Data Mining – Trace Phase Analysis

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Transcript Data Mining – Trace Phase Analysis

Data Mining – Minor Phase Analysis

This tutorial was created from a presentation by Dr. James Kaduk, Senior Research Associate, INEOS Technologies. The presentation was given at an ICDD workshop held during the 2008 International Union of Crystallography Meeting in Osaka, Japan. The tutorial includes three case histories of industrial problems solved using the PDF-4+ database and some creative thinking!

The ICDD is grateful to both Dr. Kaduk and INEOS Technologies for allowing the ICDD to use their data for this tutorial.

Examples of Data Mining Applications of the Powder Diffraction File in Industrial Problem Solving

James A. Kaduk Senior Research Associate An alytical S ciences R esearch S ervices INEOS Technologies [email protected]

A Vanadium Phosphate Catalyst for the Oxidation of Butane to Maleic Anhydride

40 [g oed80.raw] 21228-95-5 (40,40,0.3) JAK [g oed80.raw] 21228-95-5 (40,40,0.3) JAK 10 x10^3 30 20 10 20 30 40 01-089-8338> (V O)2(P 2O7) - V anadium Oxide P hos phate 01-085-2281> (V O)2(P 2O7) - V anadyl P hos phate 01-083-2388> (V O)2(P 2O7) - V anadium Oxide P hos phate 70 80 90 50 Two-Theta (deg) 60 From the top, raw data scan, background subtracted scan and then the phase identification match to phases in the Powder Diffraction File. The reference phases are represented as stick figures. The identification accounts for some of the peaks, but not all peaks in the pattern.

Locate peaks by interactive deconvolution, and create GOED80.PEAK

GOED80.PEAK

7.2107 10 6.3038 15 5.6645 7 4.8107 12 4.4577 1 4.2699 1 4.0957 2 3.9854 4 3.8799 70 3.5823 9 3.2904 1 3.1447 100 3.0760 7 3.0487 4 3.0027 24 2.9864 28 2.6625 14 2.6141 1 2.4649 2 2.4415 15 2.3997 2 2.3665 5 2.2550 1 2.2123 1 2.0946 19 2.0780 5 1.9916 1 1.9730 1 1.9377 7 1.9026 2 1.8420 9 1.8293 2 1.7939 1 1.7503 1 1.7147 1 1.6488 3 1.6373 5 1.6257 1 1.6007 3 1.5781 10 1.5604 1 1.5232 1 1.5073 2 1.4925 1 1.4757 5 1.4611 5 1.4458 1 1.4210 3 1.3920 1 1.3840 4 1.3525 2

Import into SIeve+

Note: SIeve+ is the Search and Identification program, from ICDD, that is used with PDF-4+ databases. It can utilize a d,I file, such as the one in this example, or use an experimental data file.

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00-050-0380> (VO)2P2O7 - Vanadyl Phos phate 5.0

x10^3 10 20 30 40 50 Two-Theta (deg) 60 70 80 90

Only weak peaks left. Redo Hanawalt/Fink search, or use other capabilities …

There is a peak at 7.2107 Å. Limit our search to phases containing just V, P, O, and H, and which have a strong peak 7.16 <

d

< 7.26 Å.

Note: In this real example, supplementary XRF data, taken at INEOS, limited the number of elements in the specimen. This information can be used in the search process in combination with the location of a single d-spacing.

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x10^3 10 20 30 40 50 00-050-0380> (VO)2P2O7 - Vanadyl Phos phate 00-047-0967> H4V3P3O16.5·xH2O - Hydrogen Vanadium Phos phate Hydrate 70 80 90 Two-Theta (deg) 60

At the time of this analysis, no structure had been reported for H 4 V 3 P 3 O 16.5

(H 2 O) x . Search the ICSD for phases containing only V, P, O, and H.

Found ICSD entry 92847

This subsequently was entered into the PDF as PDF 01-074-2749!

Boolean search on “just” H,V, P and O with a strong line at ~7.21

Å.

There are still peaks at 3.5823 and 3.0760Å.

Look for phases which have strong peaks 3.55-3.61 and 3.05-3.11 Å.

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10 20 30 40 50 00-050-0380> (VO)2P2O7 - Vanadyl Phos phate 00-047-0967> H4V3P3O16.5·xH2O - Hydrogen Vanadium Phos phate Hydrate 01-070-0265> V1.08P0.92O5 - Vanadium Phos phorus Oxide 70 80 90 Two-Theta (deg) 60

Carry out a Rietveld Refinement

Note: In this example, the identified phases were sourced from the ICSD data. Using the cross references in the PDF database, the atomic coordinates for a Rietveld refinement can be extracted from the ICSD database or from the original references.

Alternatively, in PDF-4+ for Rietveld refinement PDF 04-008-8054 replaces 01-070-0265 PDF 04-011-5579 replaces 00-050-0380 The replacements are identified through PDF’s cross references located in both entries.

Rietveld Refinements

In all the examples, Jim Kaduk follows phase identification with Rietveld refinement for quantitative analysis. This requires that each entry has a set of atomic coordinates. There are several ways to get this information

1.

Directly from PDF-4+ in the Structure tab, as shown above. PDF-4+ contains 114,630 data sets with atomic coordinates.

2 .

From the literature reference in the Experimental tab.

3.

From the cross reference collection code found in the comments tab, or a cross reference structure found in the Miscellaneous tab.

There is still a peak at 3.985Å.

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10 20 30 40 00-050-0380> (VO)2P2O7 - Vanadyl Phos phate 50 00-047-0967> H4V3P3O16.5·xH2O - Hydrogen Vanadium Phos phate Hydrate 01-070-0265> V1.08P0.92O5 - Vanadium Phos phorus Oxide 01-084-0048> VO(PO3)2 - Phos phate Vanadium Oxide 70 80 90 Two-Theta (deg) 60

Add to the refinement

The quantitative analysis is:

(VO) 2 P 2 O 7 84.8(1) wt% H 0.6

(VO) 3 (PO 4 ) 3 (H 2 O) 7  -VOPO 4 β-VO(PO 3 ) 2 5.9(1) wt% 5.6(1) wt% 3.7(1) wt%

A Deactivated Pd/C Hydrogenation Catalyst

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[nube157.raw] 22247-126D-(UCB-0308-014)/ Fines/ (40,40,0.3) TN 10.0

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x10 3 10 20 30 40 50 Two-Theta (deg) 60 00-046-1043> Palladium - Pd 70 80 90 Automated identification finds the Pd catalyst, but there are clearly additional phases in the pattern. There is a characteristic unidentified long line, shown by the arrow, at 4.05

Å.

Pd and long line 4.05

0.02

Å

The search finds a number of Pd alloys, most have the formula XPd3.

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x10 3 10 20 30 40 50 Two-Theta (deg) 60 00-046-1043> Palladium - Pd 00-050-1631> Zv y agintsev ite - PbPd 70 80 90 The prior search suggested that an XRF analysis would be appropriate (to find X) and Pb was found in high concentration. PbPd3 was easily identified (above).

The source of Pb in the plant was found and removed, solving the deactivation problem.

Rust from a bag filter in a refinery unit

150 100 50 0 350 300 250 200 [wint190.rd] GF-111 filter 8/12/04 red (40,30,zbc,tap 10 20 30 40 50 Two-Theta (deg) 60 70 80 90

Locate the peaks by interactive deconvolution, and create WINT190.PEAK

WINT190.PEAK

6.2904 12 4.8517 12 4.1888 1 3.6883 7 3.4385 2 3.2950 11 3.1251 15 2.9682 30 2.8207 2 2.7040 22 2.6365 2 2.5819 3 2.5309 100 2.5196 22 2.4723 9 2.4233 7 2.3596 4 2.2371 5 2.2097 5 2.0978 20 1.9350 5 1.9118 6 1.8431 8 1.7118 5 1.6968 12 1.6554 3 1.6300 6 1.6149 23 1.5982 1 1.5638 1 1.5244 2 1.4839 32 1.4546 6

Import into SIeve+

Data screen for SIeve+, candidate phases are shown at the top, with matched lines in red. Identified phases are shown at the bottom left. Matched lines for each identified phase are shown on the bottom right, with matches in blue, and peaks to be matched in black. The candidate list strongly suggests ZnS as a match for the unmatched lines!

Magnetite, hematite, and lepidocrocite were easy to identify (and expected components of rust), but now we have to think …

ZnS would be very strange here, so look far down (>100 hits) the list.

We start seeing

F

-cubic things with a = 5.407

Å . Do an author’s cell search for compounds with lattice parameter around this value…

Selected criteria for a search using Cubic structures with a 5.40 cell edge

Could this be CeO

2

? Bulk chemical analysis shows 2.1 wt% Ce, so, yes!

And this is what the customer wanted to know!

Note: The customer suspected that this was a contaminant, but did not tell the analyst until after the analysis was conducted!

All the results, including the CeO2, are identified. SIeve+ also provides integrated intensities and I/Ic values enabling a quantitative analysis by the Reference Intensity Ratio method.

Simulation of the reference pattern identification as compared to the raw data – all peaks identified and accounted for.

Compare the RIR concentrations to those from a Rietveld refinement

Phase Sieve+ GSAS Magnetite Hematite 55 wt% 19 39.2(4) 32.4(6) Cerianite 13 2.7(1) Lepidocrocite 12 25.6(6) Note: SIeve+ provides a scaled simulation, not a refinement. Improved RIR results would be expected from a refinement. Refined results are not provided by SIeve+, but are provided with many OEM data analysis programs.

Conclusions

These examples demonstrate how different pieces of knowledge about a sample can be combined, with the aid of data mining, to solve complex problems.

In the three examples, the unknown was always a minor phase with a small number of diffraction peaks identified through a residual peak analysis. The use of XRF data, and/or a knowledge of the specimen history, was cross referenced with the diffraction peaks to greatly reduce the number of candidate materials that fit all the known observations.

Thank you for viewing our tutorial. Additional tutorials are available at the ICDD web site ( www.icdd.com

).

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