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This blog will now partly shift from what I learned as a data scientist to what I’ve learned as a scientist, to keep track of my thesis progress. Of course some of what I learn and do will be related to data science, but for the most part my posts will switch from dataframes in pandas to x-ray absorption near edge spectroscopy monte-carlo simulations. One thing to think about is how I want to define some KPI’s track my thesis progress to ensure I finish by the end of August.

What I did

  • Monday: Read Frenkel JPCL 2017: “Supervised Machine Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles”
  • Tuesday: Lab meeting, Downloaded and installed Mathematica and Demeter, Watched lecture 1 from the short course on XAFS
  • Wednesday: Lectures 5, 6, 7. Widdle away at thesis chapter 1.
  • Thursday: Lectures 8, 9, 10. Thesis restructuring.
  • Friday: Lecture 11. Lots of thesis writing on XAFS.
  • Sat: Hike
  • Sun: More XAFS thesis writing.

What I learned

  • Monday: My work will be similar to the 2017 paper, though I will explicitly be looking to reconstruct disordered nanoparticle structures from XANES data via an ANN.
  • Tuesday: Unlike EXAFS, XANES features are due to the interference from multiple scatterings.
  • Wednesday: Problems with exploding parameter numbers with FEFF and spectra fitting
  • Thursday: Coordination Subshells are group by atom type, not by sphere’s of nearest neighbors. I had a previous misconception.
  • Friday: Disorder in XANES in mathematica.

What I will do next

  • Finish XAFS course and begin using FDMES or FEFF9

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