Informed Chemical Classification of Organophosphorus Compounds via Unsupervised Machine Learning of X-ray Absorption Spectroscopy and X-ray Emission Spectroscopy
Samantha Tetef, Vikram Kashyap, William M. Holden, Alexandra Velian, Niranjan Govind, and Gerald T. Seidler
The Journal of Physical Chemistry A 2022 126 (29), 4862-4872
UW Scalable Quantum Computing Lab
In March 2022, I began research as part of the UW SQRLab headed by Prof. Sara Mouradian. I have been working on analyzing crosstalk error in trapped ion quantum computing using simulations. “Crosstalk” error refers to when a laser pointed at one ion has non-negligible intensity on neighboring ions as well.
Argonne National Laboratory Spectroscopy Group
I joined Argonne National Labs’s Spectroscopy Group at the Advanced Photon Source. August 2021 and worked through July 2022 on the Argonne X-ray Emmission Analysis Package in Python (pyAXEAP), a python package aimed at automating the process of calibrating and calculating X-ray emmision spectra (XES) from 2D pixel-array-detectors on the beamline. I spent 2 weeks on-site at the APS outside Chicago during June 2022.
UW Seidler Lab
I joined the UW Seidler Lab March 2020 and began working on a project designing a refrigerated, vacuum-sealed, holder for a sample that some collaborators in the Chemistry department wanted to analyze mid reaction. The project was postponed due to COVID and so I transitioned to a project applying unsupervised machine learning to categorizing the calculated X-ray spectra of organic molecules containing phosphorus. Our goal was to see if the computer was able to, while only looking at the spectra, sort the spectra by similarity into groups that we could then correlate with various common molecule structure types. The computer was able to do this surprisingly well, giving us a measure of how much chemical structure information is encoded in the spectra. This work became my first scientific paper.