Physics Department: REU Projects - Condensed Matter Physics/Biophysics

Prof. Badih Assaf
Email: bassaf (at) nd.edu

Quantum materials: optical and electronic properties. Our team specializes in studying the optical and electronic properties of quantum materials. We use various tools that allow us to measure the optical response and electrical conductivity of nanosized quantum materials at various temperatures and under a strong magnetic field. The projects that are available for the summer REU include Raman spectroscopy measurements on 2D quantum materials, infrared absorption spectroscopy measurements on topological insulator thin films, and magnetometry measurements on magnetic quantum material thin films.

Prof. Margaret Dobrowolska-Furdyna and Prof. Jacek Furdyna
Email: mdobrowo (at) nd.edu
Email: furdyna (at) nd.edu

The available projects involve the study of properties of ferromagnetic semiconductors in the form of thin layers and multilayers. As an example, the well-known semiconductor GaAs in which a fraction of Ga atoms is replaced by the magnetic ion Mn becomes a ferromagnet. Such novel structures are fabricated by the process of Molecular Beam Epitaxy, where they can be grown with atomic precision. Some of our projects involving these materials include electrical transport measurements in magnetic field, studies of magnetic properties using superconducting quantum interference device (SQUID), optical studies, and magnetic resonance.

Prof. Morten Eskildsen
Email: eskildsen (at) nd.edu

The research of our group is focused on the study of vortices in superconductors and how they reflect on the detailed nature of the superconducting state. More information can be found at our web site: www.nd.edu/~vortex.

The REU project will involve data analysis of results from small-angle neutron scattering (SANS) experiments complemented with molecular dynamics simulations. Scheduling permitting it may also include the participation in a SANS experiment at a domestic or international neutron facility.

Prof. Sylwia Ptasinska
Email: sylwia.ptasinska.1 (at) nd.edu

Low-energy electron interactions with biomolecules. Abundance of fundamental and applied cross-disciplinary research areas, involving low energy electrons (LEEs), have experienced a significant growth in recent years. Specific reactions, induced by LEEs, are relevant to many fields: plasma, nanolithography, dielectric aging, radiation processing and waste management, astrobiology, planetary and atmospheric chemistry, radiobiology, radiotherapy, and explosive detection. The LEE interactions are also relevant to many experimental techniques in which samples are probed by radiation (e.g., synchrotron studies). It is generally accepted that electrons with energies less than 15 eV are considered “low energy”. In recent years our group focused on LEE interactions with DNA and its constituents. It has been shown that nucleobases play an essential role in radiation damage to DNA by acting as antennas for capturing the LEEs. However, other macromolecules within the cell (e.g., cell membrane or proteins) may be susceptible to radiation damage.

Thus, in this research project, a student will be involved in revealing, identifying and quantifying all major electron induced fragmentation patterns of different biologically relevant molecules in the gas phase.
 

Prof. Dervis Can Vural
Email: dvural (at) nd.edu

We are a theoretical group that works on the interface between statistical mechanics and biology. Currently we focus on three categories of problems: First, evolution of strongly interacting populations, particularly when stochastic factors are as influential as selection events. For example, we would like to understand how an ecological web gets mingled, or what role phenotypic diversity plays in cancer. Secondly, we are interested in failure and death: We study how complex systems respond to the malfunction of one or few crucial components, and how malfunctions spread. Thirdly we are interested in “inverse problems”, particularly in the context of complex materials and networks. This class of problems involves obtaining equations and assumptions directly from experimental behavior, rather than the other way around. We are particularly excited about cases where the data is consistent with multiple conflicting assumptions!