U.S. Congressman Erik Paulsen, who represents Minnesota's 3rd District, visited the LCSE-MSI Visualization Laboratory on September 26, 2011. Rep. Paulsen was on campus to meet with officials from the Office of Technology Commercialization and a start-up company spun out of the University to talk...
The University of Minnesota announced recently that discoveries by University researchers were used to launch 12 startup companies in fiscal year 2012. This is a record number. You can read the news story describing the companies on the Office of the VP for Research (OVPR) Business blog . Several...
posted November 20, 2013 Last weekend, MSI staff members participated in the College of Science and Engineering’s 2013 Math and Science Family Fun Fair . The Fair was held on Saturday, November 16 in Coffman Memorial Union. This annual event is designed for young people to learn about science,...
posted on August 21, 2014 The Office of the Vice President for Research recently announced that a record 15 start-up companies based on University inventions were formed in Fiscal Year 2014, which ended on June 30, 2014. Several of these start-ups are headed up by MSI Principal Investigators. These...
The University of Minnesota Materials Research Science and Engineering Center (MRSEC) has received a $17.8 million grant from the National Science Foundation . Over a dozen MSI Principal Investigators are participating faculty at the Center (see list below). The mission of the Center is to enable “...
Zeolites are porous silicate materials that are used in gas separation, catalysis, and other applications. Several MSI Principal Investigators are involved in a project to develop zeolite nanosheets—plate-like crystals—that are very desirable because of their packing and processing advantages. In...
<p> </p> <p><strong>The Phase Diagram of QCD</strong></p> <p>The long-term goal of this project is to determine from first principles the properties of quantum chromodynamics (QCD) as a function of the temperature and the densities of the u, d, and s quarks. A similar effort from experimental physicists is under way at particle accelerators RHIC and LHC, by colliding heavy ions. Theoretical progress is hampered by the “sign problem”: the fermion determinant becomes complex when the quark density (or equivalently the quark chemical potential) is non-zero, which makes the usual Monte Carlo sampling impossible. These researchers have been pursuing, very successfully, the strategy of making the chemical potential mu imaginary. Positivity of the determinant is restored, and standard Monte Carlo can be used. The imaginary-mu results can be analytically continued to real mu. Moreover, the critical points found at imaginary mu imply scaling laws extending to real mu. Thus, the researchers want to constrain the real-mu properties, by pinning down the phase diagram for imaginary-mu, accumulating more knowledge by letting the quark masses take arbitrary values. These simulations of lattice QCD with imaginary chemical potential are quite standard. The researchers are determining the critical surfaces and tricritical lines in the extended phase diagram by well-established finite-size scaling techniques. Computing resources are absorbed in the simulation of large systems near criticality.</p>
<p> </p> <p><strong>Algorithms and Analysis for Natural Systems</strong></p> <p>These researchers are involved in two projects requiring large-scale computation. Both projects are developing new algorithms for understanding natural systems and are applying those algorithms to prominent real-world problems.</p> <p> </p> <p>In the first project, the researchers are continuing their development work on Order-1 algorithms for large-scale, individual-based, equation-free modeling in ecology, epidemiology, and economics, and applying those agorithms to a whole-nation test case that addresses the unexpected resurgence of tuberculosis in recent decades. These Order-1 algorithms cover time and group management and run at a fixed speed regardless of whether the simulation encompasses sixty individuals or sixty-million. That allows the researchers to extend their investigations beyond what has normally been possible.</p> <p> </p> <p>The second project is in its early stages. The researchers are developing parallel algorithms for processing fine-scale elevation data of the earth’s surface in order to identify new watershed configurations. They are applying LIDAR data at one-square-meter resolution in a regional test case to learn how to decouple pollutant-laden waters in the artificial watershed of drain tiles and ditches from fresh waters in the natural watershed of lakes, ponds, rivers, and streams. </p>
<p> </p> <p><strong>Modeling Countercurrent Shear in Practical Devices</strong></p> <p>These researchers are extending their previous MSI-supported work that looked into adding a counterblowing device to a backward facing step. The simulations to date modeled flow over a backward facing step using ANSYS CFX under isothermal conditions. At the sudden expansion a small device was added through which air was blown in opposition to the primary stream. The additional shear was sufficient to activate a global instability and dramatically alter the mixing of the well-established backward facing step. Backward facing step flow is a geometry used to model a RAM jet combustor and an active area of research by our group and others. The simulations and experiments to date have shown counterblowing to be a good candidate to increase burning rates. Experiments are underway to quantify the degree to which the blowing can improve combustion and provide benchmark data. The researchers are simulating the counterblowing backward facing step with combustion added. This work builds on existing computer simulations and continues to be two-dimensional and use both laminar and turbulence models. The researchers will initially use simple combustion models and add complexity as time and resources allow. </p>
<p> </p> <p><strong>Population Pharmacokinetic Modeling of Anticancer and Other Therapeutic Agents</strong></p> <p>This population pharmacokinetic modeling project is being conducted in support of completed and ongoing clinical trials conducted by the Mayo Clinic Comprehensive Cancer Center. Pharmacokinetic data obtained from preclinical and Phase 0–III studies are utilized to develop comprehensive compartmental models that describe the pharmacokinetic behavior of investigational drugs and their metabolites. MSI resources are used for population-based analyses of complex models and large datasets as the underlying calculations are computationally intensive and require the simultaneous use of several processors. The population-based models are developed through the use of the software program NONMEM and are utilized to quantify the pharmacokinetic variability exhibited between study subjects. Depending on the available data, correlations between pharmacokinetics and pharmacodynamic outcomes will also be investigated. Taken as a whole, the intent of this investigation is to utilize the population pharmacokinetic modeling approach to ascertain the influence of clinically relevant and measurable factors on the pharmacokinetics and pharmacodynamics of anticancer and other therapeutic agents with the ultimate goal of improving drug dosing guidelines on the individual patient level.</p>