Udo Becker

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Professor Becker leads an interdisciplinary group to understand problems in surface geochemistry and computational mineralogy, thus there are research opportunities in fields ranging from experimental approaches and computational modeling of actinide geochemistry (U immobilization in the environment, actinide-containing solids under extreme pressure, temperature, and radiation, U/Np/Pu redox processes) to carbonate biomineralization. Other research includes calculating redox processes (including resolving individual kinetic barriers that control kinetics) carbonate and phosphate biomineralization (from environmental applications to processes on teeth). As a part of Mineralogy and Materials Science Research Group, Becker’s group  interacts with Radiation Effects and Radioactive Waste Management group, Michigan Geomicrobiology group, Electron Microbeam Analysis Laboratory (EMAL) and Mineral Physics group.

Band decomposed charge density associated with the defect state at -0.7eV, introduced by Pu occupying the A site in Ca3Zr2(FE2Si)O12.

Band decomposed charge density associated with the defect state at -0.7eV, introduced by Pu occupying the A site in Ca3Zr2(FE2Si)O12.

 

Brian Arbic

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Brian Arbic is a physical oceanographer. His group focuses on global modeling of internal tides and gravity waves, with growing interests in air-sea interactions and modeling of surface tides and their role in Earth System processes over geological time scales.  Other interests include the dynamics and energy budgets of oceanic mesoscale eddies (the oceanic equivalent of atmospheric weather systems), tsunamis, and paleotsunamis. His group uses in-situ and remotely sensed observations, idealized models, and realistic models.  He collaborates widely with scientists in the US and abroad, and his projects include collaborations with scientists at large modeling centers, such as the US Naval Research Laboratory (NRL), NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL), DOE’s Los Alamos National Laboratory (LANL), Europe’s Mercator Modeling Center, and NASA’s Jet Propulsion Laboratory (JPL).  He participates in NASA missions, including the Surface Water Ocean Topography (SWOT) mission, the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) mission, and the Ocean Surface Topography mission.  Arbic has been a member of the U-M ASC STEM Africa committee since 2012.  He is the principal founder of the Coastal Ocean Environment Summer School in Ghana (https://coessing.org), is the lead on the concept note for “An Ocean Corps for Ocean Science” (https://globaloceancorps.org), and a co-lead on the concept note “EquiSea:  The Ocean Science Fund for All” (https://equisea.org).

The surface expression of the M_2 principal lunar semidiurnal internal tide — the tide that arises due to the stratification of the ocean. The top panel shows analysis of satellite altimetry data, while the bottom shows results from HYCOM, run by collaborators at the Naval Research Laboratory. (Shriver, et al 2012)

The surface expression of the M_2 principal lunar semidiurnal internal tide — the tide that arises due to the stratification of the ocean. The top panel shows analysis of satellite altimetry data, while the bottom shows results from HYCOM, run by collaborators at the Naval Research Laboratory. (Shriver, et al 2012)

Gregory J. Dick

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Microbial communities host incredible biological diversity that is encoded at the genomic level. The recent application of high-throughput DNA-sequencing technologies to these communities provides exciting new insights into uncultured organisms while presenting new computational challenges associated with massive and multidimensional data. Professor Dick’s laboratory utilizes such metagenomic and metatranscriptomic approaches to problems in environmental and geological science, addressing questions such as: How do microorganisms control elemental cycles in deep-sea hydrothermal systems?  How did microbial processes influence the timing of Earth’s oxygenation? Computational applications focus on metagenomic and metatranscriptomic assembly, comparative genomics, and “binning,” whereby fragmentary metagenomic sequences of unknown origin are assigned to organisms on the basis of genome signatures of nucleotide composition.

An emergent self-organizing map of genome signatures (tetranucleotide frequency) from a microbial community at the Mid-Cayman Rise (5,000 meters water depth, Caribbean). This approach allows computational reconstruction of genome sequences from complex microbial communities.

An emergent self-organizing map of genome signatures (tetranucleotide frequency) from a microbial community at the Mid-Cayman Rise (5,000 meters water depth, Caribbean). This approach allows computational reconstruction of genome sequences from complex microbial communities.

Mark Flanner

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Professor Flanner’s research ambitions lie in understanding large-scale energy transport in Earth’s climate system, with particular focus on the roles of the cryosphere (including seasonal snow cover, glaciers, and sea-ice) and atmospheric aerosols. To approach these topics, his research group applies and develops computationally demanding models of Earth’s global climate system. The team also analyzes large datasets generated by climate models and satellite measurements, spanning numerous dimensions of space, time, spectrum, and state.  Flanner’s group strives to improve climate models by developing numerically efficient algorithms for microphysical processes that occur on scales too small to represent explicitly in global climate models, such as crystal growth in snowpack and interaction of sunlight with aerosols and ice crystals. The group also informs climate mitigation discussions by applying climate models to estimate the perturbations to Earth’s radiation field caused by emissions of short-lived pollutants from different regions and sectors.

Volumetric absorption of solar energy in snowpack, simulated with the Snow, Ice, and Aerosol Radiative (SINCAR) model, shown as a function of wavelength and depth beneath the top of the snow column.

Volumetric absorption of solar energy in snowpack, simulated with the Snow, Ice, and Aerosol Radiative (SINCAR) model, shown as a function of wavelength and depth beneath the top of the snow column.