Index: [thread] [date] [subject] [author]
  From: Gresham Weatherly <gresham@unc.edu>
  To  : rasmb@alpha.bbri.org
  Date: Mon, 06 Dec 1999 14:09:43 -0500

XLA monochromator

I am trying to collect data at two different wavelengths during an
equilibrium sedimentation experiment. The monochromator does not always
collect the data at the correct wavelength, sometimes the header file shows
that it has collected + 1 nm from the desired wavelength.  This is okay
because I can discard these files that have been collected at the wrong
wavelength.
However, sometimes subsequent scans are offset even though the wavelength
in the header file is the same.  The attached file shows three scans that
have supposedly been collected at one wavelength, but appear to be
collected at different wavelengths. The data collected at the second
wavelength overlay, so I believe the system is at equilibrium.  
My question is when the monochromator collects five scans and averages them
does it collect all five scans at the same wavelength, and is there
anything I can do to make the XLA collect data at the right wavelengths?

Thank you for any help you can give me,

Gresham Weatherly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Department of Chemistry; CB# 3290 
University of North Carolina
Chapel Hill, NC 27599-3290
Tel: Lab (919)962-1297, Home (919)933-7837
Fax: (919)966-3675

Index: [thread] [date] [subject] [author]