>The problem with powder diffraction measurements
> is that they often leave us information-starved.
Certain informational starvation is a feature of any experimental technique and
powder diffraction is not a marginal one in this respect. Starvation, however,
is not an absolution for artificial additions in natural food. Sometimes
starvation may even help improving the health.
Sorry for the pontification if it is ;-)
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Leonid A. Solovyov
Institute of Chemistry and Chemical Technology
660049, K. Marx 42, Krasnoyarsk, Russia
http://sites.google.com/site/solovyovleonid
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________________________________
From: Brian Toby <brian.t...@anl.gov>
To: rietveld_l@ill.fr
Cc: s...@yahoogroups.com
Sent: Thursday, August 1, 2013 1:19 AM
Subject: Re: [sdpd] Re: Are restraints as good as observations ?
Let me pontificate a bit on restraints and on R-free etc.
The problem with powder diffraction measurements is that they often leave us
information-starved. We just don't get enough data to investigate what we want
to learn from the experiment, along with all the things we [think we] already
know. No one needs to measure the flatness of a benzene ring in a 50-atom
asymmetric unit from a powder.
Building restraints into a model in the early stages is an excellent way to
ensure that model stays chemically reasonable while we tinker with getting all
the experimental terms under control. It is not unusual to have to hit the
project over the head with restraints to make them matter (weighting them on
the order of the number of real data points or even more). In the end it is
nice when the weights can be set to zero, which allows us to see a fully
relaxed fit to the data, but some problems are just too complex, even with the
best of data. (I have a Faujasite refinement I sometimes expound upon as an
example...).
The way that I would describe a situation where constraints are required is
this: the paucity of data allow a wide range of models to be fit with
approximately the same goodness of fit. However, many of those models are not
chemically reasonable (non-flat benzene rings for example) so we use restraints
to make sure that we select a model that at worst is plausible. Note that even
when we don't use restraints, almost no one ever does a uniqueness test to
prove that their model is the only one that can fit the data and false minima
are always possible. Every time when one looks at a published structure, with
or without restraints, one must think that there could be another structure
that fits the data as well, if not better.
An important test when restraints are used is to see what happens as their
weights are made smaller. The model may become unreasonable, since there are
not enough data to constrain everything, but the fit to the [real] data (Rwp,
etc.) should not get significantly better. If that is not true, then the
restraints are in conflict with the experiment and something is wrong.
To perform R-free with powder data, one must excise multiple complete peaks
from the pattern, say a few sections making up 10-20% of pattern. Thus one has
even less data. This makes the information problem above even worse.
Macromolecular crystallographers can afford to "throw away" data because they
fit molecular fragment envelopes, mostly not individual atoms. Sorry, no free
lunch here.
Brian
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