Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers

09251 Abstracts Collection -- Scientific Visualization

From 06-14-2009 to 06-19-2009, the Dagstuhl Seminar 09251 ``Scientific Visualization \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, over 50 international participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general

Advanced Computer Graphics Aided Molecular Visualization and Manipulation Softwares: The Hierarchy of Research Methodologies

In the present day, the huge obstacles, and the major technical problems encountered by the teaching and research faculties, academicians, industrial specialists, laboratory demonstrators and instructors, fellow students and researchers, etc. are to adopt integrative approaches of demonstrating (learning) chemistry and chemical education, and the realistic ways of delivering (grasping) scientific materials articulately with graceful and effortless manner. Towards minimizing these challenges, various audio-visual tools and technologies, advanced computer aided molecular graphics, freely available electronic gadgets assisted chemistry and chemical education apps, human unreadable data reading and accessing softwares, etc. are being incorporated worldwide as the most indispensable physical and electronic means for successful professionalisms. This short article is essentially a collective report underscoring extraordinary approaches, incredible efforts, and innovative skills of the computer based chemical and molecular graphics towards illuminating intrinsic parts of the chemistry and chemical education, and revealing various aspects of the cutting -edge research. As their representatives, herein, the different type computer coding languages based graphical tools such as Molden, GaussView, Jmol, and Visual Molecular Dynamics (VMD) are referred, and elucidated their potential applications and remarkable attempts in the advancement of diverse areas of chemistry and chemical education. Beside this, the most essential graphical features, unique rendering abilities with magnificent views, splendid visualizing skills, awesome data accessing functionalities, etc. of each of them, and their invaluable roles for studying complex molecules, biomolecules, crystals, and the entire material assemblies as well as for investigating global and local molecular physicochemical properties are presented concisely with the special stresses on their relatively better and comparatively more applicable distinctive attributes explicitl

MaterialVis: Material visualization tool using direct volume and surface rendering techniques

Cataloged from PDF version of article.Visualization of the materials is an indispensable part of their structural analysis. We developed a visualization tool for amorphous as well as crystalline structures, called Material Vis. Unlike the existing tools, Material Vis represents material structures as a volume and a surface manifold, in addition to plain atomic coordinates. Both amorphous and crystalline structures exhibit topological features as well as various defects. Material Vis provides a wide range of functionality to visualize such topological structures and crystal defects interactively. Direct volume rendering techniques are used to visualize the volumetric features of materials, such as crystal defects, which are responsible for the distinct fingerprints of a specific sample. In addition, the tool provides surface visualization to extract hidden topological features within the material. Together with the rich set of parameters and options to control the visualization, Material Vis allows users to visualize various aspects of materials very efficiently as generated by modern analytical techniques such as the Atom Probe Tomography. (C) 2014 Elsevier Inc. All rights reserved

Automated computation of materials properties

Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials. Through the use of sophisticated data analysis techniques, underlying property trends can be identified, facilitating the formulation of new design rules. Such methods require large sets of consistently generated, programmatically accessible materials data. Computational materials design frameworks using standardized parameter sets are the ideal tools for producing such data. This work reviews the state-of-the-art in computational materials design, with a focus on these automated $\textit{ab-initio}$ frameworks. Features such as structural prototyping and automated error correction that enable rapid generation of large datasets are discussed, and the way in which integrated workflows can simplify the calculation of complex properties, such as thermal conductivity and mechanical stability, is demonstrated. The organization of large datasets composed of $\textit{ab-initio}$ calculations, and the tools that render them programmatically accessible for use in statistical learning applications, are also described. Finally, recent advances in leveraging existing data to predict novel functional materials, such as entropy stabilized ceramics, bulk metallic glasses, thermoelectrics, superalloys, and magnets, are surveyed.Comment: 25 pages, 7 figures, chapter in a boo