Hi all, A basic question about EXAFS data collection strategies occurred to me today, so I thought I'd see what you all think. I was taught to collect data points spaced equally in k-space. The argument given to me was that collecting data points spaced equally in energy over-sampled at high-k, relative to low-k, since of course E ~ k^2. But before analyzing my data (applying a FT or whatever), we generally k-weight it. So let's say we're in a situation where random noise is significant, and suppose k-weight 1 gives a spectrum that is fairly uniform in amplitude over the k-range we are planning to analyze. (I know there have been various rationales put forth for using various k-weights, but that's not the subject of this post...) If the noise is itself independent of k, then that will mean our signal-to-noise ratio decreases with increasing k (constant noise; signal decreases as 1/k). So it would seem reasonable to me to correct for that by taking more data at high k than at low k. A start in that direction would be to collect data spaced equally in energy, although because Poisson noise falls off as the square root of the number of counts, that's not enough to give a constant signal-to-noise ratio even for a k-weight of 1, and certainly not enough for k-weights of 2 or 3. But at least it's closer than data that's evenly spaced in k. I'm sure this is something those of you who work with dilute samples have thought a lot about...I eagerly await your collective wisdom. --Scott Calvin Sarah Lawrence College