The LONI Institute staff from the six partner sites conducts research primarily in materials science, biology and computational sciences.
This area will focus on developing new classes of computational materials that can be used for pharmaceuticals, large-scale modeling and other scientific applications.
→ Materials Theory, Modeling, Computation & Analysis - this area will pair fundamental physics concepts with computational sciences to create new approaches for designing computational materials and will provide an improved model for how theoreticians and computational scientists can collaborate.
→ Surfaces, Interfaces and Nanostructures - computational studies will help to unravel the structured, electronic and other physical properties of low-dimensional materials and to develop novel techniques for developing surface structures.
→ System On-Chip Design and Integration - this area will develop pre-fabricated designs and simulation sensors to aid LI staff in their work.
→ Computational Modeling of Mechanical Behavior of Polymer Nanocomposites - investigating interfacial, bulk and composite performance properties requires advanced modeling and computer simulation techniques at several levels. Such techniques will be developed in this area.
→ Micro Electro-Mechanical Systems - this area will develop a broad range of computational capabilities to aid effective polymer design and synthesis.
→ Polymer Design and Synthesis - this area will use computational approaches to complex materials problems. One key research area will be developing a framework to understand and control nano-structural material properties.
→ Polymer Rheology and Mixed-Scale Flow - this area will conduct numerical modeling and simulation of manufacturing processes.
→ Polymer (soft-matter) imaging - this area will be one of a small, select group of researchers around the world who focus on aiding polymer simulation (see above.)
This area will focus on applying computational sciences to studying biological processes in the human body as well as in other organisms.
→ Metagenomics - this area will provide the resources needed for effective examination of genomes from an entire ecosystem.
→ Ciliary Motion - this area will develop large-scale computational fluid dynamics simulations to further understanding of the biological processes of hair-like appendages in the body.
→ Pulmonary Mechanics - this area will develop computational science methods to extend current studies of airway processes in the body to incorporate realistic bio-physical properties.
→ Computational Biofluid Mechanics - this area will work with computational materials teams to make progress in studying/simulating fluid flow in the body.
→ DNA-based Detection - this area will develop cyberinfrastructure and computing workflow tools to aid design of new methods for detection and quantification of new organisms in water samples.
→ Phlogenomic Protein Identification - this area will develop computational methods of detecting and analyzing new proteins found in analysis of new species.
→ Understanding the Infection Mechanism - this area will expand on computational efforts to simulate the HIV virus' effect on bodily cells for better understanding of how the virus spreads.
This area will focus primarily on developing novel approaches for data retrieval, storage, archiving and simulation. The tools developed for data in this area will greatly aid the applications in the computational materials and biology groups.
→ Cactus Toolkit for Multi-Scale Simulations - this area will develop Cactus-based toolkits to better aid biological and materials science research.
→ SAGA - this area will develop a new set of Cactus "thorns," using the SAGA libraries that run multi-physics, multi-scale codes in any desired configuration, to support the scientific goals of the biologists and materials scientists.
→ Distributed Data Management - this area will develop more effective data management tools to improve how scientists can perform their research. Innovative data distribution systems also will facilitate rapid sharing of information among scientists.
→ Scheduling Services - this area will improve data scheduling through LONI to ease collaboration between different scientific research groups.
→ Algorithms for Medical Data Integration, Mining and Discovery - this area will develop inter-operable middleware and associated algorithms for improved medical data integration, mining and storage to aid the LONI Institute's biomedical applications.