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Bruker AXS Company Presentation

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PolySNAP 3 is the successor product to the groundbreaking PolySNAP ... Data formats: RAW, Powder-CIF, ASCII, CSV, Raman SPC, Opus. 8/10/09. Bruker Confidential ... – PowerPoint PPT presentation

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Title: Bruker AXS Company Presentation


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Introducing PolySNAP 3
  • PolySNAP 3 is the successor product to the
    groundbreaking PolySNAP
  • PolySNAP provided powerful cluster analysis tools
    and clean, elegant and informative graphic
    displays to allow for high-throughput analysis of
    Powder X-Ray Diffraction patterns.
  • PolySNAP 3 has the same powerful tools, but
    allows them to be employed to ANY kind of numeric
    data
  • PXRD, Raman, IR, DSC, Melting Points. Anything!
  • PolySNAP 3 allows up to four different datasets
    to be analysed simultaneously
  • (or a single dataset with up to four different
    processing options)
  • PolySNAP 3 combines the results from individual
    datasets to show the overall picture of whats
    going on

3
Multiple Datasets
  • Combined XRPD Raman instruments now available
    D8 Spectrolab
  • Applying multiple techniques to the same samples
    helps give additional information to work with
  • How would we actually combine results from two
    such different techniques ?
  • Automatically calculate optimal weighting for
    each entry in each dataset
  • Much more powerful than manually averaging
    results

4
Methodology- PXRD Raman
Full profile matching all patterns against all
patterns
n XRPD Patterns
nxn Correlation Matrix
XRD results
nxn Distance Matrix
Combined results
nxn Distance Matrix
Combine
Full profile matching all patterns against all
patterns
n Raman Patterns
nxn Correlation Matrix
nxn Distance Matrix
Raman results
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Run ona single dataset
  • Just like PolySNAP
  • - but can now select
    different kinds of input
  • - Separate automatic
    pre-processing defaults for each type of
    data
  • - also new is the
    ability to transform spectra
  • - either Fourier
    transform or derivative (1st or 2nd)
  • - can also specify a
    location to load sample image files from
    (JPEG files)

8
Analysis ToolsDendrogram
  • Similar patterns are clustered together
  • Position of Cut-Level partitions the data into
    separate clusters
  • Adjust the cut-level to best
  • describe the data

Too high?
Too low?
Just right
9
Analysis Tools3D MMDS Plot
  • Each sphere is a pattern
  • The closer together two spheres are, the more
    similar they are
  • Similar patterns clump together
  • Different patterns are far apart
  • Easy to spot outliers at a glance
  • As with all PolySNAP graphics, you can
  • Zoom in, zoom out, rotate
  • Hide and show and drag labels
  • Change rendering quality
  • Change colour of background, axes etc.
  • Produce figures for publication

10
Multiple MethodsConsistent Colouring
  • Changing the clustering in the dendrogram
    automatically updates the colours in the other
    plots.
  • Cluster colours from dendrogram are used on MMDS
    plot so you can compare the groupings from both
    methods. Same results from both increases
    confidence in the accuracy of the results.

11
Analysis ToolsQuantitative Analysis
  • Given reference phases, PolySNAP can identify
    possible mixtures and perform fast quantitative
    analysis. Results are shown on the Cell Display
    in the form of Pie Charts or Stacks.

12
Analysis ToolsCell Display
  • Cell Display is also useful for seeing the
    clustering result colours superimposed on e.g.
    the layout of an original 96 well plate from a
    high-throughput system.

13
Analysis Tools6D Plots Sample Preparation
Information
  • Automatically read sample preparation information
    from data file headers or standalone CSV file
  • Plot any combination of this information as
    different variables in the 3D plot vary size,
    shape and colour of plotted points
  • e.g. show different solvents as different
  • shapes
  • Vary the shape size with temperature,
  • the colour with time
  • See what initial variables correlate to
  • resulting materials

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Analysis ToolsValidation
  • Check the validity of the clustering using
    powerful statistical tests
  • Silhouettes are these cluster memberships
    reasonable?
  • Fuzzy Clustering should this pattern be in a
    different cluster?
  • Scree plots how many clusters are needed to
    explain the data?
  • Minimum Spanning Trees an alternative way to
    construct clusters
  • Silhouettes example
  • Pattern 21 scores poorly as a member of this
    cluster
  • it is the least tightly connected in the
    dendrogram
  • This turns out to be a mixture, rather than a
    pure phase

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Analysis ToolsHigh Dimensionality Viewers
  • Advanced visualisers to test if the clustering
    holds true in higher dimensional space
  • Animated dataset Grand Tour
  • Parallel Coordinates Plots
  • Space Explorer View

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Analysis ToolsPattern Thumbnail Viewer
  • Thumbnail colouring updated as dendrogram cut
    level is changed
  • Helps show which samples are grouped together in
    which clusters
  • Useful visual overview of smaller datasets

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Analysis ToolsColour-coded Numeric Results
  • Draws the eye to help see patterns in the data
  • User-controlled colour scheme and cut-off points

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Analysis ToolsPeak Overlap Viewer
  • Overview of peak intensities and positions
    throughout the entire dataset
  • Colouring can be user controlled
  • See at a glance if peaks coincide or overlap at
    similar angles

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Run onMultiple Datasets
  • 3 potential ways of working with PolySNAP
  • 1. Multiple types of data have been collected on
    the same samples
  • e.g. there is a set of 96 samples, from which
    have been collected both PXRD and Raman spectra
  • Examine the clustering from the PXRD, and the
    Raman, and the combined PXRD Raman
  • Do the different methods agree? Do they
    contradict each other?
  • 2. Multiple instances of the same type of data
    collected
  • e.g. PXRD patterns collected on the same samples
    at different times, or under different conditions
  • 3. Investigate a single dataset under different
    processing options
  • Compare side-by-side what difference turning
    background subtraction, etc. on makes to the
    final results

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Run onMultiple Datasets
Select PXRD and choose data location
Select Raman and choose data location
Select any different processing options for each
dataset
Click OK to start
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How much data?
  • For each individual dataset, PolySNAP can analyse
    up to 1,500 samples at once
  • Up to four different datasets can be input for
    each run
  • The datasets can be any combination of
  • PXRD
  • Raman
  • DSC
  • IR
  • Other spectra data
  • Numeric
  • Numeric can be a correlation matrix, or raw
    numeric data relating to the samples being
    analysed
  • e.g. Melting points
  • Data formats RAW, Powder-CIF, ASCII, CSV, Raman
    SPC, Opus,

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Results Screen
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Results Screen
Click on the dataset name to switch between
different sets of results here, choose between
PXRD and Raman individually, or the combined
results
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Results Screen
Click on the tabs to see different display
screens to help you interpret the results
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Results Screen
Select a sample or samples in the results screen
to see information about it and its profile
displayed below
Click the vertical tabs to switch between seeing
the PXRD or Raman profile for the currently
selected patterns
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Results Screen
  • Compare the clustering results from each datatype
    in turn

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Results Screen
  • Look at both the PXRD and Raman spectra to make
    sure this clustering looks sensible

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Results Screen
Or select up to four multiple datasets to view
results side by side
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Multiple ScreensMultiple Windows
  • Customers with multiple monitors can open
    separate results screens on each one, allowing
    easy comparison of different results side-by-side

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Combined DatasetsExample 1
  • 48 patterns of 3 forms of Sulfathiazol (forms 2,
    3 and 4)
  • PXRD and Raman data collected
  • PXRD Data only
  • Splits form 3 into 2 separate clusters

Form 2
Form 3
Form 3
Form 4
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Combined DatasetsExample 1
  • 48 patterns of 3 forms of Sulfathiazol (forms 2,
    3 and 4)
  • PXRD and Raman data collected
  • Raman Data only
  • Doesnt distinguish between Form 3 and Form 4

Form 2
Forms 3 4
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Combined DatasetsExample 1
  • 48 patterns of 3 forms of Sulfathiazol (forms 2,
    3 and 4)
  • PXRD and Raman data collected
  • Combined PXRD Raman using Automatic Weights
  • Does much better than the individual methods alone

Form 3
Form 4
Form 2
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Combine ResultsExample 2
  • 46 patterns of 2 anhydrous forms of
    Carbamazepeine (Forms 1 3)
  • PXRD and Raman data collected
  • PXRD Data only
  • E3 and F7 in different clusters

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Combine ResultsExample 2
  • 46 patterns of 2 anhydrous forms of
    Carbamazepeine (Forms 1 3)
  • PXRD and Raman data collected
  • Raman Data only
  • E3 and F7 in same cluster!

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Combine ResultsExample 2
  • 46 patterns of 2 anhydrous forms of
    Carbamazepeine (Forms 1 3)
  • PXRD and Raman data collected
  • PXRDRaman Data Combined
  • F7 highlighted as an outlier due to this
    inconsistency

  • Other outliers (yellow) are
    mixtures of the 2 forms

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Combined Results
  • Matching method does very well in distinguishing
    forms automatically using either Raman or PXRD
    data
  • Combined results using Automatic Weights seem to
    do better than either PXRD or Raman individually
  • Identification of pure phases / mixtures improved
  • Use of combined data highlights any
    inconsistencies in separate analyses
  • Such inconsistencies would not be obvious with
    only one data source
  • User can then examine outliers manually in detail
  • Seeing similar clustering from multiple original
    data sources increases confidence in the results

37
Quality Control
  • Given a set of reference patterns, new patterns
    can be considered to be similar enough to the
    references to pass, or different enough to
    fail.
  • Graphical representation
  • new samples within the green
  • Pass surface are OK, samples
  • falling outside the surface fail.

38
Pre-screening
  • Have a large dataset of existing patterns
    (100,000) ?
  • Compare a single new unknown sample to the large
    dataset in minutes
  • Get back a list of top 50 best matches to the
    unknown
  • Perform PolySNAP clustering visualisation on
    the best matches
  • Pre-screen a large dataset down to a smaller,
    more relevant subset

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Other Features
  • Automatic Report Writer
  • Ability to run from command line - perform
    analysis as part of a script
  • Integration with other Bruker software
  • Audit-trail detailed logfile
  • Raw numeric results available for interrogation
  • Results automatically archived to encrypted file
  • Full manual and tutorial provided
  • View sample images alongside patterns
  • Manual analysis mode
  • Compare one pattern to many
  • Detailed numeric breakdown of results

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Dealing withLarge Datasets
  • Specially designed tools for dealing with large,
    complex datasets
  • Select subsets for re-analysis
  • View simplified dendrograms and 3D plots
  • Show/Hide selected clusters
  • Hide all but current cluster being investigated
  • Transparency options
  • Search options locate individual patterns of
    interest

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PolySNAP M
  • Ideal for single, smaller datasets (up to 96
    patterns)
  • PolySNAP M has dendrograms, 3D plots, and manual
    analysis mode

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Which PolySNAPDo I Need?
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Support Services
  • Training
  • One and two-day in-depth training packages
    available
  • Gain detailed knowledge of advanced program
    functions
  • Use advanced options with trickier datasets with
    confidence
  • Look at your own data with
  • Customisation
  • Personalised modifications to suit
    company-specific workflows
  • Interface alterations
  • Integration with other custom-software

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www.bruker-axs.com
www.chem.gla.ac.uk/snap
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