Hi Jatin from my modest experience the problem comes with the noise from detectors (typically from ionisation chambers- before and after sample). When the sample is too thick than signal/noise ratio becomes smaller, that means you are limited in k space. I have measured liquid samples with edge jump ~0.1 (in ln scale) and this allowed me to observe changes in the first coordination shell, but nothing more. If you measure you can also try to rotate sample 45 deg. answering for your second question - usually I mix sample with cellulose, or with other powders and make a pellet. with such small signal you can also think about TFY (e.g. PIPS diode) - it gives sometimes in such situation better signal/noise ratio cheers kicaj W dniu 10-11-19 10:55, Jatinkumar Rana pisze:
Dear all,
I have very basic question about the sample preparation for EXAFS. It is well understood and proven by several researchers that the optimum amount of sample (per unit area) required for EXAFS is determined by the fact that the total absorbtion of the entire sample above the absorption edge (of interest) should be between 2 to 2.5, more precisely, it should be 2.3.
The reason which forces me to put this question to a mailing list is that, i treat my sample through a process which yields only few percentage of the total amount of sample required for EXAFS. I would prefer to measure EXAFS in transmission mode with samples prepared on several layers of Kapton tape which are bound together to ensure pinhole free sample.
My questions are :
-- Can my sample be only few percentage of the "actual amount" (i.e. calculated based on above fact) required, and still i can perform transmission EXAFS ? How would this affect my data ? (I guess, it will be heavily dominated by noise)
-- What if, i have required amount of sample but since material's density is so high that it yields only small volume of powder (for a given weight), that it can not be covered up on multiple layers of Kapton tape to ensure pinhole-free sample ?
I look forward to any comments or suggestions as this would help me improvise the quality of my data.
With best regards, Jatin