SURF: Summer Undergraduate Research at Florida

SURF: Summer Undergraduate Research at Florida

UF biomaterials ResearchThe Summer Undergraduate Research experience at Florida (SURF) program spans 10 weeks and is strictly for students planning to enroll as UF Ph.D. candidates. Prospective Ph.D. students for the University of Florida fall 2023 term will be considered for SURF 2022.

SURF provides the opportunity to work with a premier faculty advisor and a senior Ph.D. student mentor. SURF Students will also engage in research and spend time furthering their path to applying and enrolling in a Ph.D. program at the University of Florida. All participants will be eligible to receive preferred Ph.D. admission and fellowship offers provided they have a successful SURF experience and maintain high academic performance levels through the completion of their bachelor’s degree. All costs for SURF participants are paid by UF including a $5,000 summer stipend, summer workshops and other social events and activities.

SURF 2022 for the Fall 2023 Ph.D. enrollment term will be held from May 28 – August 5, 2022. Apply Now for SURF 2022.

Hartig group SURF projects

  • Drone-based radiation detection: Under a Department of Defense grant we are developing a student grand-challenge (competition) related to radionuclide plume tracking. To enable this challenge, we are developing a radiation detection system that will ultimately be implemented on a drone platform for detection, characterizing and tracking the radionuclide plume released by the University of Florida Training Reactor (UFTR). Students on this project will get experience in radiation detection, drones, system integration, electronics, data acquisition, machine learning, and research collaboration among many others.
  • Optical and radiofrequency (RF) detonation detection: This project, which is funded by the Department of Defense and the National Nuclear Security Administration, is aimed at detecting and characterizing nuclear detonation events using optical (visible and near-IR wavelengths) and RF emissions. Additionally, the group is developing several laser ablation and laser-produced plasmas as testbeds for investigating the physics, chemistry, and phenomenology associated with nuclear and chemical detonations. Students involved in this project may gain experience in laser physics, optical spectroscopy, nuclear detonations, machine learning, data acquisition, and research collaboration among others.
  • Special projects: As stated earlier, students working in the group are more than welcome to lead their own effort and several existing ideas exist that you may be interested in leading.
  • Sensor fusion – Fusing multiple sensors for extracting features of interests and anomalies.
  • Optical sensing – Analysis of spectra using machine learning and ab initio modeling.
  • Detonation modeling – Assisting in a collaboration with the Department of Mechanical and Aerospace Engineering (MAE) on laser-produced plasma modeling and simulation.

Hennig group SURF projects

  • Ultra-fast machine learning potentials. We will apply our recently developed machine learning methods to learn the energy landscape of materials for battery or structural applications. The student will learn how to use Python, develop skills in machine learning, and use quantum mechanical simulations to develop a force field that describes the dynamics of the material. The choice of material depends on the student’s interest and available data.
  • Structure prediction for materials under extreme conditions. We will apply a genetic algorithm structure search to materials that have the potential of superconductivity at high pressure. In this project, we closely collaborate with experimentalists using diamond-anvil cells to compress materials to extreme pressures and measure the material’s properties down to a few Kelvin. The project has the potential to identify new crystal structures and possibly a new superconductor.

Manuel group SURF project

  • Professor Manuel’s group studies a range of materials from ferrous and non-ferrous alloys, shape memory alloys, biodegradable metals, to radiation effects on materials using alloy design techniques. Highly motivated individuals are sought in the development of advanced metals and alloys for medical applications, space/radiation shielding, magnetic processing of metals and alloy design. 

McDevitt group SURF project

  • This project involves the treatment of the formation and evolution of a relativistic electron population in a fusion device. Emphasis is placed on Monte Carlo modeling of a relativistic electron population, radiative cooling of the bulk plasma and impurity transport. The student will work on contributing to the development of a relativistic electron solver along with a coupled system of fluid equations.

Krause group SURF project

  • The relationships between microstructure and properties are the core of materials science and engineering. Dr. Amanda Krause’s research group investigates the mechanisms for grain growth to identify new processing paths to tune microstructures for improved performance. This summer project will investigate grain growth in SrTiO3 using the new, non-destructive x-ray diffraction microscopy technique that allows individual grain boundaries in 3D to be tracked before and after heat treatment. We have already found that particular grain boundaries move against their curvature, disobeying the classical laws of grain growth. Now we need to identify why! This project will entail powder processing, x-ray characterization and data analysis in Matlab/Python.

 Butala group SURF projects

  • Understanding energy storage behavior of new Li-ion battery materials. This will involve making, characterizing, and testing new battery materials. In addition to hands-on laboratory work, the analysis and effective presentation of atomic structure and battery cycling data will be key responsibilities of interns.
  • Developing data processing for local atomic structure details in thin films. This primarily computer-based project will involve using python-based tools to process and analyze atomic structure data from thin film samples, including those with energy, electronic and computing applications.

SURF projects are Also available with:

Dr. Tori Miller

Dr. Michael Tonks

Dr. Assel Aitkaliyeva