Project Info
*Machine Learning Software Development for X-ray Photoelectron Spectroscopy
Xerxes Steirer
ksteirer@mines.edu
X-ray Photoelectron Spectroscopy (XPS) is used to identify the elements and their bonding structures in countless applications including solar energy, batteries and mining ore! This project seeks to implement machine learning algorithms to improve speed and accuracy of applied XPS analyses generated from the Rocky Mountain Environmental XPS Facility.
Weekly mentoring sessions and fun learning opportunities will support the students' growth and skill development.
More Information:
Grand Challenge: Not applicable
XPS is certainly applicable to ALL grand challenges of engineering, such as solar, water, batteries, etc. The student may be engaged in some or all of these depending on their level of enthusiasm.
See XPSsimplified.com for general info.
See https://github.com/csm-xps/minespex for the early release of the software that will be the hub for the MURF effort.
Primary Contacts:
Xerxes Steirer
Student Preparation
Qualifications
Python coding skills will be needed. Also, a general interest in physics and chemistry are important.
TIME COMMITMENT (HRS/WK)
8
SKILLS/TECHNIQUES GAINED
Students will gain a deep understanding of the photoelectron process, how the analysis of XPS data is directed by research goals, and a resume builder for contributing to an open source python coding project.
MENTORING PLAN
Weekly meetings, Slack channel for MURF project, 1 to 1 meetings as needed, as well as support and feedback on code and project report for MURF celebration event.
PREFERRED STUDENT STATUS
Sophomore
Sophomore
Junior
Senior