Here is some data I collected a few weeks ago from my QC block which contains K412 and the necessary standards (Al2O3, SiO2, Fe, CaF2, MgO). For each material, I collected 13 spectra from each of 4 detectors. For the standards, I did a little data quality assurance and then summed the spectra (per detector) to build a standard. The standards are then fit to each unknown. The result is a set of 13 k-ratios for each characteristic line set for each element. I summarize these k-ratios by calculating mean, min, max, std and a couple other statistics and tabulate this. The results are:
40×10 DataFrame
Row │ variable det nspec mean min max std mms mps frac
│ Symbol Cat… Int64 Float64 Float64 Float64 Float64 Float64 Float64 Float64
─────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ k[Al K-L3 + 3 others, Al2O3] 0 13 0.0673782 0.0667252 0.0688065 0.000563834 0.0668143 0.067942 0.83682
2 │ k[Al K-L3 + 3 others, Al2O3] 1 13 0.0664715 0.0658443 0.0672787 0.000546057 0.0659254 0.0670175 0.821491
3 │ k[Al K-L3 + 3 others, Al2O3] 2 13 0.0671671 0.0660373 0.0684215 0.00057184 0.0665952 0.0677389 0.851369
4 │ k[Al K-L3 + 3 others, Al2O3] 3 13 0.067121 0.0662979 0.0681173 0.000524488 0.0665966 0.0676455 0.781406
5 │ k[Al K-L3 + 3 others, Al2O3] 4 13 0.0670778 0.0665836 0.0679787 0.000431807 0.066646 0.0675097 0.64374
6 │ k[Ca K-L3 + 3 others, CaF2] 0 13 0.206919 0.20563 0.208516 0.000864144 0.206055 0.207783 0.417624
7 │ k[Ca K-L3 + 3 others, CaF2] 1 13 0.200773 0.199439 0.202793 0.000951106 0.199822 0.201724 0.473721
8 │ k[Ca K-L3 + 3 others, CaF2] 2 13 0.198908 0.196795 0.201411 0.00139895 0.197509 0.200307 0.703317
9 │ k[Ca K-L3 + 3 others, CaF2] 3 13 0.201701 0.200865 0.203697 0.000876597 0.200824 0.202577 0.434603
10 │ k[Ca K-L3 + 3 others, CaF2] 4 13 0.202279 0.201183 0.204263 0.000897193 0.201381 0.203176 0.443543
11 │ k[Fe K-L3 + 1 other, Fe] 0 13 0.0664122 0.0656582 0.0671871 0.000507176 0.0659051 0.0669194 0.763678
12 │ k[Fe K-L3 + 1 other, Fe] 1 13 0.0661916 0.0657228 0.0672809 0.000469286 0.0657223 0.0666609 0.708981
13 │ k[Fe K-L3 + 1 other, Fe] 2 13 0.0665982 0.0656377 0.0676449 0.000624965 0.0659733 0.0672232 0.938411
14 │ k[Fe K-L3 + 1 other, Fe] 3 13 0.0661991 0.0657107 0.0668829 0.000332966 0.0658661 0.066532 0.502976
15 │ k[Fe K-L3 + 1 other, Fe] 4 13 0.0663986 0.065982 0.0672085 0.000358371 0.0660402 0.066757 0.539727
16 │ k[Fe K-M3 + 3 others, Fe] 0 13 0.0650205 0.0629254 0.0671526 0.00142598 0.0635945 0.0664465 2.19313
17 │ k[Fe K-M3 + 3 others, Fe] 1 13 0.0654008 0.0632611 0.0672457 0.00126211 0.0641387 0.0666629 1.9298
18 │ k[Fe K-M3 + 3 others, Fe] 2 13 0.065876 0.0621917 0.0685643 0.00178602 0.06409 0.067662 2.71118
19 │ k[Fe K-M3 + 3 others, Fe] 3 13 0.0647002 0.0622948 0.066894 0.00146527 0.063235 0.0661655 2.26471
20 │ k[Fe K-M3 + 3 others, Fe] 4 13 0.0652447 0.0633649 0.0663351 0.000881101 0.0643636 0.0661258 1.35046
21 │ k[Fe L3-M5 + 13 others, Fe] 0 13 0.03989 0.0390774 0.0411357 0.000739593 0.0391504 0.0406296 1.85408
22 │ k[Fe L3-M5 + 13 others, Fe] 1 13 0.0403173 0.0385843 0.0421022 0.00102367 0.0392937 0.041341 2.53903
23 │ k[Fe L3-M5 + 13 others, Fe] 2 13 0.0422189 0.0401851 0.0440921 0.00114563 0.0410733 0.0433645 2.71355
24 │ k[Fe L3-M5 + 13 others, Fe] 3 13 0.0413002 0.0398211 0.0428919 0.000976003 0.0403242 0.0422762 2.3632
25 │ k[Fe L3-M5 + 13 others, Fe] 4 13 0.0416638 0.0410419 0.0428226 0.000562996 0.0411008 0.0422268 1.35128
26 │ k[Mg K-L3 + 1 other, MgO] 0 13 0.144145 0.14326 0.145784 0.000778769 0.143367 0.144924 0.540266
27 │ k[Mg K-L3 + 1 other, MgO] 1 13 0.143494 0.142553 0.145288 0.000865561 0.142629 0.14436 0.603202
28 │ k[Mg K-L3 + 1 other, MgO] 2 13 0.146789 0.145792 0.147557 0.000484152 0.146304 0.147273 0.329829
29 │ k[Mg K-L3 + 1 other, MgO] 3 13 0.146177 0.145544 0.14718 0.000507883 0.145669 0.146685 0.347444
30 │ k[Mg K-L3 + 1 other, MgO] 4 13 0.145219 0.144653 0.14651 0.00057413 0.144645 0.145793 0.395355
31 │ k[O K-L3 + 1 other, Al2O3] 0 13 0.652263 0.647599 0.661162 0.00379261 0.64847 0.656055 0.581454
32 │ k[O K-L3 + 1 other, Al2O3] 1 13 0.638632 0.633832 0.644866 0.0032374 0.635395 0.641869 0.506927
33 │ k[O K-L3 + 1 other, Al2O3] 2 13 0.645777 0.640643 0.651841 0.00294525 0.642831 0.648722 0.456079
34 │ k[O K-L3 + 1 other, Al2O3] 3 13 0.651737 0.645822 0.658638 0.00353831 0.648199 0.655275 0.542905
35 │ k[O K-L3 + 1 other, Al2O3] 4 13 0.649076 0.644075 0.655744 0.00315486 0.645921 0.652231 0.486055
36 │ k[Si K-L3 + 3 others, SiO2] 0 13 0.346675 0.345486 0.349379 0.00119801 0.345477 0.347873 0.345572
37 │ k[Si K-L3 + 3 others, SiO2] 1 13 0.34378 0.341762 0.346746 0.00149526 0.342285 0.345275 0.434947
38 │ k[Si K-L3 + 3 others, SiO2] 2 13 0.350525 0.348511 0.352958 0.00115872 0.349367 0.351684 0.330567
39 │ k[Si K-L3 + 3 others, SiO2] 3 13 0.346128 0.34396 0.349919 0.00172684 0.344401 0.347855 0.498902
40 │ k[Si K-L3 + 3 others, SiO2] 4 13 0.346853 0.345311 0.349609 0.00130634 0.345547 0.348159 0.376626
I've attached the Jupyter notebook (exported as HTML) and the results as a CSV file and plot in SVG format.
I'll leave the interpretation to JD.