Jimmy Capela

Jimmy Capela

Biography

Jimmy Capela is a rising junior majoring in Applied Physics and Nuclear Engineering at Morehouse College from Detroit, Michigan. He is passionate about efficiency, which translates into his interests in math and energy. Capela was first introduced to research at Morehouse College, analyzing how wavelengths influence termite behavior. Mr. Capela is currently researching nanocrystals with the Nuclear Science and Engineering department, specifically modeling nanocrystals. Jimmy enjoys exercising, discussing investments, engaging in volunteer work, and having a good laugh. Jimmy K. Capela’s ultimate goal in academia is to give back to God’s people through education by decreasing inequality of outcome
and opportunity.

Abstract

Automated Process to Find Facets on Nanocrystals with Stereographic Projection

Jimmy Capela¹, David Simonne², Riley Hultquist², Ericmoore Jossou^2,3
1Department of Physics, Morehouse College
²Nuclear Science and Engineering Department, Massachusetts Institute of Technology
³Electrical Engineering and Computer Science Department, Massachusetts
Institute of Technology

Nanocrystals exhibit unique properties that are crucial in various scientific and industrial applications, particularly in studying surface phenomena and catalytic processes. This research project aims to develop an automated method for determining the morphology and orientation of single Nickel nanocrystals using Python. The data, representing a 3D diffraction pattern encoding the crystal shape, is collected via Bragg Coherent Diffraction Imaging (BCDI), a technique where an X-ray beam is focused on a nanocrystal.
The primary goal is to manipulate these 3D datasets to identify and categorize the types of facets present on the crystal surfaces. Retrieving these facets is vital as they possess different atomic arrangements, leading to varied chemical and physical properties. The evolution of sample morphology under reaction brings critical information about facet dependent phenomena. For example, hydrogen embrittlement and corrosion. Some techniques used will be stereographic projection and image recognition. This project involves implementing image recognition algorithms to automatically find the facet orientation, leveraging previous methodologies outlined by Grothausmann (2012) and Carnis (2021).