These rings are nanocrystalline cubic ice (ice Ic, as opposed to the "usual" ice Ih). It is an interesting substance in that noone has ever prepared a large single crystal of it. In fact, for very small crystals it can be hard to distinguish it from amorphous ice (or "glassy water"). The three main rings that you see from ice Ic coincide almost exactly with the centroids of the three main diffuse rings of glassy water, and as the ice Ic crystals get smaller, the rings get fatter (Scherrer broadening). You can even measure the size of the crystallites by measuring the width of the rings. At the limit of 1-2 unit cells wide, the diffraction pattern of ice Ic powder looks almost exactly like that of glassy water, so I suppose one could say that there is a continuum of phases between the two.

And yes, there are crystals that "like" a certain mixture of cubic ice and amorphous water in their solvent channels. Other's don't like it at all. But I agree with JS below that the problem here is not the ice rings. Probably overlaps? Best to look only at spots inside the 3.8A circle until you figure out what is going on.

-James Holton
MAD Scientist

On 10/13/2011 11:20 PM, James Stroud wrote:
First of all, are you sure those are ice rings? They do not look typical. I 
think you might have salt crystals from dehydration *before* freezing. 
Otherwise, I think your freezing went well. Maybe try a humidity controlled 
environment when you freeze.

Second, I'm not so sure the bad stats come from the contaminating rings. The 
lattice seems to have some sort of problem, like a split lattice. You might be 
able to tackle this problem by increasing your spot size or skewing it's shape 
to compensate for the split. You need to investigate several images throughout 
the run to see whether and how to manipulate your spot size. Sometimes, the 
split lengthens the spots in the direction of the phi axis and you get lucky. 
But I think the phi axis might be horizontal in this picture, which makes 
things a little trickier. From one image, it is difficult to tell the pathology 
of this crystal.

In principle, if you can accurately measure the most high-resolution spots 
visible (which appear to be about 1.9 Å, guessing from your log file) then you 
will have a pretty good data set, even with the contaminating rings.

Personally, I'd use Denzo for this data, but I don't know what is vogue with 
the community right now. I still use O, so my tastes might be somewhat 
antiquated.

James



On Oct 13, 2011, at 11:12 PM, ChenTiantian wrote:

Hi there,
I am processing a dataset which has bad ice rings (as you can see in the attach 
png file).
I tried both XDS and imosflm, and got similar results, it seems that adding " 
EXCLUDE_RESOLUTION_RANGE" cannot get rid of the effects of the ice rings.
the following is part of the CORRECT.LP which is the second attached file, you 
can find more details there.

   SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE>= -3.0 AS FUNCTION OF RESOLUTION
  RESOLUTION     NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR 
COMPARED I/SIGMA   R-meas  Rmrgd-F  Anomal  SigAno   Nano
    LIMIT     OBSERVED  UNIQUE  POSSIBLE     OF DATA   observed  expected       
                               Corr

      4.24       37152    5537      5545       99.9%      46.9%     52.7%    
37150    2.48    50.8%    19.4%   -28%   0.513    5136
      3.01       55344    9002      9840       91.5%      62.7%     65.1%    
55116    1.76    68.3%    48.1%   -28%   0.520    7760
      2.46       84636   12699     12703      100.0%      67.4%     84.7%    
84634    1.55    73.0%    54.2%   -19%   0.513   12104
      2.13       97910   14743     14987       98.4%     254.5%    199.3%    
97908    0.16   276.2%  4899.9%   -23%   0.473   14037
      1.90      110260   16846     16940       99.4%     299.2%    303.3%   
110245    0.06   325.0%   -99.9%   -17%   0.422   15995
      1.74      118354   18629     18744       99.4%    1062.0%   1043.6%   
118317   -0.20  1156.4%   -99.9%   -13%   0.380   17414
      1.61      122958   20193     20331       99.3%     967.5%   1571.1%   
122868    0.10  1059.7%   987.3%    -2%   0.402   18348
      1.51      125075   21554     21794       98.9%     838.9%   1355.1%   
124933    0.08   922.6%  1116.9%    -1%   0.402   18977
      1.42       72057   17042     23233       73.4%     640.8%    775.3%    
70391    0.08   732.5%   826.7%    -8%   0.425   10003
     total      823746  136245    144117       94.5%     166.4%    166.7%   
821562    0.40   181.1%   296.7%   -15%   0.435  119774

Note that I/SIGMA of each resolution shell is<2.5, so how should I do to 
process the dataset properly? Any suggestion about this super ice rings?
Thanks!

Tiantian

--
Shanghai Institute of Materia Medica, Chinese Academy of Sciences
Address: Room 101, 646 Songtao Road, Zhangjiang Hi-Tech Park,
Shanghai, 201203
<csrc.png><CORRECT.LP>

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