Re-stating the obvious: To solve structures from powder diffraction, first they must be indexed! Lachlan M. D. Cranswick CCP14 (Collaborative Computation.

Re-stating the obvious: To solve structures from powder diffraction, first they must be indexed!
Lachlan M. D. Cranswick CCP14 (Collaborative Computation Project No 14 for Single Crystal and Powder Diffraction) Department of Crystallography; Birkbeck College, University of London, Malet Street, Bloomsbury, London, WC1E 7HX, UK. WWW:

Based on a co-authored presentation at the ACA 2002 conference in San-Antonio, Texas, USA
Lachlan M. D. Cranswick CCP14 (Collaborative Computation Project No 14 for Single Crystal and Powder Diffraction) Department of Crystallography; Birkbeck College, University of London, Malet Street, Bloomsbury, London, WC1E 7HX, UK. WWW: Robin Shirley School of Human Sciences University of Surrey Guildford, Surrey, GU2 7XH, U.K. Tel: (+44) Fax: (+44)

Notes Free Zone - they are on the web http://www. ccp14. ac
Slide 3 Lachlan M. D. Cranswick

Talk Aims Some history of Indexing of Powder Diffraction Data
Peak finding and peak profiling software Fundamental Parameters Peak Fitting Available powder indexing software and indexing suites Crysfire in action Chekcell in action Mmap with Crysfire 2002 (released August 2002) MCMaille by Armel Le Bail (released Sep 2002) Possibilities for the future and conclusion Slide 4 Lachlan M. D. Cranswick

Some History of Powder Indexing
First published manual powder indexing method: Runge, C. (1917), "Die Bestimmung eines Kristallsystems durch Rontgenstrahlen", Physik. Z., 18, Candidates for first published computer based powder indexing Haendler, H. M. & Cooney, W. A. (1963), "Computer Determination of Unit-Cell from Powder-Diffraction Data", Acta Cryst., 16, Lefker, R. (1964), "Indexing of tetragonal and hexagonal X-ray powder photographs with the aid of a small computer", Anal. Chem., 36, Slide 5 Lachlan M. D. Cranswick

Some History of Powder Indexing - 2
Candidates for first published publicly available powder-indexing program Haendler, H. M. & Cooney, W. A. (1963), "Computer Determination of Unit-Cell from Powder-Diffraction Data", Acta Cryst., 16, Lefker, R. (1964), "Indexing of tetragonal and hexagonal X-ray powder photographs with the aid of a small computer", Anal. Chem., 36, Werner, P.-E. (1964), "Trial and error computer methods for the indexing of unknown powder patterns", Z. Krist., 120, Hoff, W. D. & Kitchingman, W. J. (1966), "Computer indexing of x-ray powder patterns from crystals of unknown structures", J. Sci. Instrum., 43, Slide 6 Lachlan M. D. Cranswick

Some History of Powder Indexing - 3
Candidates for first publically available general indexing program Ishida, T & Watanabe, Y. (1967), "Probability Computer Method of Determining the Lattice Parameters from Powder Diffraction Data", J. Phys. Soc. Japan, 23, Roof, R. B. (1968), "INDX: A Computer Program to Aid in the Indexing of X-Ray Powder Patterns of Crystal Structures of Unknown Symmetry", Los Alamos Laboratory, University of California, Report LA-3920. Taupin, D. (1968), "Une Methode Generale pour l'Indexation des Diagrammes de Poudres", J. Appl. Cryst., 1, Visser, J. W. (1969), "A Fully Automatic Program for Finding the Unit Cell from Powder Data", J. Appl. Cryst., 2, Slide 7 Lachlan M. D. Cranswick

Checking Sample Purity
Powder indexing requires line-position data of the highest available quality An important aspect of this is purity, since indexing programs don’t like to struggle with impurity lines, and several will not accept them at all. Some suggestions from Robin for checking sample purity: Optical (polarising) microscope Density analysis in a gradient column Electron microscopy and diffraction of selected crystallites And, if time permits, see whether properties are changing with time Slide 8 Lachlan M. D. Cranswick

Peak Profiling Software
For Overall Summary of available peak profiling software refer to: Some of the available freeware includes: CMPR DRXWin EFLECH GPLSFT pearson.xls Rawplot (with GSAS) SHADOW Powder v2.00 PowderX Winfit Winplotr (with Fullprof) XFIT Slide 9 Lachlan M. D. Cranswick

Empirical peak fitting : Some tricks may be required for stability and reasonable results
Peaks over small ranges may have to be linked to have the same shape and width Usually fit small ranges of data - groups of peaks Might have to fit large and medium peaks first, followed by trace peaks Slide 10 Lachlan M. D. Cranswick

Peak Profiling: high accuracy peak positions using Fundamental Parameters peak profiling
Example of Fundamental parameters (convoluting in the geometry elements of the diffractometer) that can provide accurate peak positions as though your sample was being run on an “ideal” diffractometer. Tutorial at: Available Fundamental Parameters Peak Profiling and Rietveld software: XFIT (no longer maintained) Topas (Commercial - sequel to XFIT) BGMN (Commercial - academic demonstration version is freely downloadable) EFLECH/Index freeware from BGMN website Slide 11 Lachlan M. D. Cranswick

XFIT Fundamental Parameters Peak Profiling mode : fit to a low angle peak on a Bragg-Brentano diffractometer Slide 12 Lachlan M. D. Cranswick

Powder Indexing FOM Results XFIT Fundamental Parameters peak profiling compared to empirical Peak Fitting Slide 13 Lachlan M. D. Cranswick

Powder Indexing - indexing programs
Overall Summary of available powder indexing software refer to: Powder Indexing: Classic (widely used): Ito, Dicvol, Treor High symmetry (exhaustive): Taup (=Powder), Dicvol Other powerful (general symmetry): Lzon, Kohl (=TMO), Fjzn Dominant-zone cases: Lzon, Losh, Mmap Semi-automatic (via SIW basis set): Losh, Mmap Fundamental parameters & covariance matrix: EFLECH/Index Incommensurate, etc: Supercell Monte Carlo / Random search: EFLECH/Index, McMaille Others (better with some user guidance): Scanix, Autox Slide 14 Lachlan M. D. Cranswick

Powder Indexing - indexing suites
Overall Summary of available powder indexing software refer to: Integrated Suites: Crysfire Powder v2.00 PowderX PROSZKI WinPlotr and after primary indexing: Chekcell Slide 15 Lachlan M. D. Cranswick

Powder Indexing - specialist programs
Supercel is a specialised indexing program by Juan Rodriguez-Carvajal for tackling incommensurate cells and super/sub-cell relationships. (available within Winplotr/Fullprof) Web: FTP: ftp://bali.saclay.cea.fr/pub/divers/fullprof.2k/ Slide 16 Lachlan M. D. Cranswick

Powder Indexing - specialist programs
McMaille reconstitutes a peak listing into a full profile and performs monte carlo based searching for good cells. Because it is Monte Carlo based it can be very slow, but due to it being whole profile, can be insensitive to trace impurity peaks. Web: Slide 17 Lachlan M. D. Cranswick

Powder Indexing - Using PowderX
by Cheng Dong Peak finding Links to Treor Slide 18 Lachlan M. D. Cranswick

Powder Indexing - Using Winplotr
by Juan Rodriguez-Carvajal and T. Roisnel Peak finding / profiling Links to WinTreor, Windicvol, Winito and supercell Slide 19 Lachlan M. D. Cranswick

Powder Indexing - the Crysfire suite (1)
by Robin Shirley (+ many contributing authors) Intelligent defaults for control-parameters when launching each indexing program Data rescaling for tackling high-volume cells from macromolecular samples and zeolites Integrated under a common interface for use by non-specialists Slide 20 Lachlan M. D. Cranswick

Principal Contributors: Franz Kohlbeck (Kohl [=TMO]) Daniel Louër (Dicvol, Lzon, Losh) Robin Shirley (Overall + Mmap, Lzon, Losh, Fjzn, etc) Ton Spek & A.Meetsma (Lepage) Daniel Taupin (Taup [=Powder]) Jan Visser (Ito, Fjzn, Lzon, etc) Per-Eric Werner (Treor) Slide 21 Lachlan M. D. Cranswick

Crysfire 2000: 8 different indexing programs (Ito, Dicvol, Treor, Taup, Kohl, Lzon, Fjzn, Losh) It’s good to have a wide variety of methods available: to cater for different types of problem to give a feel for the range of solutions out there and see which ones turn up repeatedly using different methods, either identically or as derivative cells Slide 22 Lachlan M. D. Cranswick

New Release - Crysfire 2002 August 2002 Now 9 indexing programs:
Ito, Dicvol, Treor, Taup, Kohl, Lzon, Fjzn, Losh, Mmap New features: Mmap for exploring solution-space and evaluating trial cells Le Page/Niggli reduced-cell summary Greater ease of use, especially for first-time users Better resilience, especially under the Windows/NT family (master program totally rewritten) Slide 23 Lachlan M. D. Cranswick

Why bother running more than one powder indexing program?
Maximize the possibility of indexing unknowns by taking advantage of different algorithms and different program implementations. Slide 24 Lachlan M. D. Cranswick

Powder Indexing - Routine Crysfire Example Run crysfire (giving the following screen)

Powder Indexing - Routine Crysfire Example Importing an XFIT peak file using the IM (Import command)

Powder Indexing - Routine Crysfire Example “lo” to load a CDT file estimate of expected unit cell volume is given Slide 27 Lachlan M. D. Cranswick

Powder Indexing - Routine Crysfire Example “in” to target an indexing program

Powder Indexing - Routine Crysfire Example target ITO with defaults

Powder Indexing - Routine Crysfire Example ITO runs

Powder Indexing - Routine Crysfire Example After Ito completes, press enter to see output file

Powder Indexing - Routine Crysfire Example Then “enter” again to see “one solution per line” summary

Powder Indexing - Routine Crysfire Example “Enter” again to see Le Page summary of reduced cells

Powder Indexing - Routine Crysfire Example
Repeat the sequence to run the remaining relevant indexing programs. Recommended sequence is actually: Taup, Dicvol high sym, Ito, FJZN, Treor, Kohl, Dicvol low sym, Lzon in to select and launch an indexing program look at the output file look at the summary file look at the Le Page summary file of reduced cells repeat Slide 34 Lachlan M. D. Cranswick

Powder Indexing - Routine Crysfire Example Finally: the complete summary file - 3332 trial solutions

Powder Indexing - Routine Crysfire Example Complete Le Page summary file of reduced cells trial solutions Slide 36 Lachlan M. D. Cranswick

Crysfire Self Calibration Bragg-Bretano Data
Sometimes it’s hard to be sure how far the beam is penetrating into the sample, giving an unknown sample-displacement error This can be addressed by trying self-calibration (SC) If indexing the uncorrected data has failed, try SC Select T (for specimen-displacement correction ratio) A list of candidates for T will be displayed, based on 1st/2nd-order line pairs If a particular ratio comes up several times and looks plausible, adopt it Save it (SA) in Crysfire format under a new name, so that it can be reloaded Do another cycle of indexing runs, this time with the “corrected” data Slide 37 Lachlan M. D. Cranswick

Crysfire Self Calibration Example
Self calibration output of an organometallic sample in histogram format Slide 38 Lachlan M. D. Cranswick

Crysfire Rescaling Most indexing program have evolved using a range of data with solutions between 500 and 1500 If you have cells outside this range, many indexing programs can fail A possible solution to still index large cells it to rescale the data by changing the wavelength Slide 39 Lachlan M. D. Cranswick

Crysfire Re-scaling Protein Data (from Bob von Dreele)
Input for RAWPLOT: ( Å) Crysfire Re-scaling Protein Data (from Bob von Dreele) Lysozyme – single peak fits for 24 reflections : Rescale factor = 0.1 Rescaled cell = a of ~7.9Å and c of ~3.8Å Unscaled cell = a of ~79Å and c of ~38Å Slide 40 Lachlan M. D. Cranswick

Crysfire Rescaling example Inorganic - on opening : Crysfire suggests rescaling

Ignoring the rescaling suggestion No obvious solutions

RS is the Rescale Command Crysfire will automatically change the filename and title

After running the indexing programs: MS, then U to unscale the summary file

Indexing using the suggested rescaling of 0. 5 An obvious cubic (23
Indexing using the suggested rescaling of 0.5 An obvious cubic ( A) solution found by Taup Slide 45 Lachlan M. D. Cranswick

Chekcell: Interpreting Crysfire Summary Files: Powder Indexing and Spacegroup Assignment
Crysfire interlinks with Chekcell for Windows (part of the LMGP suite for Windows by Jean Laugier and Bernard Bochu). Chekcell provides a graphical interface for manually and automatically suggesting a best cell/spacegroup combination using both FOM and algorithms relating to parsimony of superfluous HKLs. Slide 46 Lachlan M. D. Cranswick

Chekcell : easy to see non-matching or impurity peaks

Chekcell : automatic cell and spacegroup searching
can trudge through a single selected unitcell; or over 1000s of trial cells looking for the best cell and spacegroup combination based on parsimony of extra reflections criteria. Slide 48 Lachlan M. D. Cranswick

Chekcell: “integration” of Ton Spek and A
Chekcell: “integration” of Ton Spek and A. Meetsma’s Le Page (Crysfire 2001 now also provides a reduced-cell summary) Obtaining the Reduced Cell which in the past many powder indexing programs have not determined either reliably or at all Refer: "'Reduced Cells', M.J. Buerger, (Zeitschift fur Kristallographie, BD 109, S (1957)” Crysfire 2001 gives a LePage overview Chekcell displays a fuller analysis Efficient Sub-cell and super-cell searching, then easy reviewing of newly derived cells within the Chekcell interface Slide 49 Lachlan M. D. Cranswick

Chekcell: GUI Cell transformation
Easily transform cells and test them withing Chekcell Knows about common transformations Can manually look at sub-cells and super-cells Slide 50 Lachlan M. D. Cranswick

Chekcell: Density / Z/ Mol. Vol explorer
Easily explore values of Z, density and estimated molecular volume - comparing with your found trial cells. Slide 51 Lachlan M. D. Cranswick

Chekcell: example of it running Load the raw diffraction data

Chekcell: example of it running Load the peak position file

Chekcell: example of it running Load the Crysfire summary file

Chekcell: example of it running Use the tools to evaluate the trial cells

Crysfire / Chekcell: indexing powder Protein data
Using the “Lepage” feature in Chekcell Can find the correct rhombohedral cell as published in: R. B. Von Dreele, P. W. Stephens, G. D. Smith and R. H. Blessing, "The first protein crystal structure determined from high-resolution X-ray powder diffraction data: a variant of T3R3 human insulin-zinc complex produced by grinding", Acta Cryst. (2000). D56, Slide 56 Lachlan M. D. Cranswick

Crysfire / Chekcell: indexing powder Protein data
Even on rescaled data, if Crysfire and the various indexing programs do not find the “true cell”, Chekcell and possibly can find a derivative cell which LePage (combined with Chekcell’s “parsimony and superflous reflections” criteria), can find the true cell. In the case of reindexing of the protein data: Crysfire and Dicvol finds Orthorhomic P222 or PMM2 or PMMM : 157 hkls to match 41 reflections LePage followed by Chekcell “parsimony check” then finds: Hexagonal setting Rhombohedral R-3 or R3 etc : 60 hkls to match 41 reflections Slide 57 Lachlan M. D. Cranswick

MMAP Mmap explores sections of solution-space (e.g. sections with varying alpha* and beta*, holding the other 4 parameters constant) The results are displayed as a map, with the high-ground colored It lists all the peaks in the map and refines them - each is a trial solution So it can act as an indexing program in its own right (taking the basis set containing the first 4 constants from Lzon’s output) This offers another way to search for trial cells Use the new “LC” (Load a trial cell from the Crysfire summary file) to then run MMAP (using the MM command) on it. Slide 58 Lachlan M. D. Cranswick

MMAP - what does the output look like?
Example MMap thumbnail output from a high FOM trial cell Slide 59 Lachlan M. D. Cranswick

MMAP - what does the output look like?
Example MMap output from a high FOM trial cell Slide 60 Lachlan M. D. Cranswick

MMAP But another use is for checking out trial solutions taken from the summary lists generated by other indexing programs The usual guides to which solutions are the most promising are ones like figures of merit, numbers of lines indexed, etc., but only at the position of the refined cell in the map That’s like having a list of high points in a landscape, and trying to tell tall buildings from natural features with only their heights to go on Knowing the surroundings of the high-point tells us which are man-made, and similarly which Mmap peak corresponds to the physical solution Slide 61 Lachlan M. D. Cranswick

Height of 80 Height of 78 Height of 65
MMAP - which of these objects is man made? Using peak height as the selection criteria. Height of 80 Height of 78 Height of 65 Slide 62 Lachlan M. D. Cranswick

MMAP - which of these peaks is man made? 2
It’s obvious once you can see the landscape Slide 63 Lachlan M. D. Cranswick

Analogous problem with powder indexing
Traditional indexing only gives you the numbers (and possibly a Chekcell style fit) where a large number of trial cells can give reasonable matches Mmap shows you the actual “landscape” Slide 64 Lachlan M. D. Cranswick

An Mmap landscape Quick scan of an alpha*/beta* section for some real data for a triclinic cell (a finely-divided triclinic biological sample showing some line broadening) There are a number of high points scattered across the map Each of these peaks is a potential solution (+others others out of section) Slide 65 Lachlan M. D. Cranswick

Mmap Looking at some real data and see how figure-of-merit lists can be illuminated by looking at the landscapes that they come from. Slide 66 Lachlan M. D. Cranswick

Mmap After refinement, though one peak has reached a figure of merit of 21, it still has a long list of competitors - no one solution really stands out There are 48 peaks in the whole list, all non-equivalent 17 of these have M>10 and index all of the first 20 lines Slide 67 Lachlan M. D. Cranswick

Mmap : Is the following a good solution?
Here is the traditional set of information that we have for solution 1 from that list: a = A alpha = deg b = A beta = deg c = A gamma = deg V = A3 M20 = 21.02 Slide 68 Lachlan M. D. Cranswick

Mmap : Yes looks a good solution
Here is a magnification of the region around map-peak 1 (M=21.0), reloaded into Crysfire from the Mmap summary file using LC and then selecting a cell. It’s relatively compact (though sitting on a lowish diagonal ridge) Slide 69 Lachlan M. D. Cranswick

Mmap : Is the following a good solution?
Similarly for the solution that corresponds to map-peak 2: a = A alpha = deg b = A beta = deg c = A gamma = deg V = A3 M20 = 16.05 Slide 70 Lachlan M. D. Cranswick

Mmap A similar magnified map around map-peak 2 (M=16.0)
This is revealed to be less well defined as well as lower, with its central region extending as a broad ridge right off the top of the map Slide 71 Lachlan M. D. Cranswick

Mmap: Is the following a good solution?
And for map-peak 3: a = A alpha = deg b = A beta = deg c = A gamma = deg V = A3 M20 = 14.57 Slide 72 Lachlan M. D. Cranswick

Mmap Map-peak 3 (M=14.6) is broader still, and also drifts off the top of the map Slide 73 Lachlan M. D. Cranswick

Mmap We can also avoid wasting time on landscapes that are broad and featureless, indicating data problems or wrong initial assumptions, and so not worth pursuing Slide 74 Lachlan M. D. Cranswick

MCMaile by Armel Le Bail
Developed in September 2002 (on from the ESPOIR code) GPL’d (free and you get the source code) Whole profile Monte Carlo and Grid Search methods using a pattern reconstituted from the peak list Columnar peak shape - can increase/decrease width Can make “important” trace peaks more likely to be part of a solution by increasing their intensities. Insensitive to impurity peaks 20,000 tests per second - but can still take many hours Thus a method of last resort Slide 75 Lachlan M. D. Cranswick

A MCMaile ASCII input file

MCMaile is running Slide 77
Lachlan M. D. Cranswick

MCMaile output files Chekcell *.ckm summary file of all trial cells and Fullprof PRF profile file of top solution: viewable in Winplotr Slide 78 Lachlan M. D. Cranswick

MCMaile : on large cubic
Finds cubic cell easily - even with trace “impurity” peaks Via outputted Chekcell *.ckm summary file. Top solution is not correct solution (possible effect of impurity peaks) Slide 79 Lachlan M. D. Cranswick

MCMaile : on large cubic
Finds cubic cell easily - even with trace “impurity” peaks Via outputted Chekcell *.ckm summary file. Second set of solutions is correct Slide 80 Lachlan M. D. Cranswick

SDPDRR-II (Structure Determination by Powder Diffractometry Round Robin - 2 )
WWW: Started: Monday 9th September Part 1 (powder indexing): Start: Monday 9th September Finish: Sunday 13th October 8 samples 1 - 3 : Powder indexing and structure solution 4 - 8 : Powder Indexing only > 100 downloads of the data (samples 1 to 3) Slide 81 Lachlan M. D. Cranswick

SDPDRR-II - Indexing Results
WWW: 6 returns/100 downloads = 6% return rate Slide 82 Lachlan M. D. Cranswick

SDPDRR-II - Sample 1 WWW: http://sdpd.univ-lemans.fr/sdpdrr2/results/
Organisers: Reduced cell: P1: P2: P3: Reduced cell: P4: No solution P5: P6: Slide 83 Lachlan M. D. Cranswick

Organisers: Reduced cell: P1: P2: P3: P4: P5: P6: Slide 84 Lachlan M. D. Cranswick

Organisers: (vol 6734Å3) P1: (Tet Å3) P2: P3: (Tet Å3) P4: No Solution P5: P6: Slide 85 Lachlan M. D. Cranswick

SDPDRR-II - Sample 3 Tetragonal or Cubic?
2 participants (1 and 3) obtained the same tetragonal cell instead of the correct cubic. Possibly due to default volume restrictions in the programs used(?) What happens if you run LePage (via Chekcell) followed by a “parsimony of extra reflections” check on the tetragonal solution Slide 86 Lachlan M. D. Cranswick

SDPDRR-II - Sample 3: Tetragonal: 1 peak unmatched - 46 hkl’s (P42MC et al) to match 25 reflections

SDPDRR-II - Sample 3: Tetragonal: Running LePage shows a cubic cell (18.885Å)

SDPDRR-II - Sample 3: Visual inspection of cubic cell implies “bad”peak could still be an impurity

SDPDRR-II - Sample 3: Cubic: 37 hkl’s to match 25 reflections (I23 et al) (vs 46 hkl’s in tetragonal) Slide 90 Lachlan M. D. Cranswick

SDPDRR-II - Samples 4 to 8 WWW: Only one response - using the EFLECH/Index software of Joerg Bergmann ( S4: none suggested S5: S6: none suggested S7: S8: Summary: Powder indexing is not easy and not routine! Slide 91 Lachlan M. D. Cranswick

Be on the lookout for bugs in the Software
Be on the lookout for bugs in the Software! Found in LePage - within Chekcell Slide 92 Lachlan M. D. Cranswick

The Future The message has got through that indexing has become a bottleneck for solving structures from powder diffraction data. New Indexing programs are being developed. MCMaille (Free GPL’d - get the source code as well) Bruker SVD Indexing (commercial) Accerlys Indexing program (commercial) EFLECH/Index (new developments due to the SDPDRR-2) Slide 93 Lachlan M. D. Cranswick

Conclusion Don’t give up if your lab’s favorite indexing program doesn’t work on a particular dataset Suites like Crysfire offer a wide range of indexing tools Follow on with Chekcell to help pin down the correct physical cell If that does not work - whole profile methods such as MCMaille (still using Chekcell to evaluate trial solutions) Relevant web links: CCP14 Summary Page: Crysfire: Chekcell: McMaille: Slide 94 Lachlan M. D. Cranswick

Re-stating the obvious: To solve structures from powder diffraction, first they must be indexed! Lachlan M. D. Cranswick CCP14 (Collaborative Computation.

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Re-stating the obvious: To solve structures from powder diffraction, first they must be indexed! Lachlan M. D. Cranswick CCP14 (Collaborative Computation.

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Presentation on theme: "Re-stating the obvious: To solve structures from powder diffraction, first they must be indexed! Lachlan M. D. Cranswick CCP14 (Collaborative Computation."— Presentation transcript:

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