PHYS 8990 Research Topics for Spring 2019
- All first-year PhD-seeking graduate students are required to take two semesters of PHYS 8990, Introduction to Research. In this course, the student spends one half of each semester doing a research project under the supervision of a faculty member. Each semester the student will choose two topics from the list below. Availability is first-come, first-serve.
- Please do not choose more than one project from any given supervisor and do not choose projects from supervisors with whom you have already worked in an earlier semester.
- Click on "Make Choices" when you are ready to make your selections (hal login required). The topic descriptions are also available on the choices page.
Structural Properties of PolymersMichael Bachmann
In several projects, our group investigates the structural behavior of polymers,
with particular emphasis on structural transitions. In its simplest form, a
polymer is a linear chain of identical chemical units, so-called monomers, bound
by covariant bonds. A well-known example of such a system is polyethylene. Since
there are competing repulsive and attractive interactions and the chains can be
quite long, the structural reaction of such a system upon changes of
environmental parameters (temperature, concentration, pressure, etc.) results in
amazing cooperative structural effects (collapse, crystallization, formation of
glassy structures, etc.). Our main goal aims at the understanding of the basic
physical effects causing the collective behavior of the monomers when the
polymer experiences a
structural transition. Since the observed behavior strongly reminds one of phase
transitions, it is particularly exciting to study this relationship within the
framework of statistical mechanics and thermodynamics, even though polymer
systems can be so small that finite-size effects are dominant.
To achieve this goal, only the application of most contemporary Monte Carlo computer
simulation strategies provides the quality of data that is required to identify
transition points in state space for complex polymer models.
The interested student will learn how polymer systems can be modeled and how
these models are simulated by means of computational resources ranging from
standard PCs via highly parallelized graphics processing units (GPUs) and
compute clusters to supercomputers. Since data analysis is crucial for
understanding the physics behind, methods for the identification of transition
signals in stochastic data series will be introduced as well. This also includes
the visualization of three-dimensional polymer structures.
Concepts in Computational Molecular BiophysicsMichael Bachmann
The understanding of biological processes is one of the most challenging tasks
modern interdisciplinary research has to tackle. Apart from the general interest
in the nature of cell processes, it is the enormous
impact of epidemic diseases that attracts scientists with biological, chemical,
medical, and physical background to combine efforts to solve the problems that
arise from malfunctions in the fine-tuned molecular interplay of cells and cell
Proteins are the most prominent examples of such molecules. They control almost
all relevant cell processes. The subtle, sensitive relationship between their
geometric structure and the associated biological function is the reason why
mutation, misfolding, and clustering can cause the breakdown of a complete cell
system. This is, e.g., the case in Alzheimer's disease, where the interaction of
neurons is disturbed by protein-mediated processes.
Why is this interesting for theoretical physics? The most exciting thing is that
a protein is a "no-no" in theory: It is too large to be treated by classical
mechanics, but it is large enough that a full quantum approach is possibly not
necessary (it is even too complex to try this). It is a "meso-scale" object, but
with individuality. Being a chain of linearly connected amino acids of different
types, this individuality is inevitably connected with the amino acid sequence,
which determines the biological function. Structurally, this "engraved disorder"
renders a protein and its function unique, but the associated "glassiness" makes
the understanding of the relationship between structure and function so
complicated. The identification of general principles is difficult. Proteins
live in an aqueous, thermal environment and thus require a statistical theory,
but being small, they lack the general assumption of an infinitely large
system (thermodynamic limit) in this theory. Therefore, their structural transitions -
although obvious and strong - are not phase transitions in the traditional
sense. These and many more reasons let proteins be interesting objects for
modern physics-based research, but also teach us that we have not yet found the
fundamental physical principles for the systems that control our well-being.
Since analytic theory is not applicable, sophisticated computer simulation
strategies are the only way out of the dilemma. The interested student will
learn how proteins are modeled and simulated and what intrinsic problems need to
be faced because of their individual nature.
Characterization of Nanostructured SemiconductorsUwe Happek
In collaboration with Prof. Stickney, Chemistry, our group is investigating semiconductor structures grown via electrochemical deposition onto gold substrates. Coating the substrate with a nano-structured polymer film will result in the growth of nanostructured semiconductor deposits, because electrodeposition will take place on the exposed gold substrate only.
The student will be introduced to a number of techniques to study the semiconductor structures, infrared spectroscopy, fluorescence, atomic force microscopy, and x-ray scattering.
Frequency Stabilization of Semiconductor LasersUwe Happek
Precise clocks play a very important role in physics, a well known example is the so-called “atomic clock”, which is based on locking an oscillator to the emission of Cs atoms (this clock defines the unit of time). However, these devices are very bulky, they fill a small laboratory. Thus, there is a demand for compact, portable precision clocks.
Stabilized semiconductor lasers are a promising approach, and short time stabilization of 1 part in 1012 has been demonstrated recently by Rufus Cone’s group in Montana.
In this project, the student will conduct fundamental research to improve the long-term stability of a semiconductor laser by locking it to an infrared transition of an impurity ion in a glassy host.
Monte Carlo Simulations of Phase TransitionsDavid P. Landau
Phase transitions of diverse kinds occur in an immense variety of physical systems. We use large scale, importance sampling Monte Carlo simulations to carefully examine the equilibrium thermodynamic behavior for different models in statistical physics. Our goal is to elucidate the effects of changing spatial dimensionality, symmetry, and interactions and to search for Universal behavior. We will focus on magnetic phase transitions that occur in simple lattice models, but we also examine order-disorder transitions in semiconductor alloys, equilibrium polymers, interface delocalization, and surface reconstruction. Appropriate models can be constructed that are well suited for simulation and visualization, and these will be investigated from different perspectives. We use standard Monte Carlos sampling techniques as well as novel new methods like Wang-Landau sampling.
Spin Dynamics Simulations of Magnetic SystemsDavid P. Landau
The study of elementary excitations and “critical slowing” (long time scales) in simple magnetic lattice models forms an exciting topic of investigation. We use a variety of modern time integration techniques to follow the microscopic equations of motion of large numbers of interacting magnetic moments. The resultant data allow us to compute time-displaced, space-displaced correlation functions from which we extract the dynamic structure factor. Results from the simulations can be compared directly with data from inelastic neutron scattering experiments and can also be used to test theoretical predictions.
Computer Simulations of Non-equilibrium BehaviorDavid P. Landau
The behavior of non-equilibrium systems is an exciting topic but one which is still on the frontier of statistical physics. We use kinetic Monte Carlo simulations to investigate lattice models for the growth of films by molecular beam epitaxy (MBE) and other simple kinetic processes. Our goals are to determine the long time behavior of the growth interface as well as to provide information that can be used to build appropriate theoretical models. We also use “spin-exchange” Monte Carlo simulations to study pattern formation in driven diffusive systems that constitute a simple paradigm for super-ionic diffusion in a field. In both cases, computer visualization is an important tool!
Radio Spectroscopy of the Interstellar MediumLoris Magnani
We will have a look at how radio astronomers study the cold interstellar medium primarily using spectroscopy of diatomic molecules. After a brief introduction to the topic, the student will learn some basic data reduction techniques for molecular spectral line data and see how that data are used to determine the physical parameters of molecular clouds in the Galaxy.
Molecular Beam Laser SpectroscopyHenning Meyer
Our research program is centered around the experimental study of the interactions in molecular clusters. The interest in such systems is motivated largely by the prospect of developing a detailed understanding of bulk matter through the access to direct quantum specific information on finite sized molecular clusters. Dimers are of particular interest as the first step towards describing bulk material at a molecular level. Their structure and dynamics can be described in terms of a multidimensional potential energy surface (PES) which provides the basis for a great variety of active research areas like molecular modelling of bio-molecules and the influence due to solvent effects. It is also the basis for the theoretical description of bimolecular reactions and energy transfer which are essential to understanding and modelling of such diverse processes like combustion, atmospheric warming and pollution.
As part of the PHYS 8990 rotation, the incoming graduate student will be exposed to different techniques employed in our research:
- Molecular beam laser spectroscopy of clusters in the ultraviolet and infrared.
- Laser spectroscopic detection of molecular products in molecular beam scattering experiments.
The theoretical background of these experiments is soundly based on non-relativistic quantum mechanics either through the bound or the continuum states of the cluster under investigation. Although the main emphasis is on experimental research, theoretical work on our own or in collaboration with theory groups represents another important aspect of this research,
Theory of fluids in bulk and restricted geometryK K Mon
We are interested in the fundamental equilibrium and non-equilibrium properties of fluids in bulk and restricted geometry. Analytical and numerical methods are used to study hardsphere fluids in the bulk and narrow pores. Recent projects focus on hardsphere perturbation theory for bulk fluids and single-file diffusion of fluids in narrow cylindrical pores.
Stochastic processes in physics, finance and other complex systemsK K Mon
We apply methods of non-equilibrium statistical mechanics to understand dynamical processes of complex systems. Current interests include fluid diffusion in restricted geometry, stock price dynamics, and application of first passage time concept.
Hadron dynamics and its structureKanzo Nakayama
Hadronic physics is currently a major fundamental area of research in Nuclear/Elementary Particle physics. In fact, a large part of the Nuclear/Elementary Particle physics community worldwide is currently trying to understand the structure of hadrons and their dynamics in terms of the basic degrees of freedom of Quantum Chromodynamics, the fundamental theory of strongly interacting particles. This type of study has been made especially timely with the advent of a new generation of particle accelerators such as the one at Thomas Jefferson National Laboratory. Thus, the participating student will be exposed to one of the cutting-edge research topics in the area of Hadron physics. The student will learn the basic concepts of the theory of strongly interacting particles as well as calculational techniques in order to compare theoretical predictions with experimental data. This will provide the student a taste as to how research in the area of theoretical hadronic physics is done.
Biological Applications of Statistical MechanicsH.B. Schuttler
My group is pursuing research in two major areas: strongly correlated electron physics and biological applications of statistical mechanics. In the strongly corrlated electron area, we are presently working on the implementation of Monte Carlo simulation methods for the evaluation of self-consistent Feynman diagram expansions. In the biological stat. mech. area, we are pursuing efforts to model gene regulation and biochemical/metabolic processes observed in living cells by means of ensembles of chemical rate equation models.
In both research areas, Monte Carlo simulation techniques are very important and they also provide a convenient way to introduce students to the respective subjects. There are two projects for incoming graduate students to work on:
(A) Monte Carlo evaluation of self-energy diagrams in the Hubbard model
(B) Ensemble equilibration and sampling for a simplified 3-gene model of the "Repressilator" in E. coli.
In both projects, the student will first be introduced to Markov-chain based random sample generation. The student will then be asked to write a simple Metropolis Monte Carlo code to generate random samples from discrete ("loaded dice") and 1-D continuous probabability distributions (with plenty of help from the instructor). The student will then be given an existing self-energy diagram code, in Project (A), or an exisiting ensemble simulation code, in Project (B), to run a small simulation, make graphical displays of some of the simulation results and interpret the results.
Astrophysical Computer SimulationsRobin SheltonOur galaxy is made of dark matter, stars, and a gaseous atmosphere. Like other galaxies, our galaxy is surrounded by a low density gas of material that was made in the Big Bang. As time goes by, such material falls into galaxies, becomes part of their gaseous atmospheres, and then can condense into stars and planets. The Shelton group studies the gas as it falls into galaxies and studies gas that is already in our galaxy. We use computer codes to simulate these clouds of gas.
Ultrafast spectroscopy of nanostructures and materialsSusanne Ullrich
In this independent study course, students will learn about ultrafast spectroscopic techniques such as transient absorption and transient grating spectroscopy. You will be involved in the construction and optimization of various optical set ups that we intend to use for the characterization of photoinduced dynamical processes in nanostructures and materials.
Experimental BiophysicsSusanne Ullrich
Our research group uses modern femtosecond pump-probe spectroscopies to investigate the photophysical and photochemical properties of biomolecular building blocks and their clusters. Biophotonic functions are triggered through light activation. The photoexcited biomolecules can undergo a variety of relaxation processes and the competition between these processes governs the selectivity, efficiency and reliability of their function. Our intention is to discern in detail relaxation processes in individual biomolecules and study the effect of intermolecular interactions (the local environment) on these dynamics. The main emphasis is on experimental research however the interpretation of our data is usually supported by ab inito quantum mechanical calculations. The understanding of dynamical processes in molecules is relevant to a variety of active research areas ranging from biomedical (e.g. light activated drugs) to molecular electronics (e.g. molecular switches) applications.
Magnetic Resonance Imaging (MRI) PhysicsQun Zhao
Our research program is centered on one of the most advanced biomedical imaging modalities, MRI, and its advanced applications such as functional MRI (brain imaging), cancer imaging, and NMR spectroscopy.
MRI relies on the relaxation properties of excited nuclei, e.g. hydrogen nuclei in water and fat. When the object to be imaged is placed in a powerful, uniform magnetic field the spins of the atomic nuclei within the tissue all align with the magnetic field. The magnetic dipole moment of the nuclei then precesses around the axial field. The frequency with which the dipole moments precess is called the Larmor frequency. MRI allows the subject (e.g. human) to be imaged in x, y, and z from head to toe, or completely flexible orientations for images. MRI images are created from the acquired data using the discrete Fourier transform (DFT) in 2D or 3D.
In this project, students will have an opportunity to learn fundamentals on MR imaging, such as radiofrequency transmit/receive, gradients encoding, as well as learn MRI image processing methods. The BioImaging Research Center (located in Coverdell Center) has a state-of-the-art 7 Tesla (Varian) and 3T (GE) magnet, which provides top quality MR imaging capabilities. Students will have opportunities to work on the magnet and build hands-on experiences in MR systems.
Dynamic Contrast Enhanced MRI and Biological/Biomedical ApplicationsQun Zhao
Dynamic Contrast Enhanced MRI (DCE-MRI) using contrast agent (e.g. superparamagnetic iron oxide or SPIO nanoparticles) has been the subject of extensive research since the early 1990s. For DCE-MRI, a series of MRI images were taken before, during, and after the injection of an MR contrast agent. Conventional MR imaging can be considered as a snapshot at a given time whereas DCE MRI can be thought as a movie which is the series of images. From the analysis of time series data of DCE-MRI, information about blood volume and vascular permeability which are physiological parameters associated with the tumor can be obtained. Novel DCE-MRI applications include cancer diagnosis, treatment evaluation, drug delivery, molecular and cellular imaging etc.
On the other hand, the paramagnetic nanoparticles can be used to label stem cell or cancer cells, providing researchers with the ability to monitor the migration and homing of the cells in living tissues with MRI. Researchers have been investigating different methods to provide positive contrast, such as gradient-compensation techniques (White Marker), Off-resonance techniques (IRON), and Post-processing techniques (SGM), etc.
In this project, with availability of a top quality 7 Tesla and a 3 Tesla magnet located at the BioImaging Research Center (BIRC), Coverdell Center, students will have an opportunity to learn fundamentals on contrast-enhanced MR imaging using paramagnetic nanoparticles, as well as post-processing techniques to generate positive contrast.
Machine Learning in Applications of Magnetic Resonance ImagingQun ZhaoMagnetic resonance imaging (MRI) has been extensively applied in biomedical research (e.g. tracking of labeled stem cells, assessment of drug delivery) and clinical applications (e.g., early detection of cancer). Additionally, functional MRI (fMRI) has recently been used to investigate human brain functions through changes of magnetic susceptibility property of oxygen-carrying blood in the brain. Machine learning, an artificial intelligence approach, can further enhance detection of tumors and identification of brain function changes. In this project, interested students will have opportunities to learn basic statistical analysis techniques (neural network models) to ‘train’ computers to ‘learn’ with data acquired at the MRI physics lab, at the Bioimaging Research Center on UGA campus.
Biosensor Design and ApplicationYiping Zhao
Surface-enhanced Raman scattering (SERS) is a powerful analytical tool for chemical and biological detection. The practical application of the remarkable analytical sensitivity of SERS has not been widely accepted as a viable diagnostic technique due to the difficulty in preparing robust substrates of the correct surface morphology that provide maximum SERS enhancements. Recently we have demonstrated that the Ag nanorod (AgNR) array substrates fabricated by oblique angle deposition method can serve as excellent SERS substrate. Those substrates can be used as a rapid and sensitive detections of virus and bacteria. Our results have demonstrated that i) SERS can detect surface-bound viruses; ii) SERS can detect extremely low concentrations of surface-bound viruses; iii) SERS can distinguish between different viruses based on their Raman spectra; iv) SERS can detect viruses in biological media, and v) SERS can differentiate between different strains of the same virus. (https://www.physast.uga.edu/~zhaoy/sensor.htm). The goal of this project is to develop this SERS technique into a practical point-of-care diagnostic technique for real clinic applications. Therefore, we are focusing on:
- Multiplexing sensor development for infectious diseases: based on surface enhanced Raman scattering and portable Raman instrument, we are interested to develop a point of care (POC) sensors that can simultaneously detect multiple viruses. This project requires additional training in optical engineering, statistical method development, instrument design, and the student is willing to work with scientists from Infectious Diseases.
- Portable PCR development: based on the principle of polymerized chain reaction (PCR) and nanomaterial principle, the project seeks to develop a portable PCR system for POC applications.
- Colorimetric sensors development: based on the diffraction principle or other optical principle, used the advance fabrication techniques or biomimic materials to develop biological sensors that change color.
- Magneto-optical sensors: using the magneto-optical Kerr effect, or other optical rotation or circular dichroism principle to develop structural sensitive sensors.
Plasmonics and Metamaterials Design and ApplicationYiping Zhao
Metamaterials are artificial media composed of engineered sub-wavelength structures, which cause them to have fascinating new electromagnetic properties that are not usually found in nature; this research area is the forefront of modern optics and optical technology. Optically chiral nanostructures have received a considerable amount of attention recently. This is largely due to intriguing phenomena associated with strong optical chirality, including negative refraction, repulsive Casimir forces, unusual spin Hall effects, and super chiral fields. The exciting properties of optically chiral nanostructures open up a wide array of potential applications in a variety of fields such as nanophotonics, biosensing, and nanofabrication, yet fabrication of plasmonic materials with strong optical chirality remains challenging, particularly for those structures operating in the visible regime. This project focus on both experimental and theoretical aspects of metamaterial design:
- Monte Carlo simulation of chiral metamaterial growth and numerical calculation of the optical properties: kinetic Monte Carlo simulation will be conducted to visualize the metamaterial growth mechanism and three dimensional structures, new design will be proposed, and finite difference time domain (FDTD) method will be used to solve Maxwell equations and predict the optical response.
- Experimental fabrication and characterization of chiral metamaterials: based on the glancing angle deposition technique and two-dimensional nanostructure template fabrication technique, different chiral nanostructures will be fabricated, and their optical properties, their sensing applications will be explored.
Multiscale Modeling Nano-Bio Materials SystemYiping Zhao
Nanotechnology has profound impact on biological applications, such as drug delivery, disease treatment, bactericidal/viracidal, etc. Therefore, to understand how nanostructured materials interact with biological system is a key to extend and sophisticate these applications. This project we will focus on the following two aspects:
- Computational modeling of layer-by-layer nanomaterial self-assembly on bacteria cells or cancel cells: We will develop a coarse-grained molecular dynamics model to simulate the dynamic self-assembly process of charged nanoparticles on cells, analyze the pattern of self-assembled nanoparticle system, and establish the guideline from predictive modeling to design or control the self-assembly process in experiments for drug delivery, bactericidal effect, cancer cell killing and cell protection.
- Nanorod-mediated mechanical destruction of cell membrane: dissipative particle dynamics simulations will be performed to analyze the shape effect of magnetic nanorods (MNDs) on the integrity of cell membranes when they actively move around cell membranes so as to provide a novel mechanical design of cancer treatment using active rotational MNDs.
Smart Nanomotor Design and ApplicationsYiping Zhao
The construction of artificial nanomachines remains a major contemporary challenge; while in nature, biological systems employ bionanomachines to perform important biological functions such as ATP synthesis, bacterial motility, cell replication, and muscle contraction. Those bionanomachines have been studied extensively in order to understand their operation mechanisms. Another kind of small machine in nature is the molecular machine. Synthetic molecules have been produced to possess the functions of shuttles, rotors, muscles, switches, elevators, and motors. One significant advantage of the bionanomotor is the use of chemicals to fuel its motion, usually though a catalytic reaction. To mimic this mechanism, a catalytic reaction can be introduced to an inorganic nanosystem to achieve the desired motion. These catalytic nanomotors have captured the essential idea of “fueling” the nanomachine, and translate the catalytic reaction energy to kinetic energy for nanorod motion. Here we are interested in three aspects of these nanomotors:
- Designing integrated smart nanomotor systems: Controlled motion of nanoscale objects is the first step in achieving integrated nanomachinary systems that can enable break-through applications in nanoelectronics, photonics, bioengineering, and drug delivery or disease treatment. However, to mimic the complicated motion and functionality of bionanomotors, such as rotation, rolling, shuttling, delivery, contraction, etc., it requires one to design intelligent nanomotor systems to be able to perform different motion, actuation, sensing, targeting and transportation. In this project, we will design different nanomotor components for self-assembly. Both magnetic self-assembly through incorporating magnetic layers and electrostatic self-assembly through chemical interactions will be used to assemble the nanomotor systems. The kinematics and dynamics of the nanomotor component and nanomotor systems will be investigated by comparing results from microhydrodynamic simulations with the experimental data.
- Kinetics of nanomotors in confined and crowded environment: Micro/nano-robots can be used for 1) localized delivery of chemical or biological substances for targeted therapy, 2) selectively removing material mechanically, and 3) transmitting information from a specific location that would otherwise be difficult or impossible to get to. However, medical micro/nano-robots must be designed to work in complex environments, which often feature fluid-filled tubes and cavities, soft tissues, as well as particulates with various dimensions. The ultimate goal of this project is to understand the fundamental transport behaviors of a group of nanomotors in confined and crowded environments such as micro-blood vessels.
- Mechanically Targeting Fibrin Clot by Magnetic Nanomotors: Stroke is the third leading cause of death in the U.S. and the leading cause of disability amongst adults. We believe that the blood clot can be both chemically and mechanically removed by designing novel surgical micro-/nano motors, and engineering and controlling their interactions with the fibrin clot. This project will explore new methods to employ the principle of nanomotors and their unique behaviors in liquid to better treat stroke.