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Objective:
To determine the elemental compositions of the archaeological samples given to our team (Jose Enriquez, Satya Gullapalli, and Young Yun) using the portable X-ray Fluorescence.

Sample details:
The three samples with different sizes were given to our team. Each sample has been labeled with a specific number as shown in the figures. These samples have been obtained from different archaeological sites in North America.

 The three samples with their images and sample numbers are shown in the figure 1, 2, and 3.     
Figure 1 - Sample #1 with the Spec Number - 17153(C)

Figure 2 - Sample #2 with the Spec Number - 12363(C) 
Figure 3 - Sample #3 with the Spec Number - 10532(O)

Physics of XRF:
When the sample is bombarded by an incoming X-ray source, due to the high energy of the electron, a core electron tends to be ejected out as photo-electron creating an empty hole. This hole is then filled by another electron from higher valences. During this process, the photon energy will be released as characteristic x-ray of the element. Based on the intensity of these X-rays emitted from the sample, the elemental composition of the sample is determined by considering bonding energies of various sites.

Steps of XRF:
The samples were analyzed with EMET 3000 TXV+ Portable XRF. Each sample was placed on the XRF with the lid closed. By using the source of X-ray was silver, the sample was analyzed. The time for analyzing each sample was set to 300seconds. The data from the XRF were collected into the Personal Digital Assistance devise. The data obtained from the XRF is then transferred into the PYMCA software and utilized to analyze for peak information by examining energy vs. intensity.

Figure 4 - the picture of the XRF machine that were used and showing the experimental set up

  Data
The following tables show the output obtained from the three different samples

Table 1 - Spec Number 17153C

Cr 0.01%

Mn  0.05%

Cu 0%

Ni <0.01%

Fe >3.40%

Zn <0.03%

Table 2 - Spec Number 10532 (O)

Cr 0.02%

Mn < 0.03%

Cu 0%

Ni < 0.01%

Fe >1.51%

Zn < 0.03%

Table 3 - Spec Number 12363

Cr 0.01%

Mn   0.05%

Cu 0%

Ni < 0.01%

Fe >2.16%

Zn < 0.03%

  Data and Analysis:
The data analyzed using the PYMCA software are presented and discussed as below for every individual sample.

  • Calibration Procedure

1.  Load your data.
2.  Select S# 2.1 on left top window; this opens the window on the right with the calibrate button.
3.  Select "Internal(from Source or PyMCA)" on the calibration menu.
4.  Click on Calibrate > Compute.
5.  Click on Search on the MCA Calibration window that opens.
6.  Click on the Ag peak -see graph below.
7.  Select Ag(47) from the Element menu and KL3(0.54112) from the Line menu, click OK.
8.  Click OK to go back to PyMCA Main Window, the energy axis should then be calibrated.
9.  Once the energy is calibrated you can continue playing with the software to identify the peaks.
    
Figure 4 - Sample number 17153(C) - Calibrated Data in Blue, Fitted data in Red, Background in Black   

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SAMPLE

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17153C

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...

 

...

 

...

Peaks

...

 

...

 

...

 

...

 

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Energy (eV)

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Element

...

Rad. Type

...

Intensity

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Background

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Net Intensity

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3.314

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K

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KL3

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278.82

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58.83

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219.99

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3.691

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Ca

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KL3

...

690.65

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48.6

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642.05

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4.001

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Ca

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KM3

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128.02

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33.25

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94.77

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4.516

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Ti

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KL3

...

329.98

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20.46

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309.52

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4.941

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Ti

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KM3

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70.84

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18.55

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52.29

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5.411

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Cr

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KL3

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72.53

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16.87

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55.66

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5.923

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Mn

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KL3

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121.44

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16.8

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104.64

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6.406

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Fe

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KL3

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13535

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15.88

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13519.12

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7.06

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Fe

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KM3

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1852.1

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16.78

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1835.32

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8.04

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Cu

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KL3

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57.43

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16.7

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40.73

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8.627

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Zn

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KL3

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204.72

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27.02

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177.7

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9.706

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Au

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L3M5

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389.45

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62.11

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327.34

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11.458

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Au

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L2M4

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392.73

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182.09

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210.64

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13.383

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Au

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L2N4

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706.72

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341.34

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365.38

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14.15

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Sr

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KL3

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2022.4

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404.48

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1617.92

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14.95

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Y

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KL3

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711.43

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468.43

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243

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15.768

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Zr

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KL3

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1753.8

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538.77

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1215.03

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17667

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Zr

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KM3

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889.45

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717.99

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171.46

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SAMPLE

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12363

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...

 

...

 

...

 

...

Peaks

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...

 

...

 

...

 

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Energy (eV)

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Element

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Rad. Type

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Intensity

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Background

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Net Intensity

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3.316

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K

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KL3

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281.32

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57.17

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224.15

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3.69

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Ca

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KL3

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356.54

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46.63

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309.91

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4.001

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Ca

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KM3

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78.23

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31.6

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46.63

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4.516

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Ti

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KL3

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170

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21.06

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148.94

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4.938

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Ti

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KM3

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45.61

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20.27

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25.34

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5.418

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Cr

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KL3

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61.44

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18.37

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43.07

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5.911

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Mn

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KL3

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110.85

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16.63

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94.22

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6.403

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Fe

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KL3

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7850

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19.24

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7830.76

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7.054

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Fe

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KM3

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1096.7

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15.87

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1080.83

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8.044

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Cu

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KL3

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48.77

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17.74

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31.03

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8.63

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Zn

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KL3

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215.05

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31.04

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184.01

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9.712

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Au

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L3M5

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372.45

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66.51

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305.94

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11.459

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Au

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L2M4

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380.61

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180.29

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200.32

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11.925

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Au

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L3O45

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254.95

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214.89

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40.06

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12.659

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Ac

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L3M5

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355.11

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269.52

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85.59

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13.381

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Au

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L2N4

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964.62

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316.63

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647.99

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14.147

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Sr

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KL3

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2363.7

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382.9

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1980.8

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14.953

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Y

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KL3

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729

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441.81

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287.19

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15.78

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Zr

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KL3

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1413.8

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515.45

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898.35

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17.671

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Zr

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KM3

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784.97

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682.03

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102.94

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Figure 6 - Sample number 10532(O) - Calibrated Data in Blue, Fitted data in Red, Background in Black

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SAMPLE

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10532(O)

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...

 

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Peaks

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...

 

...

 

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Energy (eV)

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Element

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Rad. Type

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Intensity

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Background

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Net Intensity

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3.31

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K

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KL3

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162.51

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55.4

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107.11

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3.691

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Ca

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KL3

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983.01

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45.42

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937.59

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3.992

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Ca

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KM3

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171.95

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32.44

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139.51

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4.515

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Ti

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KL3

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240.07

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25.95

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214.12

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4.932

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Ti

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KM3

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52.36

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19.78

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32.58

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5.411

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Cr

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KL3

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63.23

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15.45

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47.78

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5.924

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Mn

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KL3

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68.85

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11.94

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56.91

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6.402

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Fe

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KL3

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6704.2

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18.32

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6685.88

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7.054

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Fe

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KM3

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915.88

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18.32

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897.56

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8.044

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Cu

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KL3

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51.52

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19.9

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31.62

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8.634

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Zn

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KL3

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214.12

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31.3

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182.82

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9.708

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Au

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L3M5

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365.65

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62.6

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303.05

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11.45

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Au

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L2M4

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375.14

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181.23

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193.91

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12.652

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Ac

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L3M5

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369.9

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273.81

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96.09

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13.38

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Au

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L2N4

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608.62

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327.02

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281.6

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14.15

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Sr

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KL3

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1308.1

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386.07

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922.03

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14.95

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Y

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KL3

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658.58

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449.65

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208.93

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15.766

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Zr

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KL3

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1519.1

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516.44

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1002.66

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17.671

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Zr

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KM3

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827.43

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683.54

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143.89

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The most dominant elements have been identified and they are Fe, Zr, Sr, Ca, and Au. The following data shows concentrations of these various elements in the three different samples.    

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Fe (%)

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Zr (%)

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Sr (%)

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Ca (%)

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Au (%)

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10532(O)

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60.7

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9.18

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7.38

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8.62

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6.24

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12363

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61.1

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6.8

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13.5

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2.4

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8.2

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17153C

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72.4

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6.53

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7.63

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3.47

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4.26

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