Coherent X-ray Scattering Reveals Nanoscale Fluctuations in Hydrated Proteins

Datasets:

• "Figure1a.csv": scattering intensity of hydrated proteins in Wide-Angle X-ray Scattering for different fluences  (in units of photons/second/area).

• "Figure1a_inset.csv": scattering intensity of hydrated proteins in Small-Angle X-ray Scattering for different fluences (in units of photons/second/area).

• "Figure1b.csv": Intensity autocorrelation functions g2 at momentum transfer Q = 0.08 1/nm for different fluences (in units of photons/second/area). 

• "Figure1b_inset.csv":  decay rate (in second) as a function of the momentum transfer Q (in 1/nm) for different fluences (in units of photons/second/area).

• "Figure1c.csv": decay rate (in second) for variable fluence (in photons/second/um^2) at the momentum transfer Q = 0.08 1/nm.

• "Figure1d.csv": renormalised intensity autocorrelation functions g2 at momentum transfer Q = 0.08 1/nm for variable fluence (in photons/second/um^2), where the time axis is normalised to the corresponding fluence F by calculating t/(1 + a · F·τ0), where τ0 is the equilibrium time constant extracted by extrapolation to F=0 (from data in "Figure1c.csv)"

• "Figure2a.csv": The Wide-Angle X-ray Scattering scattering intensity at different temperatures T=180-290 K

• "Figure2b.csv": The Small-Angle X-ray Scattering scattering intensity at different temperatures T=180-290 K

• "Figure2c.csv": Intensity autocorrelation functions g2 for different temperatures (T=180-290 K) at momentum transfer Q = 0.1 1/nm.

• "Figure2d-2e.csv": time constants (in second) and the Kohlrausch-Williams-Watts (KWW) exponent extracted from the fits of data in "Figure2c.csv" as a function of temperature (in K)

• "Figure3b.csv": The normalised variance Chi_T at different temperatures (T=180-290 K) extracted from the two-time correlation functions.

• "Figure3c.csv": The maximum of the normalised variance Chi_0 as a function of temperature (in K).

Additionally, a Jupyter notebook "open-data.ipynb" which shows how to load and plot the data from the csv files in Python.