84 COMPUTER PROGRAM ABSTRACTS Computer Program Abstracts The category Computer Program Abstracts provides a rapid means of communicating up-to-date informa- tion concerning both new programs or systems and significant updates to existing ones. Following nor- mal submission, a Computer Program Abstract will be reviewed by one or two members of the IUCr Commission on Crystallographic Computing. It should not exceed 500 words in length and should follow the standard format given on page 189 of the June 1985 issue of the Journal lJ.

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18, 189-190. 30, 84 UNITCELL: a nonlinear least-squares program for cell-parameter refinement implementing regression and deletion diagnostics T. HOLLAND AND S.

Rietveld L-1995 Re Rietveld-software For Mac Os X

REDFERN Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, England. E-mail: tjbh @ esc.cam.ac.uk (Received 25 July 1996; accepted 4 October 1996) The crystallographic problem: During the refinement of unit-cell parameters from the observed positions of Bragg reflections in powder diffraction patterns, errors in the indexing and measurement of reflections are usually identified by their associated large residuals (e.g. 20ob s - 20calc ). A more robust approach to the identification of such outliers in a data set is to employ regression diagnostics (Belsey, Kuh & Welsh, 1980; Powell, 1985; Holland & Redfern, 1997). The program UN/TCELL refines cell parameters by minimizing residuals in the experimentally determined Bragg position (in terms of 20hk I, d spacing dhk I or energy Ebkl) using a nonlinear least- squares method. Regression diagnostics are provided that give information on the sensitivity of the refinement result to individual reflection positions (the leverage of each datum), as well as deletion diagnostics that indicate how deleterious each observed position is to the overall fit and automatically compute the effect of removing individual potentially deleterious observations from the data set. Hence, outliers may be identified, remedial action taken, and the overall refinement improved upon.

Hints on Phase Identification Using Powder X-ray Diffraction(Supporting an Oral Presentation)Lachlan M. Cranswick(E-mail: lachlan@melbpc.org.au (old E-mail but still functional)) CCP14, Daresbury Laboratory, UK - E-mail: L.Cranswick@dl.ac.uk (Refinery, Gove, Northern Territory, May 1997 (Version 1) RMIT, Melbourne, Australia, 1997 (Version 2) Melbourne University, Melbourne, December 1997 (Version 3)CSIRO Minerals/AXAA Western Australian Branch Combined Meeting, Perth, Australia, March 1999, (Version 4)On the web at March 1999 (Version 5)March 1999, Version 5(Please inform the author of any mistakes, mis-interpretations, errors, goofs, etc presently in the text) Lachlan Cranswick 1996-1999. May be freely modified and distributed for non-commercial and commercial use providing sources are acknowledged. Much of the following are opinions of Lachlan M.

Cranswick as of March 1999.IndexAims/Agenda Search-Match Software Results ExamplesExample 1: Single Phase Unknown - Calcium Fluoride Example 2: Unknown - Zircon - and trace peaks to be assigned Caution Will Robinson: the common phase might not be the real phase. Franklinite/Magnetite as an example Example 2a: Identifying the trace phase and sample prep peaks Example 2b: Identifying spurious peaks Rantlett relating to the above Franklinite/Magnetite example Example 2c: Showing a phase is not present Example 3: Amorphous hump, preferred orientation, low background plates. Example 4: Non-optimal ICDD data example - Plattnerite Example 4a: Non-optimal ICDD data - bad data replacing good Example 4b: Non-optimal ICDD data example - Magnetite Calculating powder patterns using Rietveld Software User-friendly calculation of powder patterns using Powder Cell for Windows Example 5: Geothermal Vent sample - normally exotic phasesExample 5a: Qualitative XRF to confirm and help ID trace phases Example 6: Non-trivial sulphide ore sample - tricks to Identify - and - the Microprobe can see more complexity than the XRD. Example 7: Ilmenite System - the benefits of 20 years of experience Example 8: Microdiffraction on tiny samples using a Gandolfi camera. Example 9: Bauxite system - benefits of interacting with the people who generated the sample. Example 9a: Bauxite system - identifying 'some' of the trace phases.

Example 10: Contrived example of using quantitative Rietveld to help identify obscured trace peaks. Example 11: Example 9 Bauxite system - further example of 'accidental' interacting with experts to help solve 'unassigned' trace peaks. Example 11a: Using internet based resources (in this case the Clay Minerals Mailing List) to gain opinions, discussion and assistance.The benefits of experience or interacting with experienced people. Available Search-Match software (as of March 1999) Book References on Phase Identification using Powder X-ray Diffraction.

SummaryAims/AgendaGive an indication of what Phase Identification of Unknown Systems can be like.Try and show that when it comes to the crunch, experience and intuition in Phase Identification is what counts. You cannot just rely on computers and software programs.How to attempt to identify trace phases.Recognising spurious peaks. E.g.; CuKBeta Tungsten Spikes etcHow to report results. The main aim is to transfer across to the report reader the degree of reliability and the degree of uncertainty.

When not 100% sure of results (which can be a standard occurance with many types of phase systems), making use the full range of ambiguity the English language allows you is everything! Are you sure the identified phases can exist in this sample?(i.e., Identifying Pb2O3?- This is a high pressure phase) This is where the PDF-2 Database can be very handy.Learn to use words like, maybe, possible, likely, is expected, looks like, etc, etc. This is especially so with trace phases.

It is easier to do this after doing a lot of Phase ID as your experience gives you a guide on what Phase ID is like. Otherwise, you have to believe other people. Many Phase ID courses use contrived samples that have a known solution. In the real world, you do not know that there is a solvable answer (with the available equipment, software and databases) in advance.Search Match ResultsAll search match results give are a list of suggestions. It is up to the person running the software to try and pick the correct suggestions or recognise that there are no reasonable The software does not care if you pick the wrong results.Better algorithms and better data gives better search-match suggestions.If a sample refuses to be easily solved, what can you do?

Look under an optical microscope to try and visually identify the different phases, or acertain from different colours how many phases might exist in the sample. Only do a search on the major peaks. Only do a search on like peaks (i.e., broad, sharp) Use a different search match program Use a Hanawalt search Use a Fink Search Use a PDF-2 CD-ROM 2 to 3 peak search. Limit the search on chemistry. Limit the search based on prior experience i.e., common minerals, Contact people experienced in this phase system to see if they have suggestions. Do a literature search. Have a cup of tea and think about it.

Gunshot Peak Search Use XRF to give elemental analysis Use SEM to identify chemistry of individual particles. Try and separate the components if multiphase.In the case of minor phases, try and rig the experimental or process conditions to change the ratio of phases.

Does it really matter if some of the phases are unknown? Could these be phases not categorised before? Could there be related phases giving similar series of peaksMagnesium Hydroxide Nitrate - not in the literature or database Nickel Hydroxide Nitrate is and gives near identical peak positions. The two phases are Isostructural!