Week of March 8th

What I did

• Sunday: XAFS Thesis writing
• Monday: Traveling
• Tuesday: FEFF Codes and disorder in XANES paper reading
• Wednesday: 2010 Phys Review B, “Effects of surface disorder on EXAFS modeling of metallic clusters”
• Thursday: Finisehd above paper and tried to run FEFF9
• Friday: Wrote python code for disorder

What I learned

• Sunday: I understand the origin of the edge jumps better
• Tuesday:

  the atom-atom pair distribution information is extracted from the x-ray absorption coefficient data as a result of the photoelectron wave interference that modifies the final state of the excited atom While the data analysis methods and the computer codes that implement them vary, the most common approach to quantifying the pair distribution function is by approximating it as a quasi-Gaussian curve
  also known as a cumulant expansion method that allows to obtain the ensemble-average coordination number as the area under the curve, the average interatomic distance as the centroid, and the mean square disorder in this distance as the standard deviation. This approach, while accurate for materials with small to moderate disorder, 5 fails in systems where the disorder is either large, or the bond length distribution is markedly non-Gaussian. In those systems, as was previously shown, Gaussian approximation is inadequate, and EXAFS results obtained by using cumulant expansion are incorrect”

• Wednesday: Kurtosis, Moments, and Cumulants. Kurtosis is a measurement of a probability distribution’s skewedness. A univariate normal distribution has kurtosis=3, and a higher value means a greater right- of left-tailed skew, or thicker tails. For example, the laplace distribution is similar to a gaussian, but squished to have thicker tails, assymptotically approaching zero more slowing and producing more outliers. This is leptokurtic w.r.t. the normal distribution. The kurotisis value is the 4th moment of the distribution function scaled by some factor. Moments exist in classical mechnaics and statistics. In physics, the zeroth moment of mass is the total mass, the first moment is the COM, and the 2nd moment is the moment of rotational inertia. In statistics, the zeroth moment of a continuous PDF is the total probabiliyt (1 assuming its normalized), the 1st moment is the expectation value (the mean), the 2nd is the variance, and the 3rd moment is the skewness and the 4th is the kurtosis.
• Thursday: In the paper, I learned that EXAFS underestimate particle size and overestimate of nearest neighbor distances in systems with enhanced surface disorder in metal nanoparticles.
• Friday: Check out this sweet plot I made with plotly

The code I used to get it on my blog was

 # in python notebook
plotly.offline.plot(fig, filename = 'same_r_random_dir_plotly.html, auto_open=False)
# place the html file in the github repo /assets/images
# in markdown file
<iframe src="/assets/images/same_r_random_dir_plotly.html" height="600px" width="150%" style="border:none;"></iframe> 

What I will do next

• Consider what type of disorder to induce