Faculty/Projects
- David Allred - Extreme Ultraviolet Optics
- Branton Campbell - Symmetry in Materials
- Karine Chesnel - Nanomagnetism
- John Colton - Semiconductor Nanomaterials and Optics
- Robert Davis - Nanostructure Fabrication and Characterization
- Ben Frandsen - Local Structure of Materials for Energy Applications
- Kent Gee and Scott Sommerfeldt - Acoustics
- Eric Hintz - Astronomy: Variable Stars
- Michael Joner - Astronomy: Astronomical Observations
- David Neilsen - Numerical Relativity
- Traci Neilsen - Underwater Acoustics
- Darin Ragozzine - Orbits of Exoplanets and Solar System Small Bodies
- Richard Sandberg - Coherent Lensless Imaging and Optics
- Denise Stephens - Astronomy: Brown Dwarf Clouds, Spectral Binaries, and Transiting Planets
- Mark Transtrum - Superconducting Materials
- Richard Vanfleet - Electron Microscopy
- Jean-Francois Van Huele - Quantum Dynamics for Quantum Information Systems
Extreme Ultraviolet Optics for Next Decade’s Broadband-Space Observatory
One or two REU students will work with Professor Allred and Professor Turley to do the basic material and optical science behind determining what the mirror coating for the next very large NASA flagship space telescope will be and how that coating will be applied and protected. The LUVOIR (large UV-optical-IR) space telescope is in the formulation stage with scientists and engineers around the country contributing their insights. It may be as large as 16 meters in diameter and will be designed to meet both the needs of astrophysicists probing the beginnings and endings of stars, planetary systems and galaxies, etc., and the needs of exoplanetary scientists seeking to characterize some of the tens of thousands of planets around other stars that we will discover in the 10 years the space observatory will be used. Professors Allred and Turley’s research will look at protecting aluminum in a way that allows its VUV and EUV optical properties to remain intact. We will also look at designing, fabricating, and testing multilayer mirror coatings under the aluminum which will further extend the mirrors’ reflectance into the EUV.
*This project may not be available in the event the 2021 program is moved online.
Background Needed
- Introductory mechanics and electromagnetic theory. Modern physics and computer programming experience may be helpful.
Skills Developed and Knowledge Learned
- Computational electromagnetics (FORTRAN and/or Julia)
- Computer control of instrumentation (C#)
- Data fitting (python and/or Mathematica)
- High vacuum and ultra-high vacuum systems
- Thin-film deposition: especially, evaporation and sputtering
- Thin-film and materials characterization:
- X-ray diffraction measurements
- X-ray photoelectron spectroscopy measurements
- Spectroscopic Ellipsometry
- Atomic force microscopy
- VUV Spectroscopy
- optical engineering at BYU and
- measurements at the Advanced Light Source
Symmetry in Materials
Students in our group apply advanced computer algorithms and mathematical methods to determine and interpret the atomic structures of crystalline materials, especially those involving defects and symmetry loss, and then seek to symmetry loss to a material’s interesting or useful physical properties. Material classes of interest include high-temperature superconductors, modulated magnets, organic and hybrid organic-inorganic ferroelectrics, piezoelectrics and piezomagnetics, magnetocalorics, organic ferroelectrics, negative thermal-expansion materials, and a variety of complex oxides. See http://www.physics.byu.edu/faculty/campbell/ for more information.
Background Needed (Helpful Preparations)
- introductory physics and/or chemistry courses
- interest in mathematics and computation
- introductory computer programming course
- introductory abstract algebra helpful but not required
Skills Developed and Knowledge Learned
- Become proficient in Python and/or Mathematica programming languages.
- Analyze x-ray/neutron diffraction data.
- Become acquainted with symmetry groups and atomic structure.
- Learn basic concepts of group representation theory, graph theory, and topology.
- Become familiar with physical-property tensors.
Nanomagnetism
Our group studies magnetic properties of nanosystems such as nanoparticles and magnetic ultra-thin films. These materials exhibit magnetic structures at the nanometer scale. We use various tools to investigate the properties of these magnetic structures, including magnetic imaging (MFM), magnetometry (VSM), and synchrotron X-ray scattering techniques. By combining these different experiments we learn about how magnetic domains form, propagate and disappear as we apply an external magnetic field to the material. In the case of magnetic thin films, we also study the ability for the magnetic domain pattern to remember its configuration throughout field cycling. In case of magnetic nanoparticles, we also study magnetic ordering between nanoparticles and dynamics of magnetic fluctuations. This research is mostly experimental. A REU student would typically be involved in collecting magnetic images or magnetometry data on these magnetic structures after proper training on instrumentation, and in analyzing the data.
*This project may not be available in the event the 2021 program is moved online.
Background Needed
- Interest in material sciences
- Basic Electricity and Magnetism
- Introductory Modern Physics
- Interest in learning experimental techniques
Skills Developed and Knowledge Learned
- Expertise in Magnetic Force Imaging (MFM)
- Expertise in Vibrating Sample Magnetometry (VSM)
- Expertise in X-ray Diffraction (XRD)
- Advanced knowledge in nanomagnetism
- Analytical skills in interpreting magnetometry data and analyzing magnetic images
- Computational skills in processing X-ray scattering images
Semiconductor Nanomaterials and Optics
This research involves studying the properties of semiconductor nanomaterials through primarily optical methods. Right now we've got these projects going on:
- Semiconductor nanoparticles in ferritin - Ferritin is a hollow protein about 10 nm in diameter and can be used to create semiconductor nanoparticles which form inside the protein shell. We're investigating ways to synthesize new nanoparticles, such as PbSe, PbTe, and ZnO, and studying their properties for optical applications.
- Nanoparticles as temperature sensors - We're trying to use semiconductor nanoparticles as temperature sensors. By measuring the nanoparticles’ optical properties (photoluminescence and PL lifetime) as a function of temperature, we are developing machine learning techniques to allow these nanoparticles to later serve as optical sensors of temperature. A potential application could be injecting the nanoparticles into tissue to monitor temperatures as focused ultrasound is used to heat up and destroy tumors.
- 2D and 3D Perovskites - Perovskites are a special class of semiconductors that have great potential for use in solar cells. We're studying properties of the exciton state in 2D monolayers and 3D films, where electrons and holes are bound together. The binding energy can be measured through "electroabsorption" measurements, namely measuring the absorption as a function of wavelength, as a very strong oscillating electric field is applied to the material.
Background Needed
- introductory modern physics class would be helpful
- other skills such as optics, chemical synthesis, computer programming, and/or basic electronics can also be helpful although much can be learned “on the job”
Skills Developed and Knowledge Learned
- experience with lasers and optical spectroscopy techniques
- fundamental concepts in quantum mechanics and semiconductor physics
- materials synthesis and characterization
Nanostructure Fabrication and Characterization
Our group is working on microscale and nanometer scale fabrication and characterization. Recent advances now allow us to fabricate structures including biological structures with sizes down to a few nanometers across. In our research, we are exploring carbon nanotube composites, nanoscale chemical patterning of surfaces, and nanocrystaline phase change materials. These nanostructures have unique mechanical and electrical properties and will have significant impact in many fields including: solar power conversion, micromachines and microsensors, and biological tissue growth. We perform a host of measurements on these structures to aid in understanding and controlling their structure and physical properties.
*This project may not be available in the event the 2021 program is moved online.
Background Needed
- introductory mechanics, electricity and magnetism
- modern physics
- electronics is valuable
Skills Developed and Knowledge Learned
- Nanomaterial preparation and characterization techniques including:
- chemical vapor deposition of nanotubes
- atomic force microscopy and manipulation
- ellipsometry
- electron microscopy
- lithography
Investigating the structure and magnetism of materials for innovative energy applications
Next-generation materials will play a crucial role in addressing critical issues facing society, such as the need for sustainable energy technologies. As a first step toward understanding, optimizing, and utilizing the properties of any given candidate material, the detailed structure of the material must be known, i.e. how the atoms comprising the material are arranged or how the spins in magnetic systems are oriented relative to each other. We use advanced experimental techniques using beams of x-rays, neutrons, and muons to study the atomic and magnetic structure of energy-relevant materials such as thermoelectrics, magnetocalorics, and multiferroics to gain insight into their outstanding properties. Students will perform sophisticated data analysis and visualization in the Python programming language to develop knowledge and understanding of the structure of these materials.
Background Needed
- Introductory physics courses
- Interest in superconductivity, magnetism, and other topics in condensed matter physics
- Some experience with computer programming is helpful; a willingness to learn is necessary.
Skills Developed and Knowledge Learned
- Understanding of atomic structure and symmetry
- Understanding of exotic and useful material properties
- Knowledge of x-ray/neutron diffraction and muon spin relaxation techniques
- Data analysis and visualization in Python
Kent Gee and Scott Sommerfeldt
Acoustics
There is an opportunity for collaborative research with faculty and current graduate students in the area of acoustics. Projects may involve making a variety of acoustical measurements in different types of sound fields. Examples include pressure, intensity, or other energy-based measurements in our anechoic or reverberation chambers, in ducts, or outdoors. Some research may include working with theoretical or numerical models for comparison with experimental data. Other research could involve measurement automation using LabVIEW or another package. Applications of current research involve architectural and audio design, jet and rocket noise simulation, active noise control, and time reversal acoustics.
Background Needed
- strong interest in acoustics, audio, or noise control
- aptitude for working with instrumentation (oscilloscopes, analyzers, microphones, etc)
- familiarity with a numerical mathematics program such as MATLAB or Mathcad
- an ability to both work with a team and independently
- knowledge of passive electrical circuits would be helpful
- a working knowledge of LabVIEW would be helpful
Skills Developed and Knowledge Learned
- hands-on familiarity with acoustical measurement hardware
- ability to comprehend relevant technical literature
- acoustic data analysis and graphical representation
- data interpretation
- physical experiment design
- programming experience in MATLAB, Mathcad, LabVIEW, or another language
- a knowledge of time series photometry
Astronomy: Variable stars across the HR diagram
No other details yet
*This project may not be available in the event the 2021 program is moved online.
Securing and Analyzing Astronomical Observations
My research is focused on the study of time series observations of a wide variety of different astrophysical sources. These objects include solar system minor bodies such as asteroids and Kuiper belt objects, the detection of planetary sized objects transiting distant stars, the study of both pulsating and eclipsing variable stars, and studies of extragalactic objects such as blazars and active galactic nuclei. Current studies look for variability on timescales of a few minutes all the way up to several years. These data can be used to detect extrasolar planets, determine fundamental stellar properties, and define the fundamental properties of supermassive black holes in distant galaxies. REU students will work on a project in one of these fields by making observations at our West Mountain Observatory or by analyzing archival data from previous observing runs. One interesting bonus gained by doing work at the observatory is that there are often opportunities to help with observations on a wide variety of objects being studied as part of several different ongoing investigations.
Background Needed
- some background in introductory astronomy
- a desire to learn something new
Skills Developed and Knowledge Learned
- astronomical observing techniques
- CCD observing methods
- telescope and observatory operations
- data reduction methods using different astronomical software (IRAF, AstroImageJ, VPhot)
- a knowledge of time series photometry
Numerical Relativity
Students will study aspects of compact object systems such as neutron stars and black holes in astrophysical environments. Problems considered include the modeling the physics of neutron stars such as their interior and exterior magnetic field configurations and the effects of rotation, magnetic helicity and equations of state. Dynamical binary systems may also be studied.
Background Needed
- strong mathematical skills
- experience with numerical methods, particularly as applied to solving differential equations
Skills Developed and Knowledge Learned
- differential geometry
- an introduction to general relativity
- computational physics
- skills related to solving PDEs
Underwater Acoustics
Large arrays of hydrophones in the ocean can be used to locate acoustic sources. The reliability of these localization algorithms depends on the degree to which the ocean environment is correctly parameterized in the models. Machine learning is needed to correctly tackle this problem in real-time.
Background Needed
- Desire to learn about machine learning
- Python programming experience
Skills Developed and Knowledge Learned
- Practical experience with complex machine and deep learning algorithms
- Improved scientific computing skills
- Understanding of ocean acoustics
- Practice reading technical literature
- Written/oral communication experience
Orbits of Exoplanets and Solar System Small Bodies
Despite our powerful telescopes, most objects we discover are so far away that they only appear as a point of light. This includes objects in the far reaches of our own solar system beyond Neptune, known as Kuiper Belt Objects (or KBOs or sometimes Trans-Neptunian Objects or TNOs). Much further away are planets orbiting around other stars – exoplanets – which are usually discovered without detecting the light from the planet at all, but only the effect that the planets have on their parent stars. For both exoplanets and KBOs, the majority of the limited information we have is their orbital properties, such as time to complete an orbit or tilt of the orbit relative to some reference plane. As a result, orbital dynamics can be used to investigate both populations. An REU student could choose among multiple projects related to the orbits of KBOs or exoplanets. The goal of the project would be to develop transferable skills, to gain a letter of recommendation, and to contribute to the publication and/or conference proceeding. Dr. Ragozzine has a talent for identifying summer undergraduate projects; he has assisted 5+ undergraduate students in their eventual publication of a first-author journal article, helping to launch them into good graduate schools.
Background Needed
- Scientific computing (even at a minimal level)
- Basic knowledge of math, physics, astronomy, and/or planetary science is helpful.
Skills Developed and Knowledge Learned
- Better undergraduate research practices
- Stronger scientific computing
- Improved insight into KBOs or exoplanets
- State-of-the-art statistical analysis
- Written/oral communication
Coherent Lensless Imaging and Optics
We are developing coherent diffraction or lensless imaging to study materials dynamics at the nanometer scale. We use coherent light sources (optical, XUV, and x-ray), Fourier optics and computer algorithms to produce high resolution images of materials.
Background Needed
- desire to learn and try new things
- some exposure to optics is helpful but not necessary – some exposure of computer programming helpful but not necessary
- we have sub-teams working in optics labs and on programming algorithms, but the two teams work closely together
Skills Developed and Knowledge Learned
- basic understanding of diffraction and light scattering
- understanding of iterative computer algorithms and modeling of light propagation – understanding how light interacts with materials – understanding how materials behave at the nanometer scale
Astronomy: Brown Dwarf Clouds, Spectral Binaries, and Transiting Planets
We are using the ARC 3.5 meter to acquire spectra of brown dwarfs that appear to be either spectral binaries or have atmospheres with very patchy clouds, which leads to the emission of light from very different temperature regions. We are trying to do measure the variability of the spectral lines as the dwarf rotates to determine which features appear to be changing. We are combining this data with archival data to better understand whether what we are seeing is due to clouds or binarity. This project includes photometric and spectroscopic data reduction in the infrared as well as basic programming to fit models to results.
We also have an ongoing campaign to observe transiting planets with our 24-inch telescope and our smaller robotic telescopes. We are following-up TESS transiting planet candidates and this project will continue over the summer. This project includes just photometric reduction in the optical and is not large enough in scope to encompass the entire summer, but there will be opportunity to learn how to set up the telescopes, observe, and reduce the data to detect and measure the properties of the transit.
*This project may not be available in the event the 2021 program is moved online.
Background Needed
- Introductory astronomy class useful, but not required
- Must be able to write and work with some kind of computer programming language
- Have enough familiarity with programming to read and understand Fortran programs
Skills Developed and Knowledge Learned
- Observing and reducing ground-based IR data
- Basic programming and coding
- Making use of archival data
- Practical observing experience
Superconducting Materials for Next Generation Particle Accelerators
Particle accelerators are a foundational technology in modern science, enabling fundamental research in facilities such as the Large Hadron Collider (LHC), as well as providing some of our best sources of coherent x-rays for probing nanoscale structure in materials. The same physical principles underlie other technologies such as electron microscopy. Superconducting resonance cavities are the enabling technology that allows subatomic particles to be accelerated to near light speeds. In collaboration with researchers at the Center for Bright Beams (cbb.cornell.edu), we are working to better understand materials properties of superconductors in order to lay the foundation for the next generation of particle accelerators. Our work uses high performance computing to solve equations that describe how specific materials respond to applied magnetic fields at the mesoscale, accounting for details such as surface roughness, grain boundaries, and material inhomogeneities. Our work connects ab initio quantum calculations with precise experimental measurements to guide a “materials by design” approach to cavity development.
Information Theory of Multi-Parameter Models
Mathematical modeling is a central component of nearly all scientific inquiry. Parsimonious representations of physical systems, together with robust methods for interacting with them, is one of the primary engines of scientific progress. Much of the work in our group involves developing new methods, both theoretical and computational, for improving the predictive performance of complex multi-parameter models. Our research explores the mathematical structures that enable predictive modeling. We use information theory, statistics, differential geometry, and topology, as well as relevant physical laws from a variety of fields to better understand data, models, and the relationship between reductionism and emergence.
Modeling Complex Systems
“Complex systems” refers to a variety of physical systems whose properties make traditional modeling approaches challenging. These systems often involve many heterogeneous components connected in complicated ways. Examples include biological systems (e.g., gene or protein regulatory networks, networks of neurons, engineered systems such as the power grid, and many types of materials). These systems can exhibit a rich variety of behaviors, enabled through the complex web of interacting components. Detailed models of these systems are constructed from physical first principles, but these models involve a large number of parameters and physical components. Our research tries to develop minimal models from these “parts lists” in order to summarize and organize our understanding of the phenomena that these complex systems can exhibit.
Background Needed
- Programming experience in Python/Julia/or other scripting language
- Multivariate Calculus/Ordinary Differential Equations
- Computational Physics Tools
Skills Developed and Knowledge Learned
- Information theory
- Differential Geometry
- Programming/Scripting/Analysis skills
- Techniques of mathematical modeling and simulation
- Theory of specific complex systems (e.g., power systems, developmental biology, neuroscience, materials science)
Electron Microscopy
These projects involve the characterization of materials from the micron level down to atomic dimensions. The primary tools are electron microscopes (SEM and TEM). These unique instruments will not only allow students to image nanostructures and new materials but will allow them to probe structure, composition, and chemistry with high resolution.
*This project may not be available in the event the 2021 program is moved online.
Background Needed
- introductory physics
- some computer experience
Skills Developed and Knowledge Learned
- materials handling and polishing
- SEM and TEM sample preparation
- SEM and TEM basic operation
Quantum Dynamics for Quantum Information Systems
We study the time evolution of quantum systems with time-dependent parameters for which no exact analytic solutions are known. These involve anharmonic and coupled oscillators, quantum optical and condensed matter systems exhibiting nonlinear effects, all of which play a role in experimental implementations of quantum information schemes involving entanglement, interference, and state characterization. We aim for quantum control and watch for the onset of decoherence and dissipation through the study of open systems and different coupling mechanisms.
Background Needed
- Exposure to symbolic manipulation and programming (Mathematica and MATLAB will be used)
- Linear algebra for elementary knowledge of quantum operator formalism
- Willingness to learn, program, calculate, and interpret
Skills Developed and Knowledge Learned
- Analytical and computational skills
- Lie algebras, differential equations, operator techniques
- Interpretation of approximate solutions in quantum optical and condensed matter systems
- Exposure to concepts from quantum information and thermodynamics