Study of Biphasic Calcium Phosphate Ceramics and HA-Chitosan Composite Implanted into Sheep’s Bone

ABSTRACT
NUR AISYAH NUZULIA. Study of Biphasic Calcium Phosphate Ceramics and HA-Chitosan
Composite Implanted into Sheep’s Bone. Under direction of AKHIRUDDIN MADDU and
KIAGUS DAHLAN.

Biphasic Calcium Phosphate (BCP) biomaterials are recognized as biodegradable,
bioresorbable, and osteoconductive material and, therefore, it is suitable for filling bone defects to
aid regeneration process of new bone tissue. This study aimed to synthesize BCP ceramics by
precipitation method and observe bone growth using BCP ceramics and HA-Chitosan composite
implanted into sheep’s bone. BCP ceramics was prepared by precipitation of Na2HPO4.2H2O
which was dropped by CaCl2.2H2O at temperature 700C with various molar ratios and various
volume of solution. Molar ratio of Ca and P was variated approximately 0.2M:0.2M and
0.334M:0.2M while various volume of solution was 50 ml and 100 ml. BCP ceramics was formed
which was indicated by mass of precipitate and the result showed that sample with greater molarity
of Ca was resulting in bigger mass precipitate. It showed that higher molarity of Ca/P tends to be
more mass precipitate. The X-Ray Diffraction results showed that BCP 100 ml with molar ratio
Ca/P about 0.334M:0.2M had the expected characteristics of implant material for in vivo
experiment into sheep’s bone. Moreover, it showed the consistency of sample which indicates that
it was a reproducible biomaterial. This result was also supported by Fourier Transform Infrared
(FTIR) and Scanning Electron Microscopy (SEM) characterization. In vivo study of BCP ceramics
and HA-Chitosan composite showed that bone recovery without bone graft (control) was more

complete than that with BCP and HA-Chitosan bone grafts. Based on pathological evaluation, the
results indicated that BCP ceramics was biodegradable and bioresorbable but less osteoconductive.
In the contrary, HA-chitosan composite was not biodegradable and bioresorbable but more
osteoconductive. Moreover, BCP bone graft was more readily resorbed by the body than HAChitosan. Resorption of HA-Chitosan bone graft was very slow but new tissue growth was faster
than that of BCP bone graft. In contrary, resorption of BCP bone graft was very fast but new tissue
growth was very slow.
Keywords: Hydroxyapatite, Tricalcium Phosphate, HA-Chitosan, In Vivo Evaluation

 
 

APPENDIX

16 
 

Appendix 1 Flow chart

Materials and equipment preparation
Yes

ready

Solution preparation

Precipitation of biphasic apatite

XRD, FTIR and SEM
Characterization 

In Vivo Experiment

Analysis data

Report arrangement

No

Appendix 2 Maximum XRD peak of samples
A

2θ
10.56
22.58
25.6
27.48
28.62
31.46
31.88
32.54
33.74
39.4
46.3
49.12
50.86
52.86
63.74

Sample
int
int-f

94
61
177
59
86
424
253
282
102
106
142
151
58
83
58

22.169811
14.386792
41.745283
13.915094

20.283019
100
59.669811
66.509434
24.056604
25
33.490566
35.613208
13.679245
19.575472
13.679245

TCP
2θ

OCP

HA

int

%Δ2θ

10.847
22.206
25.802
27.42
28.68
31.026

12
4
25
8
2
100

97.354107
98.315771
99.217115

99.781182
99.790795
98.601173

32.448
33.484
39.8
46.034

20
8
10
2

99.716469
99.235456
98.994975
99.422166

50.733

52.944
63.443

6
25
6

99.74967
99.841342
99.531863

2θ

int

%Δ2θ

10.82
22.902
25.879

12
10
40

97.597043
98.594009
98.921906

28.966
31.773
31.773
32.196

18
100
100
60

98.805496

99.014887
99.663236
98.931544

39.204
46.711

8
30

99.500051
99.120122

50.493

20

99.273167

63.443

4

99.531863

2θ
22.723
25.576
27.681
28.126
31.474
31.589
32.533
33.928
39.311
46.534
49.496

int
80
80
80
80
100
100
90
90
80
80
90

PHASE
%Δ2θ
99.370682
99.906162
99.27387
98.243618
99.955519
99.078793
99.978483
99.445885
99.7736
99.497142
99.240343

HA
OCP
OCP
TCP
TCP
OCP
HA
OCP
OCP
OCP
OCP
OCP
TCP
TCP
HA/TCP

17 
 

Continue
B

2θ
10.8
22.8
25.92
27.8
28.78
31.08
31.68
32.18
32.74
34.02
34.32
39.58
41.78
46.52
47.88
49.4
49.52
50.96
53.22
61.18
64.78

Sample
int
int-f
104
50
164
56
69
85
441
372
361
88
44
114
48
174
55
149
86
71
83
32
18

TCP
2θ
23.582766
11.337868
37.188209
12.698413
15.646259
19.274376
100
84.353741
81.85941
19.954649
9.9773243
25.85034
10.884354
39.455782
12.471655
33.786848
19.501134
16.099773
18.820862
7.2562358
4.0816327

10.847
25.802
27.769
28.68
31.026

int
12
25
55
2
100

OCP

HA
%Δ2θ
99.5667
99.542671
99.888365
99.651325
99.825952

32.448

20

99.174063

34.371
39.8
41.683
46.635
47.968
49.785
49.785
50.733
53.512
60.897
64.677

65
10
12
4
16
12
12
6
8
4
4

99.851619
99.447236
99.767291
99.753404
99.816544
99.226675
99.467711
99.552559
99.454328
99.535281
99.840747

2θ

int

%Δ2θ

10.82
22.902
25.354

12
10
2

99.815157
99.554624
97.767611

28.966

18

99.357868

31.773
32.196
32.902
34.048

100
60
60
25

99.707299
99.950304
99.507629
99.917763

2θ

PHASE

int

%Δ2θ

22.723
25.955
27.681
29.257
31.361
31.589
32.291
32.533

80
100
80
90
80
100
90
90

99.661136
99.865151
99.570102
98.369621
99.103983
99.711925
99.656251
99.363723

90
70
90
80

99.576394
99.309999
99.50462
99.969914

90

99.806045

39.818
42.029
46.711

20
10
30

99.40228
99.407552
99.591103

34.466
39.855
41.988
46.534

49.468

40

99.862537

49.496

51.283
53.143
61.66
65.031

12
20
10
9

99.370162
99.855108
99.221537
99.61403

HA
HA
TCP
TCP
HA
TCP
OCP
HA
HA
HA
TCP
TCP
TCP
OCP
TCP
HA
TCP
HA/TCP
HA
TCP
TCP

18 
 

Continue
B1-1
Sample
2θ
13.56
16.84
23.16
25.88
27.8
29.74
31.08
31.56
32.56
34.32
35.6
37.34
39.38
41.14
43.88
46.44
48
50.12
53.08
57.54
59.66
60.92
64.02

int
24
32
26
60
96
28
200
94
150
110
38
34
48
52
30
58
60
36
80
22
42
30
28

int-f
12
16
13
30
48
14
100
47
75
55
19
17
24
26
15
29
30
18
40
11
21
15
14

2θ
13.633

25.802
27.769
29.655
31.026
32.448
34.371
35.597
37.328
39.8
41.088
43.893
46.635
48.402
50.314
53.512
57.557
59.513
60.897
64.677

TCP
int
16

25
55
16
100
20
65
12
10
10
14
6
4
14
6
8
4
12
4
4

%Δ2θ
99.464535

99.697698
99.888365
99.71337
99.825952
99.654832
99.851619
99.991572
99.967853
98.944724
99.873442
99.970383
99.581859
99.169456
99.614421
99.192704
99.970464
99.752995
99.962231
98.984183

HA
int

%Δ2θ

16.841
22.902
25.879

6
10
40

99.994062
98.873461
99.996136

31.773
32.902
34.048
35.48

100
60
25
6

99.329619
98.96055
99.201128
99.661781

39.204

8

99.551066

43.804
46.711
48.103
50.493
53.143
57.128
59.938
60.457
64.078

8
30
16
20
20
8
6
6
13

99.8265
99.419837
99.785876
99.261284
99.881452
99.278812
99.536187
99.234166
99.909485

2θ

OCP
int

%Δ2θ

16.043
23.082
25.955
27.681
29.858
31.361
31.589
32.533
34.466
35.164

90
80
80
80
70
80
100
90
90
80

95.032101
99.662074
99.711038
99.570102
99.604796
99.103983
99.908196
99.917007
99.576394
98.760096

39.311
40.796
43.472
46.534
48.929

80
90
80
80
90

99.824477
99.15678
99.061465
99.797997
98.10133

2θ

PHASE
TCP
HA
OCP
HA
TCP
TCP
TCP
OCP
OCP
TCP
TCP
TCP
OCP
TCP
TCP
OCP
HA
TCP
HA
TCP
TCP
TCP
HA

19 
 

Continue
B1-2

2θ
25.86
27.82
28.82
29.6
31.16
31.66
31.72
32.76
34.38
39.54
41.12
43.94
45.38
46.66
48.02
49.4
50.2
53.22
59.62
61
64.04
66.24
71.3
73.66
76

Sample
int
58
72
30
28
146
142
122
132
88
54
44
26
28
62
52
52
44
50
44
30
34
24
24
20
24

int-f
39.72603
49.31507
20.54795
19.17808
100
97.26027
83.56164
90.41096
60.27397
36.9863
30.13699
17.80822
19.17808
42.46575
35.61644
35.61644
30.13699
34.24658
30.13699
20.54795
23.28767
16.43836
16.43836
13.69863
16.43836

2θ
25.802
27.769
28.68
29.655
31.026

TCP
int
25
55
2
16
100

%Δ2θ
99.77521
99.81634
99.51185
99.81453
99.5681

32.448
34.371
39.8
41.088
43.893
45.305
46.635
48.402
49.785
50.314
53.512
59.513
60.897
64.677
66.28

20
65
10
14
6
8
4
14
12
6
8
12
4
4
6

99.03846
99.97382
99.34673
99.92212
99.89292
99.83446
99.94639
99.21078
99.22667
99.77342
99.45433
99.82021
99.83086
99.01511
99.93965

2θ
25.879

HA
int
40

%Δ2θ
99.92658

28.966

18

99.49596

31.773
32.902
34.048
39.818

100
60
25
20

99.83319
99.56842
99.02491
99.30182

43.804
45.305
46.711
48.103
49.468
50.493
53.143
59.938
61.66
64.078
66.386
71.651
73.995
76.154

8
6
30
16
40
20
20
6
10
13
4
5
7
1

99.68953
99.83446
99.89082
99.82745
99.86254
99.41972
99.85511
99.46945
98.92961
99.9407
99.78007
99.51013
99.54727
99.79778

2θ
25.955
27.681
28.126
29.554
31.361
31.589

OCP
int
100
80
80
80
80
100

%Δ2θ
99.63398
99.49785
97.53253
99.84435
99.35908
99.77524

32.533

90

99.30225

PHASE
HA
TCP
HA
TCP
TCP
OCP
HA
HA
TCP
HA
TCP
TCP
HA/TCP
HA
HA
HA
HA
HA
TCP
TCP
HA
TCP
HA
HA
HA

20 
 

Continue
B2-1
Sample

TCP

2θ

int

int-f

21.46
23.14
26.1
28.54
29.58
31.52
32.5
33.66
39.28
40.98
44.92
46.4
49.54
50.64
53.86
57.98
59.62
62.58
64.12
77.16

104
114
108
84
140
490
550
202
148
132
66
202
148
94
80
50
60
50
78
72

18.909091
20.727273
19.636364
15.272727
25.454545
89.090909
100
36.727273
26.909091
24
12
36.727273
26.909091
17.090909
14.545455
9.0909091
10.909091
9.0909091
14.181818
13.090909

2θ

int

HA
%Δ2θ

21.393

4

99.68681

26.188
28.68
29.655
31.026
32.448
33.484
39.8
41.088
44.902
46.635
49.785
50.733
53.512
57.557
59.513

4
2
16
100
20
8
10
14
4
4
12
6
8
4
12

99.66397
99.51185
99.74709
98.40779
99.83974
99.47438
98.69347
99.73715
99.95991
99.49609
99.50788
99.81669
99.34968
99.26508
99.82021

64.677

4

99.1388

2θ

int

OCP
%Δ2θ

21.819
22.902
25.879
28.126

10
10
40
12

98.35465
98.96079
99.14603
98.52805

31.773
32.196
34.048
39.204
40.452
45.305
46.711
49.468
50.493
54.44
58.073
59.938
63.011
64.078
77.175

100
60
25
8
2
6
30
40
20
4
4
6
12
13
11

99.20373
99.05578
98.86043
99.80614
98.69475
99.1502
99.3342
99.85445
99.70887
98.93461
99.83986
99.46945
99.31599
99.93445
99.98056

2θ
20.785
23.082
26.346
28.126
29.554
31.474
32.533
33.536
39.311
40.796
45.067
46.534
49.496

int
70
80
80
80
80
100
90
90
80
90
80
80
90

PHASE
%Δ2θ
96.75247
99.74872
99.06627
98.52805
99.91203
99.85385
99.89856
99.63025
99.92114
99.54898
99.67382
99.71204
99.9111

TCP
HA
TCP
TCP
TCP
OCP
OCP
HA
HA
TCP
TCP
HA
HA
TCP
TCP
HA
TCP
HA
HA
HA

21 
 

Continue
B2-2
Sample

TCP

2θ

int

int-f

22.92
26.08
27.88
31.46
32.6
33.72
34.32
39.52
41
46.5
49.6
53.64
59.56
61.02
64.12
71.24
77.08

42
48
46
146
132
64
60
42
52
70
60
42
30
24
36
16
20

28.767123
32.876712
31.506849
100
90.410959
43.835616
41.09589
28.767123
35.616438
47.945205
41.09589
28.767123
20.547945
16.438356
24.657534
10.958904
13.69863

2θ
22.206
26.188
27.769
31.026
32.448
33.484
34.371
39.8
41.088
46.635
49.785
53.512
59.513
60.897
64.677

HA

int

%Δ2θ

4
4
55
100
20
8
65
10
14
4
12
8
12
4
4

96.784653
99.587597
99.600274
98.601173
99.531558
99.295186
99.851619
99.296482
99.785826
99.710518
99.628402
99.760801
99.921026
99.79802
99.138797

2θ

OCP

int

%Δ2θ

22.902
25.879
28.126
31.773
32.902

10
40
12
100
60

99.921404
99.223308
99.125364
99.014887
99.082123

34.048
39.818

25
20

99.201128
99.251595

46.711
49.468
53.143
59.938
61.66
64.078
71.651
77.175

30
40
20
6
10
13
5
11

99.548286
99.733161
99.064787
99.369348
98.96205
99.934455
99.426386
99.876903

2θ
22.723
26.346
27.681
31.474
32.533
33.536
34.466
39.311
40.796
46.534
49.496

PHASE

int

%Δ2θ

80
80
80
100
90
90
90
80
90
80
90

99.133037
98.990359
99.281095
99.955519
99.794055
99.451336
99.576394
99.468342
99.499951
99.926935
99.789882

HA
TCP
TCP
OCP
OCP
OCP
TCP
HA
TCP
HA
HA
HA
TCP
TCP
HA
HA
HA

22 
 

23 
 

Appendix 3 JCPDS reference
Hydroxyapatite

Tri Calcium Phosphate

24 
 
Octa Calcium Phosphate

 

Appendix 4 Lattice parameter calculation match to HA

2
Where,  C = λ

1 4 ⎛ h 2 + hk + k 2 ⎞ l 2
⎟⎟ + 2
= ⎜
d 2 3 ⎜⎝
a2
⎠ c
sin

2

2
B = λ

θ = Cα + Bγ + Aδ

A = D

3a 2
4c

2

∑ α sin
∑ γ sin
∑ δ sin

α = ( h 2 + hk + k 2 )
γ = l2
δ = 10 sin 2 2 θ

10

2

θ = C ∑ α 2 + B ∑ αγ + A∑ αδ

2

θ = C ∑ αγ + B ∑ γ 2 + A∑ γδ

2

θ = C ∑ αδ + B ∑ δγ + A∑ δ

2

B1-1

2θ

h

k

l

α

γ

2θ
(rad)

θ

δ

16.8

1

0

1

1

1

0.294

0.147

0.839

25.9

0

0

2

0

4

0.452

0.226

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

a (Å)

accuracy

c (Å)

accuracy

0.021

0.021

0.021

0.018

1

1

0.704

1

0.839

0.839

9.295

98.7

6.797

98.73

1.905

0.05

0

0.201

0.096

0

16

3.63

0

7.621

0

sin2θ

48

3

1

2

13

4

0.838

0.419

5.523

0.165

2.151

0.662

0.914

169

16

30.5

52

22.09

71.79

53.1

0

0

4

0

16

0.926

0.463

6.392

0.2

0

3.194

1.276

0

256

40.85

0

102.3

0

64

3

0

4

9

16

1.117

0.559

8.081

0.281

2.529

4.496

2.271

81

256

65.3

144

129.3

72.73

0.718

4.701

8.574

4.574

251

545

141

197

262.1

145.4

Σ

25 
 

Continue
B1-2

2θ

h

k

l

α

γ

2θ
(rad)

θ

δ

sin2θ

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

25.9

0

0

2

0

4

0.451

0.226

1.902

0.05

0

0.2

0.095

0

16

3.619

0

7.61

0

28.8

2

1

0

7

0

0.503

0.252

2.324

0.062

0.434

0

0.144

49

0

5.4

0

0

16.27

31.7

2

1

1

7

1

0.554

0.277

2.764

0.075

0.523

0.075

0.206

49

1

7.641

7

2.764

19.35

32.8

3

0

0

9

0

0.572

0.286

2.928

0.08

0.716

0

0.233

81

0

8.574

0

0

26.35

39.5

3

1

0

13

0

0.69

0.345

4.053

0.114

1.487

0

0.464

169

0

16.43

0

0

52.69

45.4

2

0

3

4

9

0.792

0.396

5.066

0.149

0.595

1.339

0.754

16

81

25.67

36

45.6

20.27

46.7

2

2

2

12

4

0.814

0.407

5.29

0.157

1.882

0.627

0.83

144

16

27.98

48

21.16

63.47

48

3

1

2

13

4

0.838

0.419

5.526

0.166

2.152

0.662

0.915

169

16

30.54

52

22.1

71.84

49.4

2

1

3

7

9

0.862

0.431

5.765

0.175

1.222

1.572

1.007

49

81

33.23

63

51.88

40.35

50.2

3

2

1

19

1

0.876

0.438

5.903

0.18

3.419

0.18

1.062

361

1

34.84

19

5.903

112.1

53.2

0

0

4

0

16

0.929

0.464

6.415

0.201

0

3.21

1.287

0

256

41.15

0

102.6

0

64

3

0

4

9

16

1.118

0.559

8.084

0.281

2.53

4.498

2.273

81

256

65.35

144

129.3

72.75

71.3

4

3

1

37

1

1.244

0.622

8.972

0.34

12.57

0.34

3.048

1369

1

80.5

37

8.972

332

73.7

4

2

3

28

9

1.286

0.643

9.208

0.359

10.06

3.234

3.309

784

81

84.8

252

82.88

257.8

76

4

3

2

37

4

1.326

0.663

9.415

0.379

14.02

1.516

3.569

1369

16

88.64

148

37.66

348.3

2.766

51.61

17.45

19.19

4690

822

554.3

806

518.5

1434

Σ

a (Å)

accuracy

c (Å)

accuracy

9.443

99.73

6.863

99.69

26 
 

Continue
B2-1

2θ

h

k

l

α

γ

2θ
(rad)

θ

δ

sin2θ

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

a (Å)

accuracy

c (Å)

accuracy

9.385

99.65

6.804

98.83

23.1

1

1

1

3

1

0.404

0.202

1.544

0.04

0.121

0.04

0.062

9

1

2.385

3

1.544

4.633

33.7

2

0

2

4

4

0.587

0.294

3.072

0.084

0.335

0.335

0.258

16

16

9.438

16

12.29

12.29

39.3

2

1

2

7

4

0.686

0.343

4.008

0.113

0.791

0.452

0.453

49

16

16.07

28

16.03

28.06

46.4

2

2

2

12

4

0.81

0.405

5.244

0.155

1.862

0.621

0.814

144

16

27.5

48

20.98

62.93

49.5

2

1

3

7

9

0.865

0.432

5.789

0.176

1.229

1.58

1.016

49

81

33.51

63

52.1

40.52

58

5

0

1

25

1

1.012

0.506

7.189

0.235

5.872

0.235

1.689

625

1

51.68

25

7.189

179.7

62.6

5

0

2

25

4

1.092

0.546

7.879

0.27

6.744

1.079

2.125

625

16

62.08

100

31.52

197

64.1

3

0

4

9

16

1.119

0.56

8.095

0.282

2.536

4.508

2.281

81

256

65.52

144

129.5

72.85

77.2

5

1

3

31

9

1.347

0.673

9.506

0.389

12.06

3.5

3.697

961

81

90.37

279

85.56

294.7

1.743

31.54

12.35

12.39

2559

484

358.6

706

356.7

892.7

Σ

27 
 

Continue
B2-2

2θ

h

k

l

α

γ

2θ
(rad)

θ

δ

sin2θ

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

a (Å)

accuracy

c (Å)

accuracy

9.648

97.56

7.006

98.23

22.9

1

1

1

3

1

0.4

0.2

1.517

0.039

0.118

0.039

0.06

9

1

2.3

3

1.517

4.55

39.5

3

1

0

13

0

0.69

0.345

4.049

0.114

1.486

0

0.463

169

0

16.4

0

0

52.64

46.5

2

2

2

12

4

0.812

0.406

5.262

0.156

1.87

0.623

0.82

144

16

27.68

48

21.05

63.14

49.6

2

1

3

7

9

0.866

0.433

5.799

0.176

1.232

1.583

1.02

49

81

33.63

63

52.19

40.6

53.6

0

0

4

0

16

0.936

0.468

6.485

0.204

0

3.257

1.32

0

256

42.06

0

103.8

0

64.1

3

0

4

9

16

1.119

0.56

8.095

0.282

2.536

4.508

2.281

81

256

65.52

144

129.5

72.85

71.2

4

3

1

37

1

1.243

0.622

8.966

0.339

12.55

0.339

3.041

1369

1

80.38

37

8.966

331.7

77.1

5

1

3

31

9

1.345

0.673

9.5

0.388

12.03

3.494

3.688

961

81

90.25

279

85.5

294.5

1.698

31.83

13.84

12.69

2782

692

358.2

574

402.5

860

Σ

28 
 

Appendix 5 Lattice parameter calculation match to TCP

2
Where,  C = λ

1 4 ⎛ h 2 + hk + k 2 ⎞ l 2
⎟⎟ + 2
= ⎜
d 2 3 ⎜⎝
a2
⎠ c
sin

2
B = λ

θ = Cα + Bγ + Aδ

2

A = D

3a 2
4c

2

∑ α sin
∑ γ sin
∑ δ sin

α = ( h 2 + hk + k 2 )
γ = l2
δ = 10 sin 2 2 θ

10

2

θ = C ∑ α 2 + B ∑ αγ + A∑ αδ

2

θ = C ∑ αγ + B ∑ γ 2 + A∑ γδ

2

θ = C ∑ αδ + B ∑ δγ + A∑ δ

2

B1-1

2θ

h

k

l

α

γ

2θ
(rad)

θ

δ

sin2θ

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

13.6

1

0

4

1

16

0.237

0.118

0.55

0.014

0.014

0.223

0.008

1

256

0.302

16

8.796

0.55

27.8

2

1

4

7

16

0.485

0.243

2.175

0.058

0.404

0.923

0.126

49

256

4.731

112

34.8

15.23

29.7

3

0

0

9

0

0.519

0.26

2.461

0.066

0.593

0

0.162

81

0

6.055

0

0

22.15

31.1

0

2

10

4

100

0.542

0.271

2.665

0.072

0.287

7.178

0.191

16

10000

7.102

400

266.5

10.66

34.3

2

2

0

12

0

0.599

0.299

3.179

0.087

1.045

0

0.277

144

0

10.11

0

0

38.15

35.6

2

1

10

7

100

0.621

0.311

3.389

0.093

0.654

9.345

0.317

49

10000

11.48

700

338.9

23.72

37.3

1

2

11

7

121

0.652

0.326

3.679

0.102

0.717

12.4

0.377

49

14641

13.53

847

445.2

25.75

41.1

4

0

4

16

16

0.718

0.359

4.328

0.123

1.975

1.975

0.534

256

256

18.73

256

69.25

69.25

43.9

2

3

2

19

4

0.766

0.383

4.805

0.14

2.652

0.558

0.671

361

16

23.08

76

19.22

91.29

50.1

3

2

10

19

100

0.875

0.437

5.889

0.179

3.409

17.94

1.057

361

10000

34.68

1900

588.9

111.9

57.5

5

1

4

31

16

1.004

0.502

7.119

0.232

7.181

3.706

1.649

961

256

50.69

496

113.9

220.7

59.7

5

1

7

31

49

1.041

0.521

7.448

0.247

7.67

12.12

1.843

961

2401

55.48

1519

365

230.9

60.9

2

1

22

7

484

1.063

0.532

7.638

0.257

1.799

124.4

1.963

49

234256

58.33

3388

3697

53.46

1.671

28.4

190.8

9.173

3338

282338

294.3

9710

5947

913.7

Σ

a (Å)

accuracy

c (Å)

accuracy

10.4

99.76

37.22

99.56

29 
 

Continue
B1-2

2θ

h

k

α

l

27.8

2

1

29.6

3

31.2

0

34.4
41.1

γ

2θ
(rad)

θ

δ

16

0.486

0.243

2.178

α2

γ2

αsin2θ

γsin2θ

δsin2θ

0.058

0.405

0.925

0.126

49

sin2θ

αγ

δγ

αδ

a (Å)

accuracy

c (Å)

accuracy

4.744

112

34.85

15.25

10.46

99.57

37.4

99.951

4

7

0

0

9

0

0.517

0.258

2.44

0.065

0.587

0

0.159

81

0

5.952

0

0

21.96

2

10

4

100

0.544

0.272

2.677

0.072

0.289

7.214

0.193

16

10000

7.168

400

267.7

10.71

2

2

0

12

0

0.6

0.3

3.189

0.087

1.048

0

0.279

144

0

10.17

0

0

38.26

4

0

4

16

16

0.718

0.359

4.325

0.123

1.973

1.973

0.533

256

256

18.7

256

69.2

69.2

43.9

2

3

2

19

4

0.767

0.383

4.815

0.14

2.659

0.56

0.674

361

16

23.18

76

19.26

91.49

45.4

2

2

12

12

144

0.792

0.396

5.066

0.149

1.786

21.43

0.754

144

20736

25.67

1728

729.5

60.8

59.6

5

1

7

31

49

1.041

0.52

7.442

0.247

7.661

12.11

1.839

961

2401

55.39

1519

364.7

230.7

61

2

1

22

7

484

1.065

0.532

7.65

0.258

1.803

124.7

1.97

49

234256

58.52

3388

3702

53.55

66.2

5

2

6

39

36

1.156

0.578

8.377

0.299

11.64

10.75

2.501

1521

1296

70.17

1404

301.6

326.7

1.498

29.85

179.6

9.028

3582

269217

279.7

8883

5489

918.6

Σ

256

δ2

B2-1
2θ

h

k

α

l

γ

2θ
(rad)

θ

δ

sin2θ

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

a (Å)

accuracy

c (Å)

accuracy

10.17

97.621

36.16

96.738

21.5

0

1

8

1

64

0.375

0.187

1.338

0.035

0.035

2.218

0.046

1

4096

1.791

64

85.66

1.338

26.1

2

1

1

7

1

0.456

0.228

1.935

0.051

0.357

0.051

0.099

49

1

3.746

7

1.935

13.55

28.5

1

2

5

7

25

0.498

0.249

2.283

0.061

0.425

1.519

0.139

49

625

5.21

175

57.07

15.98

29.6

3

0

0

9

0

0.516

0.258

2.437

0.065

0.586

0

0.159

81

0

5.938

0

0

21.93

41

4

0

4

16

16

0.715

0.358

4.301

0.123

1.96

1.96

0.527

256

256

18.5

256

68.81

68.81

44.9

3

1

11

13

121

0.784

0.392

4.986

0.146

1.897

17.66

0.728

169

14641

24.86

1573

603.3

64.82

50.6

5

0

2

25

4

0.884

0.442

5.978

0.183

4.573

0.732

1.093

625

16

35.74

100

23.91

149.4

53.9

3

0

18

9

324

0.94

0.47

6.522

0.205

1.846

66.46

1.338

81

104976

42.53

2916

2113

58.7

59.6

5

1

7

31

49

1.041

0.52

7.442

0.247

7.661

12.11

1.839

961

2401

55.39

1519

364.7

230.7

1.115

19.34

102.7

5.968

2272

127012

193.7

6610

3318

625.3

Σ

Continue

30 
 

B2-2

2θ

h

k

α

l

2θ
(rad)

γ

θ

δ

sin2θ

αsin2θ

γsin2θ

δsin2θ

α2

γ2

δ2

αγ

δγ

αδ

a (Å)

accuracy

c (Å)

accuracy

10.32

99.08

36.91

98.75

26.1

2

1

1

7

1

0.455

0.228

1.933

0.051

0.356

0.051

0.098

49

1

3.735

7

1.933

13.53

27.9

2

1

4

7

16

0.487

0.243

2.187

0.058

0.406

0.929

0.127

49

256

4.782

112

34.99

15.31

34.3

2

2

0

12

0

0.599

0.299

3.179

0.087

1.045

0

0.277

144

0

10.11

0

0

38.15

41

4

0

4

16

16

0.716

0.358

4.304

0.123

1.962

1.962

0.528

256

256

18.53

256

68.87

68.87

59.6

5

1

7

31

49

1.04

0.52

7.433

0.247

7.647

12.09

1.834

961

2401

55.25

1519

364.2

230.4

61

2

1

22

7

484

1.065

0.532

7.653

0.258

1.804

124.7

1.972

49

234256

58.56

3388

3704

53.57

0.823

13.22

139.8

4.836

1508

237170

151

5282

4174

419.8

Σ

31 
 

Appendix 6 FTIR spectra of BCP samples
B1-1

32 
 

Continue
B1-2

33 
 

Continue
B2-1

34 
 

Continue
B2-2

35 
 

1 
 

INTRODUCTION
Background
Over 8 million surgical procedures are
performed annually in the United States to
treat million of Americans experiencing organ
failure or tissue loss. Although the procedures
for organ transplantation and reconstruction
surgery improve the quality of life, and in
some cases save life, there are problems
associated with them. In most cases these
procedures require either organ donation from
a donor individual or tissue transplantation
from a second surgical site of patient. The
major problem with organ transplantation is
the drastic shortage of donor organs. In 1996
alone, only 20.000 donor organs were
available for 50.000 patients in need. In fact,
patients are more likely to die while waiting
for a human donor heart than in the first two
years after transplantation. The problem with
second site surgeries is that these procedures
are associated with pain and morbidity. As a
result of these problems, the science of tissue
engineering has emerged with the goal of
developing organs, tissues, and synthetic
materials outside of the body ready for future
transplant use1. Besides tissue engineering
offers a promising approach toward healing of
large bone defects and could help an
estimated 200.000 patients each year2.
Hard tissue diseases and defects,
osteoporosis, and osteoarthritis are some of
the most significant related medical
conditions leading to an extensive need for
the use of appropriate implant materials.
Therefore, an appropriate technique is needed
to stimulate tissue repairing by induction and
regeneration despite of eliminating problems
of donor scarcity, supply limitation, pathogen
transfer, and immune rejection. Different
approaches applying synthetic materials are in
current utilization to solve bone tissue related
clinical conditions. One of them is the use of
materials as bone substitute. Several materials
produced by different synthesis methods have
been developed and used as bone plants such
as corals derivatives, calcium phosphates,
alumina, titania, polyurethane, Co–Cr alloys,
PMMA3.
The use of Calcium Phosphate materials
as bone substitutes has increased in the last
years. Although the autologous bone grafts
remain as the gold standard, the low
disponibility and the morbidity of the patient
donor site have made Calcium Phosphate
materials as the best bone substitutes for

 

certain applications, bone grafting, bone
fillers in trauma, fracture repair or in dental
applications. Their chemical structure are
close to bone mineral, their osteoconductivity
and osteoinductivity, the ability to be resorbed
by the organism and the biocompatibility of
the degradation products as a source of
calcium and phosphate ions in the implant
site, make them very suitable biomaterials4.
Most calcium phosphate ceramics are
classified as bioactive ceramics, they elicit a
direct bond between the ceramics and living
bone tissue. Because of this excellent
compatibility with bone tissue, these materials
are appealing for bone tissue engineering.
Although there are many varieties of bioactive
ceramics, bone tissue engineers have focused
almost exclusively on hydroxyapatite (HA)
and tricalcium phosphate (TCP); ceramics
that closely resemble the mineral phase of
bone. Although HA is a well-defined
crystalline material which is very stable under
physiological conditions, TCP, the dehydrated
version of HA, is much less defined and less
stable under physiological conditions.
Because HA is very stable under
physiological conditions leading to extremely
slow or nonexistent resorption, TCP may have
a biological advantage over HA in its
biodegradability, resulting in a faster
replacement of the material with bone tissue2.
Both of these osteoconductive bioceramics
bond tightly with bone, but HA is less
resorbable than -TCP. As an ideal bone
grafting material should be replaceable by
new bone, it needs to be both biodegradable
and osteoconductive. A mixture of HA and TCP produces biphasic calcium phosphate
(BCP) which possesses the reactivity of TCP and the stability of HA, providing more
bioactivity, involving more new bone growth,
and ensuring better resistance of the implants
to strain5.
The inorganic component of the bone
tissue is non-stoichiometric apatite. This
evidence stimulated design and development
of a new generation of synthetic resorbable
apatite substitutes, which, stimulating some
properties of the biological phase, which after
implantation can actively participate to the
bone generation, solving the problem caused
by stoichiometric HA implants7. In order to
determine whether a new material conforms
to the requirements of biocompatibility and
mechanical stability prior to clinical use, it
must undergo rigorous testing under both
initial in vitro and in vivo conditions6.

2 
 
Objectives of the Research
1. Synthesizing biomaterial which analyzed
by X-Ray Diffraction (XRD), Fourier
Transform Infrared (FTIR), and Scanning
Electron
Microscopy
(SEM)
characterization
2. Observing biomaterial growth which is
implanted by in vivo experiment into
sheep’s bone.
Time and Place of Research
This research was conducted from
December 2008 through July 2009 which held
in
IPB-Biophysics
Laboratory.
The
characterization was done in three different
laboratory;
Balai
Penelitian
dan
Pengembangan Kehutanan Bogor for XRD,
Integrated Laboratory - Biofarmaka Bogor
Agricultural University for FTIR, and Pusat
Penelitian Geologi Laut (PPGL) Bandung for
SEM.

THEORY
Hidroxyapatite
Apatite minerals are found in almost all
igneous rocks as well as in sedimentary and
metamorphic rocks. They are the most
abundant phosphorus bearing minerals. The
commonest varieties are:
Fluorapatite
Ca10(PO4)6F2
Chloroapatite
Ca10(PO4)6Cl2
Hydroxyapatite Ca10(PO4)6(OH)2
Podolite
Ca10(PO4)6CO3
Dahliite
Ca10(PO4 , CO3)6(OH)2
Francolite
Ca10(PO4 , CO3)6(F , OH)2
“Apatite” is a general term for crystalline
minerals with composition of M10(ZO4)6X2.
The name was taken from the Greek word
“apato” by Werner which means deceit.
Many elements occupy the M, Z, and X sites:
M = Ca, Sr, Ba, Cd, Pb, etc.
Z = P, V, As, S, Si, Ge, CO3, etc.
X = F, Cl, OH, O, Br, CO3, etc8.
The apatite structure is very hospitable in
allowing the substitutions of many other ions.
Ca, PO4, and OH groups in apatite can be
substituted. Carbonate (CO3) can substitute
either for the hydroxyl (OH) or the phosphate
(PO4) group, designated as Type A or Type B
substitution, respectively. The substitutions
cause morphological changes in precipitated
apatite crystals as well as their properties. For
example, CO3 substituted apatite is more
soluble than CO3 – free synthetic apatite9

 

“Hydroxyapatite” is a member of the
apatite group of minerals, and its chemical
formula is Ca10(PO4)6(OH)2. Hydroxyapatite
is a calcium phosphate including hydroxide
and its Ca/P ratio is represented as 1.678.
Hydroxyapatite is a hexagonal crystal with
P63/m symmetry and lattice parameters quite
similar to aragonite, and has even been
hydrothermally converted from biological and
geological aragonite10.
Hydroxyapatite is the most commonly
used calcium phosphate in the medical field,
as it possesses excellent biocompatibility and
is osteoconductive9. Hydroxyapatite has been
utilized as a fertilizer, a fluorescent substance,
an absorbent, a catalyst, and many kinds of
biomaterials.
Biomaterials
based
on
hydroxyapatite have been applied to dental,
orthopedic, and other medical uses8.
Generally, there are three essential
methods for preparing crystals, including the
process from solid reaction to solid crystals,
from solution to solid crystals, and from vapor
to solid crystals. Up to the present, the
following various methods for preparing
hydroxyapatite have been:
1. Wet method, using solution reaction (from
solution to solid)
2. Dry method, using solid reaction (from
solid to solid)
3. Hydrothermal method, using hydrothermal
reaction (from solution to solid)
4. Alkoxide method, using hydrolysis
reaction (from solution to solid)
5. Flux method, using fused salt reaction
(from melt to solid)
Table

1

Unit cell parameters
hydroxyapatite10.

axial lengths (nm)
a
9.418

b
9.418

c
6.884

for

angles(degree)
α
90

90

Figure 1 Hydroxyapatite structure11.

γ
120

2 
 
Objectives of the Research
1. Synthesizing biomaterial which analyzed
by X-Ray Diffraction (XRD), Fourier
Transform Infrared (FTIR), and Scanning
Electron
Microscopy
(SEM)
characterization
2. Observing biomaterial growth which is
implanted by in vivo experiment into
sheep’s bone.
Time and Place of Research
This research was conducted from
December 2008 through July 2009 which held
in
IPB-Biophysics
Laboratory.
The
characterization was done in three different
laboratory;
Balai
Penelitian
dan
Pengembangan Kehutanan Bogor for XRD,
Integrated Laboratory - Biofarmaka Bogor
Agricultural University for FTIR, and Pusat
Penelitian Geologi Laut (PPGL) Bandung for
SEM.

THEORY
Hidroxyapatite
Apatite minerals are found in almost all
igneous rocks as well as in sedimentary and
metamorphic rocks. They are the most
abundant phosphorus bearing minerals. The
commonest varieties are:
Fluorapatite
Ca10(PO4)6F2
Chloroapatite
Ca10(PO4)6Cl2
Hydroxyapatite Ca10(PO4)6(OH)2
Podolite
Ca10(PO4)6CO3
Dahliite
Ca10(PO4 , CO3)6(OH)2
Francolite
Ca10(PO4 , CO3)6(F , OH)2
“Apatite” is a general term for crystalline
minerals with composition of M10(ZO4)6X2.
The name was taken from the Greek word
“apato” by Werner which means deceit.
Many elements occupy the M, Z, and X sites:
M = Ca, Sr, Ba, Cd, Pb, etc.
Z = P, V, As, S, Si, Ge, CO3, etc.
X = F, Cl, OH, O, Br, CO3, etc8.
The apatite structure is very hospitable in
allowing the substitutions of many other ions.
Ca, PO4, and OH groups in apatite can be
substituted. Carbonate (CO3) can substitute
either for the hydroxyl (OH) or the phosphate
(PO4) group, designated as Type A or Type B
substitution, respectively. The substitutions
cause morphological changes in precipitated
apatite crystals as well as their properties. For
example, CO3 substituted apatite is more
soluble than CO3 – free synthetic apatite9

 

“Hydroxyapatite” is a member of the
apatite group of minerals, and its chemical
formula is Ca10(PO4)6(OH)2. Hydroxyapatite
is a calcium phosphate including hydroxide
and its Ca/P ratio is represented as 1.678.
Hydroxyapatite is a hexagonal crystal with
P63/m symmetry and lattice parameters quite
similar to aragonite, and has even been
hydrothermally converted from biological and
geological aragonite10.
Hydroxyapatite is the most commonly
used calcium phosphate in the medical field,
as it possesses excellent biocompatibility and
is osteoconductive9. Hydroxyapatite has been
utilized as a fertilizer, a fluorescent substance,
an absorbent, a catalyst, and many kinds of
biomaterials.
Biomaterials
based
on
hydroxyapatite have been applied to dental,
orthopedic, and other medical uses8.
Generally, there are three essential
methods for preparing crystals, including the
process from solid reaction to solid crystals,
from solution to solid crystals, and from vapor
to solid crystals. Up to the present, the
following various methods for preparing
hydroxyapatite have been:
1. Wet method, using solution reaction (from
solution to solid)
2. Dry method, using solid reaction (from
solid to solid)
3. Hydrothermal method, using hydrothermal
reaction (from solution to solid)
4. Alkoxide method, using hydrolysis
reaction (from solution to solid)
5. Flux method, using fused salt reaction
(from melt to solid)
Table

1

Unit cell parameters
hydroxyapatite10.

axial lengths (nm)
a
9.418

b
9.418

c
6.884

for

angles(degree)
α
90

90

Figure 1 Hydroxyapatite structure11.

γ
120

3 
 
The wet method is useful for preparing
very small crystals of hydroxyapatite while
the dry method is convenient for preparing
well-crystallized
hydroxyapatite.
The
hydrothermal method is used for preparing
single crystals of hydroxyapatite. The
alkoxide method is used for preparing thin
membranes of polycrystalline hydroxyapatite.
The flux method is used for preparing large
single crystals of apatite compounds. Pure
hydroxyapatite has not been prepared by the
flux method8.
Tri Calcium Phosphate (TCP)
TCP is a kind of Calcium Phosphate with
Ca/P ratio 1.50 and represented as Ca3(PO4)28.
TCP has four polymorphs: α, , γ, and superα. The γ polymorph is a high pressure phase
and the super- α polymorph is observed at
temperature above approximately 15000C.
Therefore, the most frequently observed TCP
polymorphs in the field of bioceramics are
α and -TCP9.
α-TCP crystal is in the monoclinic space
group P21/a with lattice parameters
a = 1.2887 nm, b = 2.7280 nm, c = 1.5219
nm, and = 126.200. There are 24 formula
units per unit cell. There is a prominent
approximate sub cell with a b axis parameter
of b/3 (0.909 nm) that contains eight formula
units. The structure comprises columns of
Ca2+ and PO43- ions parallel to the c axis9.
-TCP has the rhombohedral space group
R3c with unit cell a = 1.0439 nm, c = 3.7375
nm (hexagonal setting) with 21 formula units
per hexagonal unit cell. The structure of TCP has been determined and described in
terms of a distortion from the Ba3(VO4)2
structure. The -TCP structure is similar to
Ba3(VO4)2 but has three fewer formula units
per hexagonal unit cell. -TCP is stable up to
11250C but above this temperature and up to
14300C, α-TCP becomes the stable phase.
Super-α-TCP forms between 14300C and the
melting point at 17560C9.
Compared to -TCP , α-TCP has a lower
density and a higher free energy of formation
and therefore it is expected to be more
reactive. α-TCP is fairly reactive in aqueous
systems and can be hydrolyzed to mixtures of
DCPD, calcium-deficient oxyhydroxyapatite,
and other calcium phosphates in varying
proportions, depending upon the conditions.
-TCP does not form in aqueous systems.
Some evidence showed that -TCP is always
more soluble than oxyhydroxyapatite, but
above pH = 6, it is less soluble than other

 

calcium phosphate. Moreover, the solubility
of
-TCP decreases with increase in
temperature9.
Most of the reports on TCP have
concluded that TCP is biodegradable,
although there are some differences that is
depending on the characteristics of the
material used. Due in part to its crystalline
structure, the biodegradation rate of TCP has
been shown to be much greater than that of
HA. TCP has an important role as a
resorbable bioceramics due to its high
solubility and bioactivity. -TCP has been
accepted and used as a biocompatible,
resorbable material for bone repair in the form
of ceramics blocks, granules, and calcium
phosphate cement9.
X-Ray Diffraction (XRD)
X-ray Diffraction analysis utilizes X-ray
emission resulting from collision between
electron and target that can be Cr, Fe, Co, Cu,
Mo or W. X-ray emission is distributed
continuously and specifically for each certain
wavelength of target (Figure 2). As side
affect, the electron kinetic energy change
become heat, so the X-ray quantities
influenced by melting point and thermal
conductivity of target. This analysis could
inform us about the structure of sample, such
as crystal system, lattice parameter, and
preferred orientation. It is also useful to
identify a mixture which is referred to as semi
quantitative identification of sample phase.

Cathode

Fast electrons

 

Target

Figure 2 The principle of an X-Ray tubes.

Figure 3 Diffraction of X-Ray by a crystal.

4 
 
Then X-ray is transmitted through sample that
will be characterized, so x-ray will be
transformed into varied type of energy and
absorbed some11.
Interaction of X-rays with sample creates
secondary diffracted beams of X-rays related
to interplanar spacings in the crystalline
powder according to a mathematical relation
called Bragg’s Law below, which refers to
Figure 3:
n =2 d sin θ
where n is an integer, is the wavelength of
the X-rays, d is the interplanar spacing
generating the diffraction, θ is the diffraction
angle. and d are measured in the same units,
usually angstroms12.
Scanning Electron Microscope (SEM)
The Scanning Electron Microscope (SEM)
has unique capabilities for analyzing surfaces.
It is analogous to the reflected light
microscope, although different radiation
sources serve to produce the required
illumination. Whereas the reflected light
microscope forms an image from light
reflected from a sample surface, the SEM uses
electrons for image formation.
The difference between light and scanning
electron imaging concerns the depth of field
defined as the ability to maintain focus across
a held of view regardless of surface
roughness. Conventional photographs and
photomicrographs
are
two-dimensional
representations; the dimension of depth is
suppressed when recording an image with a
diffuse light source. In contrast, SEM
micrograph maintains the three-dimensional
appearance
of
textured
surfaces,
a
phenomenon due to the high depth of field of
scanning instruments. Depth of field is further
suppressed in both macrophotography and
photomicrography as magnification is
increased. At 10x, the relative depth of field
of a light microscope is about 250 m, while
that of the SEM is about 1000 m; at 1200x
the depth of field of a light microscope is
~0.08 m; at 10000x, the depth of field of the
SEM is 10 m.
The combination of high resolution, an
extensive magnification range, and high depth
of field makes the SEM uniquely suited for
the study of surfaces. As such, it is an
indispensable tool in materials science
research and development13.  

 

Figure 4 Schematic of scanning electron
microscope experiment.

b

Figure 5 SEM micrographs of BCP micro
particle (a) particle size < 2 m
(b) particle size 80-200 m14.

5 
 
In the SEM, the image is formed and
displayed by making use of electrons. The
column of an SEM contains an electron gun
for producing electrons and electromagnetic
lenses corresponding to the condenser
system. However, these lenses are operated in
such a way as to produce a very fine electron
beam, which is focused on the surface of the
sample.
At any given moment, the sample is
bombarded with electrons over a very small
area. They may be elastically reflected from
the sample or absorbed by the sample and
give rise to secondary electrons of very low
energy, together with X- rays. They may be
absorbed and give rise to the emission of
visible light. In addition, they may give rise to
electric currents within the sample. All these
effects can be used to produce an image. By
far the most common, however, is image
formation by means of the low-energy
secondary electrons11.
Fourier Transform Infrared (FTIR)
Infrared (IR) spectroscopy is one of the
most common spectroscopic techniques used
by organic and inorganic chemists. Simply, it
is the absorption measurement of different IR
frequencies by a sample positioned in the path
of an IR beam. The main goal of IR
spectroscopic analysis is to determine the
chemical functional groups in the sample.
Different
functional
groups
absorb
characteristic frequencies of IR radiation.
Using various sampling accessories, IR
spectrometers can accept a wide range of
sample types such as gases, liquids, and
solids. Thus, IR spectroscopy is an important
and popular tool for structural elucidation and
compound identification.

Figure 6

 

Schematic illustration of FTIR
system.

In simple terms, IR spectra are obtained
by detecting changes in transmittance (or
absorption) intensity as a function of
frequency. Most commercial instruments
separate and measure IR radiation using
dispersive spectrometers or Fourier transform
spectrometers.
Fourier
transform
spectrometers
have
recently
replaced
dispersive instruments for most applications
due to their superior speed and sensitivity.
They have greatly extended the capabilities of
infrared spectroscopy and have been applied
to many areas that are very difficult or nearly
impossible to analyze by dispersive
instruments. Instead of viewing each
component frequency sequentially, as in a
dispersive IR spectrometer, all frequencies are
examined simultaneously in Fourier transform
infrared (FTIR) spectroscopy15.
Animal used
Animal used in this experiment was sheep.
In the period of 1990-2001, sheep were used
in 9-12% of orthopedic research involving
fractures, osteoporosis, bone-lengthening and
osteoarthritis, in comparison with just over
5% in the period from 1980-1989. Most of the
literature reports that the dog is more suitable
as a model for human bone from a biological
standpoint than the sheep; however, adult
sheep offer the advantage of being of a more
similar body weight to humans and having
long bones of dimensions suitable for the
implantation of human implants and
prostheses, which is not possible in smaller
species such as rabbits or smaller breeds of
dog5.
While macroscopically, sheep’s bones
relatively similar to the human bones,
histologically, the bone structure of the sheep
is quite different. Sheep are described as
having a predominantly primary bone
structure (osteons less than 100µm diameter
containing at least two central blood vessels
and the absence of a cement line) in
comparison with the largely secondary bone
of humans5.
Differences in bone density exist between
the human and sheep, whereby sheep bone
shows a significantly higher density and
subsequently
greater
strength.
While
differences in bone structure are recognized,
several studies argue that the sheep is still a
valuable model for human bone turnover and
remodeling activity. In support of this theory,
a study observing bone ingrowths into porous
implants placed into the distal femur of sheep

6 
 
(a weight-bearing model), show that sheep
and humans have a similar pattern of bone ingrowth into porous implants over time5.

MATERIALS AND METHODS
Materials and Equipments
The materials used in this research are
pro-analyze Na2HPO4.2H2O, pro-analyze
CaCl2.2H2O, nitrogen (N2), aquadest, and
aquabidest. While the equipments are beaker
glass, mortar, aluminum foil, whatman paper,
Mohr pipette, magnetic stirrer, hotplate,
analytical
scales,
furnace,
digital
thermometer, and press machine.
Materials and equipments used for in vivo
experiment are sheep as animal model, minor
surgery set, orthopedic surgery tools,
anesthetic material, and surgery room for
aseptical implantation.
Methods
Preparation and characterization of
Biphasic Calcium Phosphate (BCP)
ceramics
Table 2

Various concentrations of starting
solutions   
CaCl2.2H2O

Na2HPO4.2H2O

M

M

A

0.2

0.2

B

0.334

0.2

Code

Starting materials used in this research
were analytical grade CaCl2.2H2O as Calcium
(Ca) source and Na2HPO4.2H2O as Phosphor
(P) source with Ca/P ratio 1.67. BCP was
synthesized by reacting 100 ml of
CaCl2.2H2O solution and 100 ml of
Na2HPO4.2H2O solution using a precipitation
method. In this process, Na2HPO4.2H2O
solution was put into the beaker glass and
CaCl2.2H2O solution was put in the burette
and added drop by drop to the solution in
beaker glass. Before reacting these solution,
Na2HPO4.2H2O solution was added with
nitrogen gases at least 3 minutes then stirred
up to 700C. After reaching that temperature,
precipitation was done with constant
temperature on hot plate. The result was
precipitated for ± 12 hours then filtered and
heated up to 10000C for 10 hours. The result
of this process was powder of biphasic
ceramics containing a mixture of HA and

 

TCP. Then, this powder was analyzed using
X-Ray Diffraction with a CuKα source
operated at 40 kV and 30mA. The
microstructure and particle size distribution of
the sample were observed by Scanning
Electron Microscopy. The sample was also
characterized using FTIR for observing the
chemical functional groups of the sample.
After characterization, this powder was
pressed in form pellet using press machine.
Then, it was coated with bone cement and
heated up to 150oC for two hours.
In vivo study in sheep
Six two years old sheep, 18-24 kg in
weight, were used in the study. All
experiments were conducted with strict
observation of institutional guidelines for the
care and use of laboratory animals. Prior to
surgery the sheep were observed closely for 2
weeks in order to check their health status.
They were maintained under identical
environment, management and standard diet
with ad libitum supply of drinking water.
Sheep’s maintenance was done for ten days
pre surgery for evaluation of animal used
condition before experimentation. Sheep’s
maintenance was done in stall of animal used
of FVM Bogor Agricultural University.
The sheep were anaesthetized by
intravenous injection of xylazin 2%. Before
the operation, bone grafts were sterilized by
exposure to ultraviolet light. Under aseptical
conditions, right os tibia of each sheep was
drilled to create a segmental defect with a
critical size defect of 6 mm in diameter. This
segmental defect then implanted with bone
graft prepared before. As control requirement,
left os tibia of each sheep was drilled in the
same manner and diameter with the right os
tibia without implantation of the bone graft.
Each biomaterial implantation was performed
under same veterinary surgeon.
The edges of the bone membrane sutured
with a traumatic suture and the incision was
closed with silk suture. Antibiotics were
injected into the sheep post surgery. All
animals were culled on day 30, day 60, and
day 90 post implantation (PI) for harvesting
bone specimen required for histological and
pathological evaluation. The animals in this in
vivo evaluation were divided into three
groups containing two sheep (each group
contains of male and female). First group was
observed on day 30 PI. Second group was
observed on day 60 PI and the last group was
observed on day 90 PI.

6 
 
(a weight-bearing model), show that sheep
and humans have a similar pattern of bone ingrowth into porous implants over time5.

MATERIALS AND METHODS
Materials and Equipments
The materials used in this research are
pro-analyze Na2HPO4.2H2O, pro-analyze
CaCl2.2H2O, nitrogen (N2), aquadest, and
aquabidest. While the equipments are beaker
glass, mortar, aluminum foil, whatman paper,
Mohr pipette, magnetic stirrer, hotplate,
analytical
scales,
furnace,
digital
thermometer, and press machine.
Materials and equipments used for in vivo
experiment are sheep as animal model, minor
surgery set, orthopedic surgery tools,
anesthetic material, and surgery room for
aseptical implantation.
Methods
Preparation and characterization of
Biphasic Calcium Phosphate (BCP)
ceramics
Table 2

Various concentrations of starting
solutions   
CaCl2.2H2O

Na2HPO4.2H2O

M

M

A

0.2

0.2

B

0.334

0.2

Code

Starting materials used in this research
were analytical grade CaCl2.2H2O as Calcium
(Ca) source and Na2HPO4.2H2O as Phosphor
(P) source with Ca/P ratio 1.67. BCP was
synthesized by reacting 100 ml of
CaCl2.2H2O solution and 100 ml of
Na2HPO4.2H2O solution using a precipitation
method. In this process, Na2HPO4.2H2O
solution was put into the beaker glass and
CaCl2.2H2O solution was put in the burette
and added drop by drop to the solution in
beaker glass. Before reacting these solution,
Na2HPO4.2H2O solution was added with
nitrogen gases at least 3 minutes then stirred
up to 700C. After reaching that temperature,
precipitation was done with constant
temperature on hot plate. The result was
precipitated for ± 12 hours then filtered and
heated up to 10000C for 10 hours. The result
of this process was powder of biphasic
ceramics containing a mixture of HA and

 

TCP. Then, this powder was analyzed using
X-Ray Diffraction with a CuKα source
operated at 40 kV and 30mA. The
microstructure and particle size distribution of
the sample were observed by Scanning
Electron Microscopy. The sample was also
characterized using FTIR for observing the
chemical functional groups of the sample.
After characte