Ajay Limaye

Drishti, a volume exploration and presentation tool

Among several rendering techniques for volumetric data, direct volume rendering is a powerful visualization tool for a wide variety of applications. This paper describes the major features of hardware based volume exploration and presentation tool - Drishti. The word, Drishti, stands for vision or insight in Sanskrit, an ancient Indian language. Drishti is a cross-platform open-source volume rendering system that delivers high quality, state of the art renderings. The features in Drishti include, though not limited to, production quality rendering, volume sculpting, multi-resolution zooming, transfer function blending, profile generation, measurement tools, mesh generation, stereo/anaglyph/crosseye renderings. Ultimately, Drishti provides an intuitive and powerful interface for choreographing animations.

Digital Core Laboratory: Properties of reservoir core derived from 3D images

A facility for digital imaging, visualizing and calculation of reservoir rock properties in three dimensions (3D) is described. The facility includes a high resolution X-ray micro-computed tomography system capable of acquiring 3D images made up of 2000 voxels on core plugs up to 5 cm diameter with resolutions down to 2 μm. Subsets of four sandstone reservoir core plugs (5 mm in diameter) from a single well of a producing gas field are imaged in this study. The four cores exhibit a broad range of pore and grain sizes, porosity, permeability and mineralogy. Computational results made directly on the digitized tomographic images are presented for the pore size distribution, permeability, formation factor, NMR response and drainage capillary pressure. We show that data across a range of porosity can be computed from the suite of 5 mm plugs. Computations of permeability, formation factor and drainage capillary pressure are compared to data from a comprehensive SCAL laboratory study on 70 cores from the same well. The results are in good agreement. Empirical correlations between permeability and other petrophysical parameters are made and compared to common correlations. The results demonstrate the potential to predict petrophysical properties from core material not suited for laboratory testing (e.g., drill cuttings, sidewall core or damaged core) and the feasibility of combining digitized images with numerical calculations to predict properties and derive correlations for individual reservoir rock lithologies.

Developing a virtual materials laboratory

Tomographic imaging can now be routinely performed over three orders of magnitude in length scale with correspondingly high data fidelity. This capability, coupled with the development of advanced computational algorithms for image interpretation, three-dimensional visualization, and structural characterization and computation of physical properties on image data, allows for a new numerical laboratory approach to the study of real complex materials: the Virtual Materials Laboratory. Numerical measurements performed directly on images can, in many cases, be performed with similar accuracy to equivalent laboratory measurements, but also on traditionally intractable materials. These emerging capabilities and their impact on a range of scientific disciplines and industry are explored here.

Elastic and transport properties of cellular solids derived from three-dimensional tomographic images

We describe a three-dimensional imaging and analysis study of eight industrial cellular foam morphologies. The foam morphologies were generated by differing industrial processing methods. Tomograms are acquired on an X-ray micro-computed tomography facility at scales of approximately equal to at resolutions down to 7 μm. The image quality is sufficient in all cases to measure local structure and connectivity of the foamed material, and the field of view large enough to calculate a range of material properties. Phase separation into solid and porous components is straightforward. Three-dimensional structural characteristics are measured directly on the porous and solid phases of the images. A number of morphological parameters are obtained, including pore volume-to-surface-area ratio, connectivity, the pore and solid phase size distributions defined by maximal sphere openings and chord length measurements. We further calculate the pore size distribution associated with capillary pressure via simulating of mercury drainage on the digital images. The binarized microstructures are used as a basis for calculations of transport properties (fluid permeability, diffusivity and thermal conductivity) and elastic moduli. From the data, we generate property–porosity relationships for the range of foam morphologies imaged and quantitatively analyse the effects of porosity and microstructure on the resultant properties of the foams. We compare our numerical data to commonly used theoretical and empirical property–porosity relationships. For thermal conductivity, we find that the numerical results agree extremely well with an empirical expression based on experimental data of various foams. The upper Hashin–Shtrikman bound also provides an excellent prediction of the data across all densities. From simulation of the diffusivity, we can define the tortuosity of the pore space within the cellular solid. We find that different processing methods lead to strong variations in the tortuosity of the pore space of the foams. For elastic properties, our results show that for the Young modulus, E, both the differential effective medium theory and the classical correlation give a good correlation. Assuming a constant Poissons ratio leads to reasonable agreement. The best correlation for is given by assuming a slight variation in as a linear function of porosity. The permeability of the foams varies over three orders of magnitude. Correlations for permeability based on the classical Kozeny–Carman equation lead to reasonable agreement, except at the lowest porosities. Permeability estimations based on mercury porosimetry give excellent agreement for all foams.

Imaging honey bee brain anatomy with micro-X-ray-computed tomography

Technologies for imaging in three dimensions are greatly desired by researchers in many biological disciplines. However, when imaging small animals such as invertebrates, the achievement of satisfactory spatial resolution and adequate contrast between tissues often requires the use of expensive and time-consuming procedures. Micro-X-ray-computed tomography (muCT) is a convenient technique which is finding greater use alongside conventional microscopies. Staining with heavy metal salts, such as osmium tetroxide improves imaging in muCT, and allows visualization of the 3D structure of the honey bee brain undistorted within the intact head capsule. We obtained detailed information about the morphology of the different brain compartments and were able to show their orientations, relative to each other, within the head capsule. This technique offers a significant improvement in resolution, time, and expense for the quantitative, three-dimensional analysis of developing bee brain centers. In this article, we introduce a rapid, high-resolution, and inexpensive technique for the three-dimensional visualization of different compartments of the honey bee brain. A detailed discussion of the honey bee brain anatomy is provided, demonstrating that muCT, with osmium staining, can indeed visualise these structures. Hence, our results show that muCT is ideally suited for researchers who are interested in the 3D visualization of small invertebrate brains.

A general parallel solution to the integral transformation and second‐order Mo/ller–Plesset energy evaluation on distributed memory parallel machines

We present here a parallel algorithm for four‐index (integral) transformation and second‐order Mo/ller–Plesset (MP2) energy evaluation, primarily designed for multiple instruction multiple data (MIMD) machines. It is a general algorithm designed to work with equal efficiency on any inhomogeneous network and any architecture. This algorithm works with only a twofold redundancy in integral storage, whereas some previously reported strategies demand a fourfold redundancy. The parallel transformation and sorting algorithm has been implemented on a 128 node inhomogeneous ring network, 64 of the processors being about 30%–40% slower. The present parallel scheme is seen to perform excellently in integral transformation processes even in such an inhomogeneous environment due to dynamic load balancing strategies. It has been found that integral transformation along with MP2 energy evaluation takes typically 120–200 min for molecules with 80–90 atomic orbitals. However, time taken for such systems reduces to ∼30–60...

Development of a restricted Hartree-Fock program INDMOL on PARAM: a highly parallel computer

Parallelization of the SCF method for closed‐shell molecules on the highly parallel transputer‐based system PARAM is described. The parallelization has been implemented on three different hardware and software environments: (1) a network of bare 64 transputers; (2) configuration 1 plus a back‐end file system (BFS); and (3) configuration 2 with one INTEL i860 processor. The evaluation of electron repulsion integrals (ERIs) and setting up of the Fock matrix is carried out in parallel on 64 nodes using minimal communication strategies. A good load balance is achieved for ERI evaluation with the help of bounds, local symmetry features, and the shell concept, as well as a data randomization technique, resulting into almost linear speedup (for ERI evaluation). In configurations 2 and 3, BFS is used for parallel storage and retrieval of ERIs. Further, in 3 matrix operations are implemented as remote procedure calls on the i860 processor. Routine techniques of level shifting and extrapolation are used for accelerating SCF convergence. The resulting package, INDMOL, has been tested for some randomly selected molecules having up to 255 contractions. Using configuration 3, a factor of 2 to 5 in computation time is obtained over 1, for the systems for which the ERIs cannot be stored in the distributed core memory. In summary, a heterogeneous system, as in configuration 3, can indeed be optimally exploited for programming peculiar diverse requirements of the SCF procedure.

Investigation of microstructural features in regenerating bone using micro computed tomography.

We illustrate some of the uses of micro-computed tomography (micro-CT) to study tissue-engineered bone using a micro-CT facility for imaging and visualizing biomaterials in three dimensions (3-D). The micro-CT is capable of acquiring 3D X-ray CT images made up of 20003 voxels on specimens up to 5 cm in extent with resolutions down to 2 μm. This allows the 3-D structure of tissue-engineered materials to be imaged across orders of magnitude in resolution. This capability is used to examine an explanted, tissue-engineered bone material based on a polycaprolactone scaffold and autologous bone marrow cells. Imaging of the tissue-engineered bone at a scale of 1 cm and resolutions of 10 μm allows one to visualize the complex ingrowth of bone into the polymer scaffold. From a theoretical viewpoint the voxel data may also be used to calculate expected mechanical properties of the tissue-engineered implant. These observations illustrate the benefits of tomography over traditional techniques for the characterization of bone morphology and interconnectivity. As the method is nondestructive it can perform a complimentary role to current histomorphometric techniques.

An x-ray tomography facility for quantitative prediction of mechanical and transport properties in geological, biological, and synthetic systems

A fully integrated X-ray tomography facility with the ability to generate tomograms with 20483 voxels at 2 micron spatial resolution was built to satisfy the requirements of a virtual materials testing laboratory. The instrument comprises of a continuously pumped micro-focus X-ray gun, a milli-degree rotation stage and a high resolution and large field X-ray camera, configured in a cone beam geometry with a circular trajectory. The purpose of this facility is to routinely analyse and investigate real world biological, geological and synthetic materials at a scale in which the traditional domains of physics, chemistry, biology and geology merge. During the first 2 years of operation, approximately 4 Terabytes of data have been collected, processed and analysed, both as static and in some cases as composite dynamic data sets. This incorporates over 300 tomograms with 10243 voxels and 50 tomograms with 20483 voxels for a wide range of research fields. Specimens analysed include sedimentary rocks, soils, bone, soft tissue, ceramics, fibre-reinforced composites, foams, wood, paper, fossils, sphere packs, bio-morphs and small animals. In this paper, the flexibility of the facility is highlighted with some prime examples.

Comparison of enzyme polarization of ligands and charge‐transfer effects for dihydrofolate reductase using point‐charge embedded ab initio quantum mechanical and linear‐scaling semiempirical quantum mechanical methods

Using quantum mechanical (QM) methods, we investigated the dependence of a number of factors on the polarization by the enzyme dihydrofolate reductase (DHFR) of its ligands—the substrates, folate and dihydrofolate, and the cofactor NADPH—and evaluated the implications for facilitation of the enzymic reductions. Two quite different levels of QM description of the biomolecular system were used. State‐of‐the‐art ab initio QM calculations of the ligands were performed with the bulk DHFR environment modeled using atom‐centered point charges. At the other extreme, semiempirical AM1 QM calculations using the linear‐scaling Mozyme formalism incorporated in MOPAC2000 allowed for consistent treatment of the 3000‐atom system of both enzyme and bound ligands. The study considered the effects of a number of factors on the polarization, including: (i) different levels of ab initio QM treatment (HF, MP2, DFT) and basis sets; (ii) different sets of molecular mechanics (MM) point charges in representing the bulk enzyme; (iii) inclusion of the bulk enzyme environment as either point charges in the ab initio calculations, or explicitly in the semiempirical calculations; (iv) ab initio QM calculations of substrate and ligand together (combined system) or separately (noncombined system); (v) degree of charge transfer between substrate and cofactor, and, for the semiempirical calculations, between bound ligands and enzyme; (vi) polarization of the enzyme in the semiempirical calculations; (vii) differences in the behavior of folate and dihydrofolate; and (viii) DHFRs from different species (E. coli and human) and different X‐ray structure coordinate sets from the same species. Polarization was analyzed mainly by differences in point‐charge distributions between gas‐phase and bound ligands at the level of complete ligands, subcomponents of ligands (residues), and individual atoms in the pterin and nicotinamide rings involved in the DHFR reactions, but some electron density differences were also calculated. Consistent with our preliminary study (Greatbanks et al., Proteins 1999, 37, 157), and earlier work by Bajorath et al. (Proteins 1991, 9, 217; 11, 263) for noncombined ligand systems, the DFT calculations showed an unrealistically large dipolar character for individual ligands compared with HF and MP2 results and anomalously large charge transfer to folate from NADPH in combined calculations, which were not shown by the HF or AM1 results. The origin of this behavior is in the representation of the gas‐phase anions (the substrates are dianionic and NADPH is tetraanioinic), with the point‐charge enzyme‐embedded calculations showing polarization similar to the HF results. The analysis highlights that successful modeling of the polarization properties depends on accurate representation of both the gas‐phase and enzyme‐bound electronic structures of the QM region. For both folate and dihydrofolate at the HF and MP2 levels, changes in density from enzyme binding in the region of the reducible bonds (N8C7 for folate, C6N5 for dihydrofolate) is small, with the bulk of the polarization taking place in the N2C2N3 region near the Asp27 (or Glu30) active‐site group. Polarization at C7 for folate and C6 for dihydrofolate is negative (i.e., does not favor hydride‐ion transfer), whereas the trend at N8 for folate, but not at N5 for dihydrofolate, favors protonation. For the Mozyme results, the substrate pterin‐ring polarization trends are similar, and also with negligible charge transfer to NADPH, and only a very small charge transfer to the enzyme. For NADPH, the HF, MP2, and Mozyme results indicate charge polarization on binding to the enzyme at the active carbon (C4) of the nicotinamide ring is favorable for hydride‐ion transfer (i.e., slightly more negative), with the active hydrogen (H4) also being more negative for the HF and MP2 results. For all methodologies, the nonactive hydrogen (H4′) becomes significantly more positive, which would reduce its potential for transfer. The Mozyme results show a net loss to the enzyme of ∼0.3 electrons, mostly from NADPH, which is strongly localized in the vicinity of the substrate glutamate and NADPH diphosphate and 3′‐phosphate groups.