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Clustering and visualization of powder-diffraction data
International Tables for Crystallography (2018). Vol. H, ch. 3.8, pp. 325-343 [ doi:10.1107/97809553602060000953 ]
... shows the use of the Pearson and Spearman correlation coefficients (Barr et al., 2004a ). In Fig. 3.8.1 (a) r = 0.93 ... not introduce potentially damaging artefacts, for example ringing around peaks (Barr et al., 2004a ; Smrcok et al., 1999 ). After pre ... bars are higher on the graph. [For further examples see Barr et al. (2004b ,c ) and Barr, Dong, Gilmore & Faber ( ...
Quality control
International Tables for Crystallography (2018). Vol. H, Section 3.8.10, p. 342 [ doi:10.1107/97809553602060000953 ]
Quality control 3.8.10. Quality control Quality control (Gilmore, Barr & Paisley, 2009 ) is designed for situations where the stability of ... from the cluster of reference measurements. References Gilmore, C. J., Barr, G. & Paisley, W. (2004). High-throughput powder diffraction. I. ...
An example combining PXRD and Raman data
International Tables for Crystallography (2018). Vol. H, Section 3.8.9.1, p. 342 [ doi:10.1107/97809553602060000953 ]
... to data collected on sulfathiazole using PXRD and Raman spectroscopy (Barr, Cunningham et al., 2009 ). A flowchart is shown in ... and 45-2. (f) The MMDS plot validates the dendrogram. (g) The Raman patterns for 35-2 and 45-2 superimposed. ... structure. The INDSCAL method is now applied starting from random G matrices and the results are shown in Fig. 3.8.16 ( ...
[more results from section 3.8.9 in volume H]
Using spectroscopic data
International Tables for Crystallography (2018). Vol. H, Section 3.8.8, pp. 339-340 [ doi:10.1107/97809553602060000953 ]
... shape are partly responsible. References Boccaleri, E., Carniato, F., Croce, G., Viterbo, D., van Beek, W., Emerich, H. & Milanesio, M. (2007 ...
Example: inorganic mixtures
International Tables for Crystallography (2018). Vol. H, Section 3.8.7.1, pp. 338-339 [ doi:10.1107/97809553602060000953 ]
... Dong et al. (2008 ). References Dong, W., Gilmore, C., Barr, G., Dallman, C., Feeder, N. & Terry, S. (2008). A quick ...
[more results from section 3.8.7 in volume H]
Phase transitions in ammonium nitrate
International Tables for Crystallography (2018). Vol. H, Section 3.8.6.2, pp. 335-337 [ doi:10.1107/97809553602060000953 ]
Phase transitions in ammonium nitrate 3.8.6.2. Phase transitions in ammonium nitrate Ammonium nitrate exhibits temperature-induced phase transformations. Between 256 and 305K it crystallizes in the orthorhombic space group Pmmm with a = 5.745, b = 5.438, c = 4.942Å and Z = 2; from 305 to 357K it crystallizes in Pbnm with a = 7.14 ...
[more results from section 3.8.6 in volume H]
The PolySNAP program and DIFFRAC.EVA
International Tables for Crystallography (2018). Vol. H, Section 3.8.5.3, p. 333 [ doi:10.1107/97809553602060000953 ]
... these techniques have been incorporated into the PolySNAP computer program (Barr et al., 2004a ,b ,c ; Barr, Dong, Gilmore & Faber, 2004 ; Barr, Dong & Gilmore, 2009 ), which was developed from the SNAP- ...
[more results from section 3.8.5 in volume H]
Powder data as a tree: the minimum spanning trees
International Tables for Crystallography (2018). Vol. H, Section 3.8.4.2.3, p. 331 [ doi:10.1107/97809553602060000953 ]
Powder data as a tree: the minimum spanning trees 3.8.4.2.3. Powder data as a tree: the minimum spanning trees The minimum spanning tree (MST) displays the MMDS plot as a tree whose points are the data from the MMDS calculation (in three dimensions) and whose weights are the distances between these ...
[more results from section 3.8.4 in volume H]
Amorphous samples
International Tables for Crystallography (2018). Vol. H, Section 3.8.3.7, p. 329 [ doi:10.1107/97809553602060000953 ]
... their effect on the estimation of the number of clusters (Barr et al., 2004 b). Of course, the question of ... varying degrees of amorphous content, which further complicates matters. References Barr, G., Dong, W. & Gilmore, C. J. (2004a). High-throughput ...
[more results from section 3.8.3 in volume H]
Generation of the correlation and distance matrices
International Tables for Crystallography (2018). Vol. H, Section 3.8.2.5, pp. 326-327 [ doi:10.1107/97809553602060000953 ]
Generation of the correlation and distance matrices 3.8.2.5. Generation of the correlation and distance matrices Using equation (3.8.3) , a correlation matrix is generated in which a set of n patterns is matched with every other to give a symmetric (n × n) correlation matrix [rho] with unit diagonal. The matrix [rho] can ...
[more results from section 3.8.2 in volume H]
International Tables for Crystallography (2018). Vol. H, ch. 3.8, pp. 325-343 [ doi:10.1107/97809553602060000953 ]
... shows the use of the Pearson and Spearman correlation coefficients (Barr et al., 2004a ). In Fig. 3.8.1 (a) r = 0.93 ... not introduce potentially damaging artefacts, for example ringing around peaks (Barr et al., 2004a ; Smrcok et al., 1999 ). After pre ... bars are higher on the graph. [For further examples see Barr et al. (2004b ,c ) and Barr, Dong, Gilmore & Faber ( ...
Quality control
International Tables for Crystallography (2018). Vol. H, Section 3.8.10, p. 342 [ doi:10.1107/97809553602060000953 ]
Quality control 3.8.10. Quality control Quality control (Gilmore, Barr & Paisley, 2009 ) is designed for situations where the stability of ... from the cluster of reference measurements. References Gilmore, C. J., Barr, G. & Paisley, W. (2004). High-throughput powder diffraction. I. ...
An example combining PXRD and Raman data
International Tables for Crystallography (2018). Vol. H, Section 3.8.9.1, p. 342 [ doi:10.1107/97809553602060000953 ]
... to data collected on sulfathiazole using PXRD and Raman spectroscopy (Barr, Cunningham et al., 2009 ). A flowchart is shown in ... and 45-2. (f) The MMDS plot validates the dendrogram. (g) The Raman patterns for 35-2 and 45-2 superimposed. ... structure. The INDSCAL method is now applied starting from random G matrices and the results are shown in Fig. 3.8.16 ( ...
[more results from section 3.8.9 in volume H]
Using spectroscopic data
International Tables for Crystallography (2018). Vol. H, Section 3.8.8, pp. 339-340 [ doi:10.1107/97809553602060000953 ]
... shape are partly responsible. References Boccaleri, E., Carniato, F., Croce, G., Viterbo, D., van Beek, W., Emerich, H. & Milanesio, M. (2007 ...
Example: inorganic mixtures
International Tables for Crystallography (2018). Vol. H, Section 3.8.7.1, pp. 338-339 [ doi:10.1107/97809553602060000953 ]
... Dong et al. (2008 ). References Dong, W., Gilmore, C., Barr, G., Dallman, C., Feeder, N. & Terry, S. (2008). A quick ...
[more results from section 3.8.7 in volume H]
Phase transitions in ammonium nitrate
International Tables for Crystallography (2018). Vol. H, Section 3.8.6.2, pp. 335-337 [ doi:10.1107/97809553602060000953 ]
Phase transitions in ammonium nitrate 3.8.6.2. Phase transitions in ammonium nitrate Ammonium nitrate exhibits temperature-induced phase transformations. Between 256 and 305K it crystallizes in the orthorhombic space group Pmmm with a = 5.745, b = 5.438, c = 4.942Å and Z = 2; from 305 to 357K it crystallizes in Pbnm with a = 7.14 ...
[more results from section 3.8.6 in volume H]
The PolySNAP program and DIFFRAC.EVA
International Tables for Crystallography (2018). Vol. H, Section 3.8.5.3, p. 333 [ doi:10.1107/97809553602060000953 ]
... these techniques have been incorporated into the PolySNAP computer program (Barr et al., 2004a ,b ,c ; Barr, Dong, Gilmore & Faber, 2004 ; Barr, Dong & Gilmore, 2009 ), which was developed from the SNAP- ...
[more results from section 3.8.5 in volume H]
Powder data as a tree: the minimum spanning trees
International Tables for Crystallography (2018). Vol. H, Section 3.8.4.2.3, p. 331 [ doi:10.1107/97809553602060000953 ]
Powder data as a tree: the minimum spanning trees 3.8.4.2.3. Powder data as a tree: the minimum spanning trees The minimum spanning tree (MST) displays the MMDS plot as a tree whose points are the data from the MMDS calculation (in three dimensions) and whose weights are the distances between these ...
[more results from section 3.8.4 in volume H]
Amorphous samples
International Tables for Crystallography (2018). Vol. H, Section 3.8.3.7, p. 329 [ doi:10.1107/97809553602060000953 ]
... their effect on the estimation of the number of clusters (Barr et al., 2004 b). Of course, the question of ... varying degrees of amorphous content, which further complicates matters. References Barr, G., Dong, W. & Gilmore, C. J. (2004a). High-throughput ...
[more results from section 3.8.3 in volume H]
Generation of the correlation and distance matrices
International Tables for Crystallography (2018). Vol. H, Section 3.8.2.5, pp. 326-327 [ doi:10.1107/97809553602060000953 ]
Generation of the correlation and distance matrices 3.8.2.5. Generation of the correlation and distance matrices Using equation (3.8.3) , a correlation matrix is generated in which a set of n patterns is matched with every other to give a symmetric (n × n) correlation matrix [rho] with unit diagonal. The matrix [rho] can ...
[more results from section 3.8.2 in volume H]
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