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XRF Report


A Godess on top of Jose Luis, Satya, and Young


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   

SAMPLE

17153C

 

 

 

 

Peaks


 

 

 

 

Energy (eV)

Element

Rad. Type

Intensity

Background

Net Intensity

3.314

K

KL3

278.82

58.83

219.99

3.691

Ca

KL3

690.65

48.6

642.05

4.001

Ca

KM3

128.02

33.25

94.77

4.516

Ti

KL3

329.98

20.46

309.52

4.941

Ti

KM3

70.84

18.55

52.29

5.411

Cr

KL3

72.53

16.87

55.66

5.923

Mn

KL3

121.44

16.8

104.64

6.406

Fe

KL3

13535

15.88

13519.12

7.06

Fe

KM3

1852.1

16.78

1835.32

8.04

Cu

KL3

57.43

16.7

40.73

8.627

Zn

KL3

204.72

27.02

177.7

9.706

Au

L3M5

389.45

62.11

327.34

11.458

Au

L2M4

392.73

182.09

210.64

13.383

Au

L2N4

706.72

341.34

365.38

14.15

Sr

KL3

2022.4

404.48

1617.92

14.95

Y

KL3

711.43

468.43

243

15.768

Zr

KL3

1753.8

538.77

1215.03

17667

Zr

KM3

889.45

717.99

171.46

 
Figure 5 - Sample number 12363 - Calibrated Data in Blue, Fitted data in Red, Background in Black 

SAMPLE

12363

 

 

 

 

Peaks


 

 

 

 

Energy (eV)

Element

Rad. Type

Intensity

Background

Net Intensity

3.316

K

KL3

281.32

57.17

224.15

3.69

Ca

KL3

356.54

46.63

309.91

4.001

Ca

KM3

78.23

31.6

46.63

4.516

Ti

KL3

170

21.06

148.94

4.938

Ti

KM3

45.61

20.27

25.34

5.418

Cr

KL3

61.44

18.37

43.07

5.911

Mn

KL3

110.85

16.63

94.22

6.403

Fe

KL3

7850

19.24

7830.76

7.054

Fe

KM3

1096.7

15.87

1080.83

8.044

Cu

KL3

48.77

17.74

31.03

8.63

Zn

KL3

215.05

31.04

184.01

9.712

Au

L3M5

372.45

66.51

305.94

11.459

Au

L2M4

380.61

180.29

200.32

11.925

Au

L3O45

254.95

214.89

40.06

12.659

Ac

L3M5

355.11

269.52

85.59

13.381

Au

L2N4

964.62

316.63

647.99

14.147

Sr

KL3

2363.7

382.9

1980.8

14.953

Y

KL3

729

441.81

287.19

15.78

Zr

KL3

1413.8

515.45

898.35

17.671

Zr

KM3

784.97

682.03

102.94

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

SAMPLE

10532(O)

 

 

 

 

Peaks


 

 

 

 

Energy (eV)

Element

Rad. Type

Intensity

Background

Net Intensity

3.31

K

KL3

162.51

55.4

107.11

3.691

Ca

KL3

983.01

45.42

937.59

3.992

Ca

KM3

171.95

32.44

139.51

4.515

Ti

KL3

240.07

25.95

214.12

4.932

Ti

KM3

52.36

19.78

32.58

5.411

Cr

KL3

63.23

15.45

47.78

5.924

Mn

KL3

68.85

11.94

56.91

6.402

Fe

KL3

6704.2

18.32

6685.88

7.054

Fe

KM3

915.88

18.32

897.56

8.044

Cu

KL3

51.52

19.9

31.62

8.634

Zn

KL3

214.12

31.3

182.82

9.708

Au

L3M5

365.65

62.6

303.05

11.45

Au

L2M4

375.14

181.23

193.91

12.652

Ac

L3M5

369.9

273.81

96.09

13.38

Au

L2N4

608.62

327.02

281.6

14.15

Sr

KL3

1308.1

386.07

922.03

14.95

Y

KL3

658.58

449.65

208.93

15.766

Zr

KL3

1519.1

516.44

1002.66

17.671

Zr

KM3

827.43

683.54

143.89

 
From the data it can be discussed that, this sample is primarily made up of iron (Fe) since its peak has the highest intensity. The next comes Zr,Ca and Sr which have the highest peaks next to Fe.          Results

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.    


Fe (%)

Zr (%)

Sr (%)

Ca (%)

Au (%)

10532(O)

60.7

9.18

7.38

8.62

6.24

12363

61.1

6.8

13.5

2.4

8.2

17153C

72.4

6.53

7.63

3.47

4.26

     

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