A basic building block of life is a cell. It hosts DNA and myriad other complex molecules such as proteins, lipids, and RNA species. How these molecules arrange in space and time in a coordinated manner to make a cell a living entity is yet unclear. Equilibrium statistical physics can explain some of their organization, but non-equilibrium processes also play a significant role and is a hallmark of life. This summer project will combine state-of-the-art microscopic measurements and image analysis, including AI-based methods, to understand how DNA is organized in a bacterial cell. This knowledge is important in designing next-generation antibacterial drugs and synthetic cells.
Advisor: Prof. J. Mannik
https://volweb.utk.edu/~jmannik/index.html
The EPIC detector is a proposed detector at the electron-ion collider. The forward hadronic calorimeter must be robust to high radiation levels and able to measure jets with high precision. Students will help assemble and test modules of the forward hadronic calorimeter for EPIC for use in a test beam. This work will take place at Oak Ridge National Laboratory.
Advisor: Professor Christine Nattrass
A new facility to measure the beta decay of laser polarized atomic nuclei (beta-NMR) was recently commissioned at the ISOLDE facility, CERN. This technique allows for precise measurements of nuclear properties such as its magnetic moment or charge radius. A powerful variant of beta-NMR uses radiation detectors to “tag” and identify specific nuclear excitations. In this project we will utilize gamma- and neutron-tagged beta-NMR to explore the anomalous nuclear structure of 47,49K. We will use CERN’s ROOT analysis software, as well as python and Julia code, to construct their decay strength distribution and compare it with state-of-the-art nuclear models.
Advisor: Professor Miguel Madurga
If you like to have hands-on experience with experiments looking for mysterious neutrinos you are welcome to join our summer activities. Most of the work will be at the ORNL. Two experiments you can be involved in are: COHERENT experiment to study neutrino interactions and LEGEND, neutrino less double beta decay experiment.
Advisor: Professor Yuri Efremenko
Photoelectron Diffraction is a methodology of photoelectron spectroscopy that
allows the determination of the local crystallographic arrangements around an
emitting atom. In one of our research endeavor,
it would be highly important to be able to determine the local crystal structure
around Fe and Se atoms in FeSe layers grown epitaxially on oxide substrates. These are systems that revealed unconventional
superconductivity, with superconducting transition temperatures much higher than
those found in bulk FeSe. The determination of the crystallographic environment
in FeSe monolayers is fundamental for a correct description of their electronic
structure.
We are looking for a highly motivated student who can run simulations with a
dedicated program called EDAC (Electron Diffraction in Atomic Clusters). The
student will have the chance to learn fundamental concepts in solid state
physics, crystallography, and to apply notions of quantum mechanical scattering
to photoelectrons.
Advisor: Professor
Norman Mannella
Angle Resolved Photoemission (ARPES) is one of the premiere techniques that
allow direct measurements of the electronic structure of materials, providing a
link between the macroscopic properties at the heart of the materials
functionality and the microscopic degrees of freedom. With
energy resolutions of a few meV, momentum resolutions of better than 0.5% of a
typical Brillouin zone size, state-of-the-art Angle Resolved Photoemission (ARPES)
experiments are now able to directly reveal the microscopic, many-body
interactions in the single-particle spectral function, making it extremely
powerful in addressing central issues in the physics of complex electron
systems.
Yet, to date, the analysis of ARPES data in multi-band systems has been severely
hampered by the fact that signals derived from different bands overlap,
resulting in broad spectral features that are impossible to resolved. We are looking for a highly motivated student
who can implement machine learning methods for the extraction of bands
dispersion. The student will have the chance to
learn fundamental concepts in solid state physics, crystallography, and to apply
notions of quantum mechanics.
Advisor: Professor
Norman Mannella
The CMS experiment at CERN will start colliding protons again this year, opening up new opportunities to search for physics beyond the Standard Model. Students will have an opportunity to help design these searches, studying triggers that make sure our detectors capture the particles we’re most interested in. We also have projects related to the design of future LHC detectors, focusing on an upgrade to the CMS tracker. In addition, there are opportunities in the group to influence where our field may head next by doing studies for a future muon collider. Projects will involve programming, so students are encouraged to build familiarity with python and a unix terminal in advance of the summer.
Advisor: Professor Tova Holmes
We use a scanning tunneling microscope (STM) to probe various kinds of quantum materials in the atomic scale. By analyzing the atomic and electronic structure acquired by STM, it is possible to reveal the novel quantum states in these materials. In this project, students will be involved in three tasks: (1) use STMs to acquire atomic structure of materials; (2) analyze STM data with advanced statistic tools to extract hidden orders; and (3) automate the STM operation by combining coding for remote operation and machine learning-based methodology.
Advisor: Professor Wonhee Ko
Dark Matter is one of the biggest puzzles of the modern physics. It is known
definitely that Dark Matter exists in the universe. It is even more abundant
than the regular matter. However, the nature of Dark Matter is not understood.
This research project will be focused on the design of a new planned experiment
for detection of Dark Mirror neutrons and on the analysis of experimental data
from a previous experiment.
To be learned: particle oscillations in two-level Quantum Mechanical system,
physics of neutron detectors, McStas neutron transport software, Monte-Carlo
calculation methods, statistics, data analysis and presentations of the results.
Student with computing experience (Python, C++, FORTRAN) are welcome to contact
Prof. Yuri Kamyshkov for an interview.
Advisor: Professor Yuri Kamyshkov
DNP is the process aligning nuclear spins in a specific direction (typically
that of a magnetic field) in a solid material. In nuclear physics, this is
desirable for a target of scattering experiments as it increases the luminosity
- physics interactions of interest. In biology, DNP is increasingly utilized to
increase the signal to noise ratio in NMR spectroscopy studies, and is now being
used at ORNL to enhance the signal from protein crystal samples, with the
specific goal of utilizing the spin dependent scattering of neutrons from
hydrogen to gain a full atomistic understanding ofprotein structure.
We will be installing and operating a dynamic nuclear polarization (DNP)
characterization apparatus at UT to benchmark spin polarizable materials,
standardize the preparation of such materials, and develop techniques to
maximize the nuclear polarization. This effort addresses the growing need across
several fields for samples with high nuclear polarization. The samples include
macromolecular crystals for use in neutron beams (biological and materials
science), or deuterated materials to use as targets for electron beams (nuclear
physics).
Advisor: Professor Nadia Fomin
All eukaryotic cells contain a cytoskeleton. A major component of the
cytoskeleton is actin, a semi-flexible biopolymer that can assemble and
disassemble. The long-term goal in
the research field of the actin cytoskeleton is to derive a predictive framework
to elucidate how the organization and activity of the cytoskeleton arise from
the mechanics, dynamics, and cooperative interactions of individual components.
It remains challenging to achieve this goal because the actin cytoskeleton is
an active system driven far from equilibrium. The summer fellow will begin work
on cytoskeleton simulations, computationally modeling and characterizing the
actin cytoskeleton's organization under applied external forces, and identifying
the force-feedback mechanism in the model system.
Advisor: Professor Yuqing Qiu
The explosions of massive stars are mediated by neutrinos, and the quantum
mechanical processes that drive them to change flavor are a significant
challenge for the theory of how stars explode. We
have a machine learning model that predicts how this flavor change proceeds, but
we need to improve it before it is useful in dynamical supernova simulations.
The student on this project will run local
simulations of neutrino flavor transformation and use it to further train the ML
model. In addition, the student will make
enhancements to the ML model to allow it to make better predictions. A background in Python or coding in general is required, and a
background in machine learning would be a large asset.
Advisor: Professor
Sherwood Richers
The oxygen you breathe, the calcium in your bones and about half of the iron in your blood were formed in the deaths of massive stars as core-collapse supernovae. We model these explosions in two and three dimensions using supercomputers as the Oak Ridge Leadership Computing Facility and other computing facilities. Many of the most important observations, which can tell us if our models are correct, depend on the new atomic nuclei that are produced in the explosion. You will assist in running our nucleosynthesis calculations and analyzing the results so that we may better understand the nuclear contributions from these exploding stars.
Advisor: Professor Raph Hix
The detection of neutrons in radioactive decay and reaction experiments is
one of the big challenges in studies of exotic nuclei. We have constructed
a pixelated detector used for decay studies at the CERN ISOLDE facility and we
are in the process of development a new generation detector for FRIB
https://frib.msu.edu/. We can offer a
variety of projects ranging from the development of GEANT 4 simulation to the
construction and characterization of prototypes.
Advisor: Professor Robert Grzywacz
Precision spectroscopy using a digital system requires the characterization of modern digitizers. We will explore novel ways to optimize the response of the detectors with digital systems, which will be able to take advantage of the capabilities of new-generation germanium or neutron detectors. T he project will involve hands-on measurement, computational efforts, and in-depth studies of digital signal processing methods.
Advisor: Professor Robert Grzywacz