Effect of pH, cationic inducer, and clam shells as bio-flocculant in the optimization of the flocculation process for enhanced microalgae harvesting using response surface methodology

Figures & data

Table 1. Coded value based on the factor at a time experiment for 4 variables employed in the study.

Code	Variables	−2	−1	0	+1	+2
A	pH	6	7	8	9	10
B	Clam shells powder (mg)	50	75	100	125	150
C	Cationic Inducer (mg)	0	25	50	75	100
D	Mixing Rate (rpm)	200	220	240	260	280

Figure 1. Mechanism of microalgae flocculation process.

Figure 2. Effect of pH on bioflocculation.

Figure 3. Effect of bioflocculant on bioflocculation.

Figure 4. Effect of cationic inducer on bioflocculation.

Figure 5. Effect of mixing rate on bioflocculation.

Table 2. Central composite design with observed responses pertaining to flocculation efficiency and recoverable biomass.

Run	pH	Clam Shell [mg/mL]	Cationic Inducer [mg/mL]	Mixing Rate [rpm]	Flocculation Efficiency [%]	Recovered Biomass [mg]
1	7	0.15	0.05	220	75.858	232.7
2	9	0.15	0.05	220	90.185	421.7
3	7	0.25	0.05	220	72.945	199.1
4	9	0.25	0.05	220	87.465	387.9
5	7	0.15	0.15	220	87.179	327.2
6	9	0.15	0.15	220	91.833	447.5
7	7	0.25	0.15	220	81.792	310.1
8	9	0.25	0.15	220	88.314	395.3
9	7	0.15	0.05	260	71.004	145.3
10	9	0.15	0.05	260	83.369	358.2
11	7	0.25	0.05	260	80.103	330.8
12	9	0.25	0.05	260	90.615	453.6
13	7	0.15	0.15	260	87.009	332.1
14	9	0.15	0.15	260	83.689	306.7
15	7	0.25	0.15	260	77.102	278.3
16	9	0.25	0.15	260	81.489	328.6
17	6	0.2	0.1	240	80.461	215.8
18	10	0.2	0.1	240	90.896	450.7
19	8	0.1	0.1	240	77.864	282.1
20	8	0.3	0.1	240	72.981	257.6
21	8	0.2	0.02	240	88.372	357
22	8	0.2	0.2	240	89.708	388.2
23	8	0.2	0.1	200	82.046	337.5
24	8	0.2	0.1	280	83.172	327.8
25	8	0.2	0.1	240	89.154	395.7
26	8	0.2	0.1	240	90.738	432.8
27	8	0.2	0.1	240	88.182	364
28	8	0.2	0.1	240	85.743	357.4
29	8	0.2	0.1	240	91.898	458.1
30	8	0.2	0.1	240	89.657	387.6

Table 3. ANOVA table for response surface function on flocculation efficiency.

Source	SS	DF	MS	F	P
Mean vs Total	2.135E+005	1	2.135E+005
Linear vs Mean	367.98	4	91.99	3.21	0.0293
2FI vs Linear	223.76	6	37.29	1.44	0.2508
Quadratic vs 2FI	379.91	4	94.98	12.75	0.0001
Cubic vs Quadratic	84.95	8	10.62	2.78	0.0979
Residual	26.74	7	3.82
Total	2.146E+005	30	7152.85

Table 4. ANOVA table for response surface function on biomass.

Source	SS	DF	MS	F	P
Mean vs Total	3.514E+006	1	3.514E+006
Linear vs Mean	88,023.21	4	22,005.80	5.88	0.0018
2FI vs Linear	38,259.77	6	6376.63	2.19	0.0896
Quadratic vs 2FI	35217.48	4	8804.37	6.57	0.0029
Cubic vs Quadratic	9830.30	8	1228.79	0.84	0.5986
Residual	10,258.57	7	1465.51
Total	3.696E+006	30	1.232E+005

Figure 6. 3D response surface and contour plots illustrating the interaction effects of a) Perna viridis-pH, b) cationic inducer-pH, c) mixing rate-pH, d) cationic inducer-Perna viridis, e) mixing rate- Perna viridis, and f) mixing rate-cationic inducer on the flocculation efficiency of Chlorella sp. Flocculation.

Figure 7. 3D response surface and contour plots illustrating the interaction effects of a) Perna viridis-pH, b) cationic inducer-pH, c) mixing rate-pH, d) cationic inducer-Perna viridis, e) mixing rate- Perna viridis, and f) mixing rate-cationic inducer on the biomass of Chlorella sp. flocculation.

Figure 8. SEM images of microalgae (a) before and (b) after flocculation.

Table 5. Energy Dispersive X-ray spectroscopy (EDX) analysis results for the chemical constituents of Chlorella sp flocculation.

Chlorella sp. content	Before flocculation	After Flocculation with dose optimum
Carbon, C	62.69	33.33
Nitrogen, N	28.77	8.35
Natrium Oxide, Na2O	3.26	-
Magnesium Oxide, MgO	0.28	0.45
Silica Dioxide, SiO2	0.20	1.02
Phosphor Pentoxide, P2O5	2.05	21.13
Sulfide, SO3	1.22	-
Chloride, Cl	-	-
Kalium Oxide, K2O	0.34	-
Calcium Oxide, CaO	0.35	20.67
Cuprum (II) Oxide, CuO	0.46	-
Zinc Oxide, ZnO	0.38	7.19

Figure 9. X-ray Diffraction (XRD) curves of microalgae control (black line) and after flocculation (red line).

Figure 10. FTIR spectra of microalgae control and after flocculation process.