Summer Undergraduate Research in Science and Engineering (SUNRISE) and Partnerships for Research and Education in Materials (PREM) @ CLASSE

The eight-week Summer Undergraduate Research in Science and Engineering (SUNRISE) and Partnerships for Research and Education in Materials (PREM) programs are closely aligned and run from mid-June through early August.

Participants will receive a stipend. Local group housing will be provided through Cornell University Campus life, if the program can be held in-person and participants prefer not to commute daily.

In the summer of 2023, we will be performing research on campus, along with formal lectures, tours of research facilities, social and recreational events, and a forum at the program's end in which participants present results of their research.

To be eligible for this program, undergraduate students must be nominated by a CLASSE researcher and collaborating faculty member from their home institution. Under this program, students interested in a career in science, engineering, and technology are invited to participate in cutting-edge research under the advisement of their faculty mentor at (CLASSE). Women, Minorities and Persons with Disabilities in Science and Engineering are strongly encouraged to participate in the SUNRISE and PREM programs.

Students work directly on research projects related to x-ray and accelerator technologies, working side-by-side a collaborating faculty from their home institution and a CLASSE scientist or graduate student mentor. Students conduct studies on such topics as photocathode sources, electrochemistry, measurement of accelerated electron beams, laser optics for use in the future accelerators, residual stress, fatigue and X-ray diffraction, x-ray optics and x-ray detectors. In addition to conducting research, students developed numerous technical skills, including familiarity with programming languages and techniques.

Interested? Here are the next steps:

MENTOR	STUDENT	2023 PROJECT	ABSTRACT
Peter Ko	Vann Montoya	"RAMS IV Metadata Capture"	The Rotation and Axial Motion System IV (RAMSIV) is a specialized mechanical load frame designed for in-situ, high-energy X-ray tension, fatigue, and torsion experiments at the synchrotron. RAMSIV generates many metadata signals consisting of internal feedback and external voltage signals. These data need to be converted into a manageable format that conforms to existing data processing workflows. To exercise this metadata conversion – we will have the student build our new Digital Image Correlation (DIC) setup designed by the Air Force Research Lab (AFRL) and perform some mechanical tests on the load frame without X-rays.
Sven Gustafson	Nikona Rousseau	"Profiling laser to meshed sample for complex geometry"	To characterize elastic strain in a sample or part, the part must be placed and manipulated precisely in the beamline. SMB recently procured a line profiling laser – this laser simultaneously reads 100’s of displacement positions along the illumination line. This project will focus on setting up the profiling laser & taking data on various geometries that will be designed and 3D printed in house by the student (geometries can be anything, but will include airfoils and rotor geometries). The student will also process this data and work on various surface fitting calculations in Python.
Kirt Page	Cullen O’Neill	"FMB Linkham stage commissioning"	The overall goal of this project is to commission the Linkam modular force stage for tensile testing and morphological investigation of high-performance polymers and polymer matrix composites. The student will develop SOPs for operating the Linkam and configure its setup for in-situ SAXS/WAXS. A secondary goal will be to investigate the structure and mechanical properties of a polymer matrix composite system. The student will explore parameters that impact the development of crystalline structure in the polymer matrix (e.g. temperature, strain, filler morphology).
Keara Soloway	Rachel Farley	"Create "CHAP-"based workflow for combined XRD/XRF"	The ChessAnalysisPipeline (CHAP) is a framework of modular building blocks that can be used to construct data processing workflows for different kinds of X-ray experiments. This project asks the student to develop a tool that assists in processing X-ray fluorescence (XRF) data within the CHAP framework. They will write an implementation of a python object (a "Processor") that takes a map of Multi-Channel Analyzer (MCA) data as input and outputs a map of element concentrations. The Processor will use PyMCA to get element concentrations from the spectra provided, and output the results in NeXus format.