Diffraction, Non-Crystallinity, and the PDF Database

Cyrus E. Crowder, ICDDTim Fawcett, ICDD

This document was presented at PPXRD -Pharmaceutical Powder X-ray Diffraction Symposium

Sponsored by The International Centre for Diffraction Data

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Classical Diffraction

• Classic ‘Bragg’ scattering is characterized by discrete peaks arising from long-range crystallographically ordered planes:

λ = 2dhkl sinθhkl• The 2009 PDF databases have > 660,000 entries based

on the concept of discrete Bragg peaks arising from crystalline structures.

• The existing concept of ‘Phase Identification’ is based on matching accurately-determined positions and intensities of peaks in an experimental patterns to those for PDF database entries.

Classical XRPD NaCl – An Example

1 1 1 2 0 0 2 2 0

2 2 2

3 1 1

The XRPD Pattern of a Common Pharmaceutical Excipient

The process of identifying this material by conventional XRPD search/match techniques is compromised by the small number of clearly defined diffraction maxima and the difficulty in specifying the precise positions of these maxima. Further, these ‘maxima’ are likely shifted from the true underlying positions of the major Bragg peaks due to the significant overlap.

Use of full pattern matching for phase identification

• The ICDD has begun compiling a database (PD3) of XRPD profiles for such materials.

• Such a database can be used for manual comparison with an experimental pattern, however manual comparisons with larger databases for identifying true unknown materials would be slow and subjective.

• An automated full-pattern comparison would be desirable to screen the database for most-likely matches.

The Integral Index

• The Integral Index is a numerical value based on a point-by-point comparison of two digitized X-ray diffraction pattern This numerical value ranges from 0-100 and is based on the Hofmann and Kuleshova similarity index [1]:

• The lower the index value, the better the match, giving 0 a perfect match and 100 a complete non-match.

• We can use this relationship to rank the match between full patterns from a given database set with the pattern from the unknown material

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Example Using Integral Index to Identify Nanocrystalline Material

• To facilitate comparison, the background is removed before computing the integral indices.

• To facilitate speed, the database is limited to a likely subset of entries, in this case anything with cellulose in the name.

• If unsuccessful, other subfiles, i.e., polymers, fillers, or forensics, could be specified.

Perform Integral Index Calculations

• An estimated crystallite size parameter is used to compute comparible FWHMs for peaks, in this case, 3.5 nm.

• The software simulates a pattern for each database entry, using the d-space and intensity values.

• Each simulated database pattern is compared with the unknown pattern to generate integral index values.

Patterns Generated from Crystal Structure Where Available

References for Form I alpha,Form I beta and Form II

Simulation of microcrystallinestates of cellulose

Via PDF-4+

Scardi, LeoniFaber

PDF 00-056-1717 Cell IIPDF 00-056-1718 Cell I betaPDF 00-056-1719 Cell I alpha

Patterns Generated from Experimental d-I list if Crystal Structure is Not Available

Use of Integral Index

Integral Index = 2.26Cellulose 1β

Comparing with all 16 PDF experimental entries that contain ‘cellulose’ in the name, the integral index values vary from 2.26 up to 19.28 for these entries.

The best integral index fit is with 50-2241 – cellulose Iβ.

Comparison of Simulated Cellulose Patterns to Experimental Pattern

Cellulose IβIntegral Index = 2.26

Cellulose IIIntegral Index = 5.93

Red – experimental pattern Blue – ‘Standard’ database pattern

Clearly, the cellulose 1β polymorph is a better match than the cellulose II polymorph.

Non-crystalline Material

This is an X-ray ‘diffraction’ pattern for amorphous cellulose (Sigma Cellulose ground 13 hours). The same pattern is obtained after long periods of grinding, regardless of whether the starting cellulose was form Iα, Iβ, or II. (Courtesy Ewa Bucher, International Paper)

The lack of long range order means we have no conventional “Bragg” diffraction, but instead, rather broad features based on the distribution of interatomic distances within the disordered structure.

Nanocrystalline Cellulose Iα?

Comparison of X-ray diffraction patterns for amorphous cellulose and that for the cellulose Iα crystalline form with a simulated crystallite size of 1.5 nm.

Nanocrystalline Cellulose Iβ?

Comparison of X-ray diffraction patterns for amorphous cellulose and that for the cellulose Iβ crystalline form with a simulated crystallite size of 1.5 nm.

Nanocrystalline Cellulose II?

Comparison of X-ray diffraction patterns for amorphous cellulose and that for the cellulose II crystalline form with a simulated crystallite size of 1.5 nm.

Amorphous Standards

• Clearly the database should be expanded to include full patterns for standard amorphous materials since these cannot be generated from Bragg peak positions or crystallographic information. 

• This would allow integral index comparisons to be performed for both amorphous standards as well as nanocrystalline variations of crystalline materials already in the database.

Raw Polymer Pattern for Identification using Integral Index

Background Removal

Integral Index Calculations for Polymer Pattern

PDF-4+ 2009 database searched for entries containing ‘poly’ in the name and having elements only within the set of C, H, N, O, F, and Cl. Found: 651

Using a crystallite size of ~15 nm, Integral Index values were computed for this experimental pattern that ranged from ~2.5 to 45. (Roughly 20 seconds to compute on a 2-year-old Dell Inspiron.)

The top three are examined closer on the next slide.

Integral Index Results for Polymer

Semi-crystalline Polypropylene

Crystalline Polypropylene

Semi-crystalline Polypropylene

Polymers such as these are really 2-phase systems, one being crystalline, the other being amorphous.

Unlike polypropylene, many have only one or two significant Bragg peaks making conventional search/match identification difficult.

Automated full pattern comparisons have the potential to be a better identification tool for XRPD patterns of many polymers.

Disordered Structures

Faulted clay materials

The Editorial Challenge of a “Full Pattern” Database

• How many ‘different’ entries are needed for a given material (i.e. chain branching, molecular weight, melting point, degree of crystallinity, etc)?

St. Johns Wort

Echinacea Lipoic Acid

Powdered Bone

Benadryl

Nanomaterialsand blends

Effexor

Cough DropSaw Palmetto

3 SourcesCellulose*

*Courtesy of Ewa BucherInternational Paper

SunTheanine

Amorphous Materials and Blends

Tools that assist in identifying materials with poor crystallinity

• Data and databases• Simulations – crystallite size, pair distribution

functions, cluster analyses, total pattern fitting, “random-walk”models, Rietveld refinement,integral index

• Any knowledge of specimen chemistry, processing and composition

• Complimentary data – melting point, infrared,nmr, functional groups