonical coordinate origin. The library is portable, open, and not dependent on any external packages. A web interface to the algorithm is publicly accessible at http://xtalopt.openmolecules.net/xtalcomp/xtalcomp.html.Program summaryProgram title: XtalCompCatalogue identifier: AEKV_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKV_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: "New" (3-clause) BSD [1]No. of lines in distributed program, including test data, etc.: 3148No. of bytes in distributed program, including test data, etc.: 21 860Distribution format: tar.gzProgramming language: C++Computer: No restrictionsOperating system: All operating systems with a compliant C++ compiler.Classification: 7.8Nature of problem: Computationally identifying duplicate crystal structures taken from the output of modern solid state calculations is a non-trivial exercise for many reasons. The translation vectors in the description are not unique - they may be transformed into linear combinations of themselves and continue to describe the same extended structure. The coordinates and cell parameters contain numerical noise. The periodic boundary conditions at the unit cell faces, edges, and corners can cause very small displacements of atomic coordinates to result in very different representations. The positions of all atoms may be uniformly translated by an arbitrary vector without modifying the underlying structure. Additionally, certain applications may consider enantiomorphic structures to be identical.Solution method: The XtalComp algorithm overcomes these issues to detect duplicate structures regardless of differences in representation. It begins by performing a Niggli reduction on the inputs, standardizing the translation vectors and orientations. A transform search is performed to identify candidate sets of rotations, reflections, and translations that potentially map the description of one crystal onto the other, solving the problems of enantiomorphs and rotationally degenerate lattices. The atomic positions resulting from each candidate transform are then compared, using a cell-expansion technique to remove periodic boundary issues. Computational noise is treated by comparing non-integer quantities using a specified tolerance.Running time: The test run provided takes less than a second to complete.References:[1] http://opensource.org/licenses/BSD-3-Clause. (C) 2011 Elsevier B.V. All rights reserved.